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Monday, October 15th, 2018

    Time Event
    7:09a
    MIT reshapes itself to shape the future

    MIT today announced a new $1 billion commitment to address the global opportunities and challenges presented by the prevalence of computing and the rise of artificial intelligence (AI). The initiative marks the single largest investment in computing and AI by an American academic institution, and will help position the United States to lead the world in preparing for the rapid evolution of computing and AI.

    At the heart of this endeavor will be the new MIT Stephen A. Schwarzman College of Computing, made possible by a $350 million foundational gift from Mr. Schwarzman, the chairman, CEO and co-founder of Blackstone, a leading global asset manager.

    Headquartered in a signature new building on MIT’s campus, the new MIT Schwarzman College of Computing will be an interdisciplinary hub for work in computer science, AI, data science, and related fields. The College will:

    • reorient MIT to bring the power of computing and AI to all fields of study at MIT, allowing the future of computing and AI to be shaped by insights from all other disciplines;
    • create 50 new faculty positions that will be located both within the College and jointly with other departments across MIT — nearly doubling MIT’s academic capability in computing and AI;
    • give MIT’s five schools a shared structure for collaborative education, research, and innovation in computing and AI;
    • educate students in every discipline to responsibly use and develop AI and computing technologies to help make a better world; and
    • transform education and research in public policy and ethical considerations relevant to computing and AI.

    With the MIT Schwarzman College of Computing’s founding, MIT seeks to strengthen its position as a key international player in the responsible and ethical evolution of technologies that are poised to fundamentally transform society. Amid a rapidly evolving geopolitical environment that is constantly being reshaped by technology, the College will have significant impact on our nation’s competitiveness and security.

    “As computing reshapes our world, MIT intends to help make sure it does so for the good of all,” says MIT President L. Rafael Reif. “In keeping with the scope of this challenge, we are reshaping MIT. The MIT Schwarzman College of Computing will constitute both a global center for computing research and education, and an intellectual foundry for powerful new AI tools. Just as important, the College will equip students and researchers in any discipline to use computing and AI to advance their disciplines and vice-versa, as well as to think critically about the human impact of their work. With uncommon insight and generosity, Mr. Schwarzman is enabling a bold agenda that will lead to a better world. I am deeply grateful for his commitment to our shared vision.”

    Stephen A. Schwarzman is chairman, CEO and co-founder of Blackstone, one of the world’s leading investment firms, with approximately $440 billion in assets under management. Mr. Schwarzman is an active philanthropist with a history of supporting education, culture, and the arts, among other things. Whether in business or philanthropy, he has dedicated himself to tackling global-scale problems, with transformative and paradigm-shifting solutions.

    This year, he gave $5 million to Harvard Business School to support the development of case studies and other programming that explore the implications of AI on industries and business. In 2015, Mr. Schwarzman donated $150 million to Yale University to establish the Schwarzman Center, a first-of-its-kind campus center in Yale’s historic Commons building. In 2013, he founded a highly selective international scholarship program, Schwarzman Scholars, at Tsinghua University in Beijing to educate future global leaders about China. At $578 million raised to date, the program is modeled on the Rhodes Scholarship and is the single largest philanthropic effort in China’s history coming largely from international donors.

    “There is no more important opportunity or challenge facing our nation than to responsibly harness the power of artificial intelligence so that we remain competitive globally and achieve breakthroughs that will improve our entire society,” Mr. Schwarzman says. “We face fundamental questions about how to ensure that technological advancements benefit all — especially those most vulnerable to the radical changes AI will inevitably bring to the nature of the workforce. MIT’s initiative will help America solve these challenges and continue to lead on computing and AI throughout the 21st century and beyond.”

    “As one of the world leaders in technological innovation, MIT has the right expertise and the right values to serve as the ‘true north’ of AI in pursuit of the answers we urgently need,” Mr. Schwarzman adds. “With the ability to bring together the best minds in AI research, development, and ethics, higher education is uniquely situated to be the incubator for solving these challenges in ways the private and public sectors cannot. Our hope is that this ambitious initiative serves as a clarion call to our government that massive financial investment in AI is necessary to ensure that America has a leading voice in shaping the future of these powerful and transformative technologies.”

    New college, structure, building, and faculty

    The MIT Schwarzman College of Computing represents the most significant structural change to MIT since the early 1950s, which saw the establishment of schools for management and for the humanities and social sciences:

    • The College is slated to open in Sept. 2019, with construction of a new building for the College scheduled to be completed in 2022.
    • Fifty new faculty positions will be created: 25 to be appointed to advance computing in the College, and 25 to be appointed jointly in the College and departments across MIT.
    • A new deanship will be established for the College.

    Today’s news follows a period of consultation of the MIT faculty led by President Reif, Provost Martin Schmidt, and Dean of the School of Engineering Anantha Chandrakasan. The chair of the faculty, Professor Susan Silbey, also participated in these consultations. Reif and Schmidt have also received letters of support for the College from academic leadership across MIT.

    “Because the journey we embark on today will be Institute-wide, we needed input from across MIT in order to establish the right vision,” Schmidt says. “Our planning benefited greatly from the imagination of many members of our community — and we will seek a great deal more input over the next year. By design, the College will not be a silo: It will be connective tissue for the whole Institute.”

    “I see exciting possibilities in this new structure,” says Melissa Nobles, dean of the MIT School of Humanities, Arts, and Social Sciences. “Faculty in a range of departments have a great deal to gain from new kinds of algorithmic tools — and a great deal of insight to offer their makers. Faculty in every school at MIT will be able to shape the work of the College.”

    At its meeting on Oct. 5, the MIT Corporation — MIT’s board of trustees — endorsed the establishment of the College.

    Corporation Chair Robert Millard says, “The new College positions MIT to lead in this important area, for the benefit of the United States and the world at large. In making this historic gift, Mr. Schwarzman has not only joined a select group of MIT’s most generous supporters, he has also helped give shape to a vision that will propel MIT into the future. We are all deeply grateful.”

    Empowering the pursuit of MIT’s mission

    The MIT Schwarzman College of Computing will aspire to excellence in MIT’s three main areas of work: education, research, and innovation:

    • The College will teach students the foundations of computing broadly and provide integrated curricula designed to satisfy the high level of interest in majors that cross computer science with other disciplines, and in learning how machine learning and data science can be applied to a variety of fields.
    • It will seek to enable advances along the full spectrum of research — from fundamental, curiosity-driven inquiry to research on market-ready applications, in a wide range of MIT departments, labs, centers, and initiatives.

    “As MIT’s partner in shaping the future of AI, IBM is excited by this new initiative,” says Ginni Rometty IBM chairman, president, and CEO. “The establishment of the MIT Schwarzman College of Computing is an unprecedented investment in the promise of this technology. It will build powerfully on the pioneering research taking place through the MIT-IBM Watson AI Lab. Together, we will continue to unlock the massive potential of AI and explore its ethical and economic impacts on society.”

    Sparking thought around policy and ethics

    The MIT Schwarzman College of Computing will seek to be not only a center of advances in computing, but also a place for teaching and research on relevant policy and ethics to better ensure that the groundbreaking technologies of the future are responsibly implemented in support of the greater good. To advance these priorities, the College will:

    • develop new curricula that will connect computer science and AI with other disciplines;
    • host forums to engage national leaders from business, government, academia, and journalism to examine the anticipated outcomes of advances in AI and machine learning, and to shape policies around the ethics of AI;
    • encourage scientists, engineers, and social scientists to collaborate on analysis of emerging technology, and on research that will serve industry, policymakers, and the broader research community; and
    • offer selective undergraduate research opportunities, graduate fellowships in ethics and AI, a seed-grant program for faculty, and a fellowship program to attract distinguished individuals from other universities, government, industry, and journalism.

    “Computing is no longer the domain of the experts alone. It’s everywhere, and it needs to be understood and mastered by almost everyone. In that context, for a host of reasons, society is uneasy about technology — and at MIT, that’s a signal we must take very seriously,” President Reif says. “Technological advancements must go hand in hand with the development of ethical guidelines that anticipate the risks of such enormously powerful innovations. This is why we must make sure that the leaders we graduate offer the world not only technological wizardry but also human wisdom — the cultural, ethical, and historical consciousness to use technology for the common good.”

    “The College’s attention to ethics matters enormously to me, because we will never realize the full potential of these advancements unless they are guided by a shared understanding of their moral implications for society,” Mr. Schwarzman says. “Advances in computing — and in AI in particular — have increasing power to alter the fabric of society. But left unchecked, these technologies could ultimately hurt more people than they help. We need to do everything we can to ensure all Americans can share in AI’s development. Universities are best positioned for fostering an environment in which everyone can embrace — not fear — the transformations ahead.”

    In its pursuit of ethical questions, the College will bring together researchers in a wide range of MIT departments, labs, centers, and initiatives, such as the Department of Electrical Engineering and Computer Science; the Computer Science and Artificial Intelligence Lab; the Institute for Data, Systems, and Society; the Operations Research Center; the Quest for Intelligence, and beyond.

    “There is no doubt that artificial intelligence and automation will impact every facet of society. As we look to the future, we must utilize these important technologies to shape our world for the better and harness their power as a force for social good,” says Darren Walker, president of the Ford Foundation. “I believe that MIT’s groundbreaking initiative, particularly its commitment to address policy and ethics alongside technological advancements, will play a crucial role in ensuring that AI is developed responsibly and used to make our world more just.”

    Building on history and breadth

    The MIT Schwarzman College of Computing will build on MIT’s legacy of excellence in computation and the study of intelligence. In the 1950s, MIT Professor Marvin Minsky and others created the very idea of artificial intelligence:

    • Today, Electrical Engineering and Computer Science (EECS) is by far the largest academic department at MIT. Forty percent of MIT’s most recent graduating class chose it, or a combination of it and another discipline, as their major. Its faculty boasts 10 of the 67 winners of the Turing Award, computing’s highest honor.
    • The largest laboratory at MIT is the Computer Science and Artificial Intelligence Laboratory, which was established in 2003 but has its roots in two pioneering MIT labs: the Artificial Intelligence Lab, established in 1959 to conduct pioneering research across a range of applications, and the Laboratory for Computer Science, established in 1963 to pursue a Department of Defense project for the development of a computer system accessible to a large number of people.
    • The College’s network function will rely on academic excellence across MIT. Outside of computer science and AI, the Institute hosts a high number of top-ranked departments, ready to be empowered by advances in these digital fields. U.S. News and World Report cites MIT as No. 1 in six graduate engineering specialties — and No. 1 in 17 disciplines and specialties outside of engineering, too, from biological sciences to economics.

    “A bold move to reshape the frontiers of computing is what you would expect from MIT,” says Eric Schmidt, former executive chairman of Alphabet and a visiting innovation fellow at MIT. “I’m especially excited about the MIT Schwarzman College of Computing, however, because it has such an obviously human agenda.” Schmidt also serves on the advisory boards of the MIT Quest for Intelligence and the MIT Work of the Future Task Force.

    “We count many MIT graduates among our team at Apple, and have long admired how the school and its alumni approach technology with humanity in mind. MIT’s decision to focus on computing and AI across the entire institution shows tremendous foresight that will drive students and the world toward a better future,” says Apple CEO Tim Cook.

    The path forward

    On top of Mr. Schwarzman’s gift, MIT has raised an additional $300 million in support, totaling $650 million of the $1 billion required for the College. Further fundraising is being actively pursued by MIT’s senior administration.

    Provost Schmidt has formed a committee to search for the College’s inaugural dean. He will also host forums in the coming days that will allow members of the MIT community to ask questions and offer suggestions about the College. The provost will work closely with the chair of the faculty and the dean of the School of Engineering to define the process for standing up the College.        

    “I am truly excited by the work ahead,” Schmidt says. “The MIT community will give shape and energy to the College we launch today.”

    7:30a
    FAQ on the newly established MIT Stephen A. Schwarzman College of Computing

    This set of FAQs offers information about the founding of the MIT Stephen A. Schwarzman College of Computing, announced today, and its implications for the MIT community and beyond.

    General questions

    Q: What is MIT announcing today that’s new?

    A: Today MIT is announcing a $1 billion commitment to address the global opportunities and challenges presented by the ubiquity of computing — across industries and academic disciplines — and by the rise of artificial intelligence. At the heart of this endeavor will be the new MIT Stephen A. Schwarzman College of Computing, made possible by a foundational $350 million gift from Stephen Schwarzman, the chairman, CEO, and co-founder of Blackstone, a leading global asset manager. An additional $300 million has been secured for the College through other fundraising.

    Q: Why is MIT creating this College?

    A: The Institute is creating the MIT Schwarzman College of Computing in response to clear trends both inside and outside MIT. Inside MIT, students are choosing in record numbers to study computer science, and departments across the Institute are creating joint majors with computer science and hiring faculty with expertise in computing. And externally, the digital fraction of the global economy has been growing much faster than the economy as a whole — and computing and AI are increasingly woven into every part of the global economy.

    Process and leadership

    Q: What will implementation look like?

    A: MIT will launch a task force prior to the College’s opening in September 2019. The task force will make recommendations to the MIT administration on details regarding the structure of the College; its academic appointments and faculty recruiting; and — in particular — how best to structure the College such that there are seamless interactions in research and teaching between the College and other MIT departments.

    Q: When will the College’s first dean be appointed? Do you have a list of leading candidates?

    A: The Institute is finalizing a search advisory committee, charged by Provost Martin Schmidt, and is beginning the search process. The committee will move forward with appropriate speed and due diligence to ensure that MIT is ready to launch the College in September 2019. 

    Q: Will the dean come from within MIT?

    A: MIT’s objective is to appoint the most highly qualified leader for this vitally important role. Such a leader may come from within MIT — but the best candidate may also come from outside the Institute. In support of the Institute and its mission, the dean will be responsible for ensuring the success of the College within the MIT community, across the broader MIT innovation ecosystem, and globally. 

    Q: I’m an MIT community member. How can I learn more and offer thoughts?

    A: Both the MIT Corporation and its Executive Committee recently approved the establishment of the new College. But its success will depend on feedback from people across MIT. To jumpstart that process, the Institute has scheduled a number of forums: 

    Faculty Forum
    Thursday, October 18, 5:30-6:30 p.m.
    Room 32-123

    Student Forum
    Thursday, October 25, 5:00-6:00 p.m.
    Room 32-123

    Staff Forum
    Thursday, October 25, 12:00-1:00 p.m.
    Room 4-270

    In the coming days, MIT will schedule a forum for alumni in the Boston area, as well as one or more webcasts to reach alumni in other regions and time zones. Every forum will include time for questions. To focus the conversations, members of the community are invited to email CollegeofComputingQuestions@mit.edu with questions or concerns.

    Impact on MIT

    Q: Why is this a college, rather than a school? What is the difference?

    A: The MIT Schwarzman College of Computing will work with and across all five of MIT’s existing schools. Its naming as a college differentiates it from the five schools, and signals that it is an Institute-wide entity: The College is designed with cross-cutting education and research as its primary missions.

    Q: Why, and how, will the College connect to the schools and other parts of MIT?

    A: As MIT’s senior leaders have engaged with faculty and departments across campus, many have spoken of how their fields are being transformed by modern computational methods — specifically, by access to large data sets and the tools to learn from them. Some of the most exciting new work in fields like political science, economics, linguistics, anthropology, and urban studies — as well as in various disciplines in science and engineering — is being made possible when advanced computational capabilities are brought to these fields.

    The key connector of the College to MIT’s five schools with be the 25 “bridge” faculty: joint faculty appointments linking the College with departments across MIT. With this new structure, MIT aims to educate students who are “bilingual” — adept in computing, as well as in their primary field. The College will also connect with the rest of MIT through its work to develop shared computing resources — infrastructure, instrumentation, and technical staffing.

    Q: Which existing MIT units will move into the College?

    A: It is expected that the Department of Electrical Engineering and Computer Science (EECS), the Computer Science and Artificial Intelligence Laboratory (CSAIL), the Institute for Data, Systems, and Society (IDSS), and the MIT Quest for Intelligence will all become part of the new College; other units may join the College. EECS (and in particular, the electrical engineering part of the department) will naturally continue to have a strong relationship with the School of Engineering, its current home. A set of faculty committees will be swiftly established to define the relationship between EECS, the School of Engineering, and the new College of Computing, as well as the range of future degree offerings.

    Q: What changes for MIT with this new College? Is this just a restructuring?

    A: The founding of the MIT Schwarzman College of Computing is the most significant structural change since 1950, when MIT established the Sloan School of Management and the School of Humanities, Arts, and Social Sciences. But this is much more than a restructuring: With this change, MIT seeks to position itself as a key player in the responsible and ethical evolution of technologies that will fundamentally transform society.

    The College will reorient MIT to bring the power of computing and AI to all fields of study — and, in turn, to allow the future direction of computing and AI to be shaped by insights from all of these other disciplines, including the humanities. By design, the MIT Schwarzman College of Computing will be the connective tissue for the entire Institute, integrating AI studies and research with disciplines throughout MIT to a degree and with an intensity that, it is believed, is unmatched anywhere else.

    Q: The College has been described as a $1 billion endeavor. Where will that $1 billion come from, and how will it be spent?

    A: The estimated $1 billion cost to create the College will pay to construct a new building, expected to be complete around 2022; to create an endowment to support the 50 new faculty positions; and to fund computing resources to support teaching and research in the College and across MIT. The hiring of these new faculty, when complete in approximately five years, will represent a 5 percent growth in the Institute’s total faculty. Including the founding $350 million gift from Mr. Schwarzman, MIT has already secured 65 percent of the funds needed to support launch of the College.

    Q: How will this College impact MIT’s budget on an ongoing basis?

    A: A guiding principle of MIT’s planning is that the College should not dilute the resources of any other part of the Institute. This is why MIT is engaging in new fundraising to secure the remaining part of the estimated $1 billion needed to house the College and to endow its faculty.

    Impact on students and alumni

    Q: Do you expect that this new structure could change the balance of undergraduate majors at MIT?

    A: About 40 percent of MIT undergraduates now major either in computer science alone or in joint programs combining computer science with some other field. It is expected that this new structure will allow interested students to gain a strong background in computer science while also focusing on a paired discipline that’s of greatest interest to them. By greatly expanding the range of disciplines that can be paired with computer science in a coherent undergraduate degree, this move will support MIT’s students in their clear desire to combine computer science with other fields where they might eventually apply their computing skills.

    Q: Will the undergraduate class size be increased?

    A: This remains to be determined. However, it is expected that the Institute’s population of graduate students will naturally grow with the addition of 50 new faculty positions.

    Q: Will current students be able to switch to the College?

    A: In general, MIT students are part of the school or college that is home to their academic program. Because the Department of Electrical Engineering and Computer Science (EECS) will become part of the new College, it is expected that the majority of EECS students will automatically become students within the new College. Students within MIT’s five other schools will, of course, be able to access the College’s faculty, courses, and facilities: Indeed, the College’s cross-Institute structure is intended to make it accessible to students across MIT, and there may be opportunities for students to be affiliated with both the College and their home department and school.

    Q: I'm a joint major in computer science and another discipline. How will this new College affect my course selection, and my degree?

    A: There should be no effect.

    Q: I’m an EECS alum. How will this new College affect my degree?

    A: You will continue to hold your MIT degree in your discipline. The creation of the College does not change your degree. This expanded footprint for computing at MIT is expected to enhance the stature of all computing-related fields at MIT.

    Impact on faculty

    Q: How many new faculty positions will be created with the launch of the College?

    A: Fifty faculty positions will be added over the next five years. It’s expected that 25 of these faculty positions will be located fully within the new MIT Schwarzman College of Computing; the other 25 new faculty will hold “bridge” positions — dual appointments between the College and academic departments located in any of MIT’s five schools.

    Q: I’m a faculty member whose field has little connection to computing or AI. How will this new College affect my position at MIT?

    A: While MIT believes this new opportunity brings much possibility for all faculty, engagement with the new College will be entirely voluntary. Faculty who do not wish to engage more deeply with computing or AI will not be required to do so.

    Q: What kinds of new joint academic programs or degrees are envisioned?

    A: MIT has been making progress in this direction for some time; for example, we already offer undergraduate majors that pair computer science with economics, biology, mathematics, and urban planning. The MIT Schwarzman College of Computing will allow MIT to respond to the student demand the Institute is seeing in course and major/minor selection more effectively and creatively. It will enable MIT to pursue this vision with unprecedented depth and ambition, and will give MIT’s five schools a shared structure for collaborative education, research, and innovation in computing and AI.

    Impact on the physical campus

    Q: What is the timeline on construction of a new building for the College? Where will the building be located? Has an architect been selected?

    A: The building is expected to be complete by 2022. Many details about the building, including its location on campus, have yet to be finalized. An architect has not been selected.

    Q: How big will the new building be?

    A: Given the expected growth of the MIT faculty with the launch of the MIT Schwarzman College of Computing, it is currently projected that the new building will house office and laboratory space for about 65 faculty members and their research groups and affiliated staff. This will likely translate to a building of 150,000 to 165,000 square feet. (For comparison purposes, MIT.nano is 200,000 square feet.)

    Q: Who will move into the new building?

    A: This remains to be determined. However, not all new MIT Schwarzman College of Computing faculty members will be in the new building, and it is expected that some existing faculty members will move there.

    The College’s focus

    Q: AI encompasses a broad range of areas, from self-driving cars to robotics. Is MIT’s goal to be a leader in all the major AI areas? Are there specific areas the College will focus on?

    A: It is hoped and expected that the MIT Schwarzman College of Computing will become a convening force for all of the fields that center on computing and AI. However, the focus of the new College within these fields will be shaped largely by its first dean and by its academic leadership.

    Q: Will the new College partner with AI research companies?

    A: Numerous such companies are already part of MIT’s broader innovation ecosystem in Kendall Square, and the Institute will continue to collaborate with them. It is fair to assume that projects and research generated by the College will be of interest to industry, and will have commercial relevance. Additionally, it is expected that the “bilingual” graduates who emerge from this new College — combining competence in computing and in other fields — will be of enormous value to employers.

    Q: What ethical concerns does MIT have about AI or specific areas of AI research?

    A: Advances in computing, and artificial intelligence in particular, have the power to alter the fabric of society. The MIT Schwarzman College of Computing aims to be not only a center of advances in computing, but also a place for teaching and research on relevant policy and ethics — to better ensure that the pioneering technologies of the future are responsibly implemented in support of the greater good.

    Q: What kind of programs will there be around ethics and advances in computing?

    A: Launching the College will involve both an expansion of existing programs and the creation of entirely new ones — with some of these new programs exploring the intersection of ethics and computing. Within this space, the College will offer prestigious undergraduate research opportunities, graduate fellowships in ethics and AI, a seed-grant program for faculty, and a fellowship program to attract distinguished individuals from other universities, government, industry, and journalism.

    Q: Why is this focus on ethics important?

    A: Technologies reflect the values of those who make them. For this reason, technological advancements must be accompanied by the development of ethical guidelines that anticipate the risks of such enormously powerful innovations. MIT must make sure that the leaders who graduate from the Institute offer the world both technological proficiency and human wisdom — the cultural, ethical, and historical consciousness to use technology for the common good. MIT is founding the College, in part, to educate students in every discipline to responsibly use and develop AI and computing technologies to help make a better world. 

    Q: At a time of growing economic disparities, there are deep concerns that AI will begin to replace humans and take over their jobs. How will MIT address such issues?

    A: AI and related technologies are poised to become a source of new wealth and industries. Together with that, however, is the risk of severe economic dislocation for individuals, communities, and entire nations. Reinventing the future of work must be a society-wide effort — and finding long-term solutions to issues arising from the deployment of AI will require ideas and initiative from every quarter.

    The College will unite expertise at the intersection of computing and the society it serves. Joining scientists and engineers with social scientists, it will produce analysis of emerging technology; this research will serve industry, policymakers, and the broader research community. Some of the graduate students who conduct research in policy and ethics may go on to fill critical roles in government and at technology companies.

    Additionally, MIT’s Task Force on the Work of the Future, launched in February 2018, is an Institute-wide effort to understand and shape the evolution of jobs during the current age of innovation. It aims to shed new light on the linked evolution of technology and human work, and will issue findings guiding the development and implementation of policy, to suggest how society can continue to offer broad opportunity and prosperity.

    Q: Are there any AI areas in which MIT would not participate because of ethical concerns? 

    A: Yes. In every action it takes, the Institute must understand whether its participation benefits society. Defining these boundaries will be the work of the College’s new leadership.

    8:10a
    Letter to the MIT community regarding the MIT Stephen A. Schwarzman College of Computing

    The following email was sent today to the MIT community by President L. Rafael Reif.

    To the members of the MIT community,

    The 2010 history, Becoming MIT: Moments of Decision, credits MIT’s record of rising impact to turning points when, responding to new challenges, MIT stayed true to its mission with a calculated change of course.

    Today, at a turning point of equal consequence, we launch the MIT Stephen A. Schwarzman College of Computing.

    This new College is our strategic response to a global phenomenon — the ubiquity of computing and the rise of AI. In this new world, we are building on MIT’s established leadership in these fields to position the Institute for decades to come as a world hub of education, research and innovation, and to prepare our students to lead in every domain.

    To state the obvious, AI in particular is reshaping geopolitics, our economy, our daily lives and the very definition of work. It is rapidly enabling new research in every discipline and new solutions to daunting problems. At the same time, it is creating ethical strains and human consequences our society is not yet equipped to control or withstand.

    In response, we are reshaping MIT.

    By giving MIT’s five Schools a shared structure for collaborative education, research and innovation, the MIT Schwarzman College of Computing aims to:

    • foster breakthroughs in computing, particularly artificial intelligence — actively informed by the wisdom of other disciplines;
    • deliver the power of AI tools to researchers in every field; and
    • advance pioneering work on AI’s ethical use and societal impact.

    Most distinctively, by adding new integrated curricula and degree programs in nearly every field, the College will equip students to be as fluent in computing and AI as they are in their own disciplines — and ready to use these digital tools wisely and humanely to help make a better world.

    To be clear: In this pivotal AI moment, society has never needed the liberal arts — the path to wise, responsible citizenship — more than it does now. It is time to educate a new generation of technologists in the public interest.

    You can read more about the vision for the MIT Schwarzman College of Computing here, and you can find answers to questions of interest to faculty, students, staff and alumni here.

    How did the MIT Schwarzman College of Computing come to be?

    More than a year ago, inspired by the remarkable tide of student interest in majors with computing in the title, we began a process of assessment and exploration with the Executive Committee of the MIT Corporation. This quickly expanded to include faculty leadership in every department, including department heads, the School Councils and Academic Council. Faculty Chair Susan Silbey deserves immense credit for the nature and success of this consultative process. We have also gained key insights from Corporation members, students, staff and alumni. Together these conversations crystallized the need for bold action, at scale and with speed.

    And so we arrived at the idea we announce as the MIT Schwarzman College of Computing — the most profound restructuring of MIT since the early 1950s. This $1 billion commitment will include a dedicated new building on campus, a new dean and a near doubling of our academic capability in computing and especially AI, with 50 new faculty positions located within the College and jointly with departments across MIT.

    Such a bold step requires a bold partner. We are extremely fortunate to have the encouragement, insight and visionary support of one of the world’s most farsighted investors, Stephen A. Schwarzman, chairman, CEO and co-founder of Blackstone. His magnificent generosity — a gift of $350 million — gave us the power to take decisive action.

    What happens now?

    Both the MIT Corporation and its Executive Committee recently approved the establishment of the new College.

    It is still, however, a very young idea ­— a prototype we are improving day by day. Its success will depend on thoughtful refinement and creative problem-solving from people across MIT. To jumpstart that feedback process, we have scheduled a number of forums:

    Faculty Forum
    October 18, 5:30–6:30 PM
    Bldg. 32-123

    Student Forum
    October 25, 5:00–6:00 PM
    Bldg. 32-123

    Staff Forum
    October 25, Noon–1:00 PM
    Bldg. 4-270

    In the coming days, we will schedule a forum for alumni in the metro-Boston area, as well as one or more webcasts to reach alumni in other regions and time zones.

    Every forum will include lots of time for questions. To focus the conversation and guide our thinking, I hope that you will let us know here what questions interest or concern you the most.

    In addition, faculty will receive an email from the Provost today describing the next steps in implementation and our search for a dean. The October 17th Faculty Meeting will also include discussion of the new College.

    *                *                *

    As we begin this fresh chapter, I offer thanks to everyone who helped bring us to this day. For shepherding the development of this transformative idea, we owe special gratitude to Provost Marty Schmidt, Dean of Engineering Anantha Chandrakasan and Executive Vice President and Treasurer Israel Ruiz.  

    If we hope to make a better world, we must constantly work to make a better MIT. As humanity faces the opportunities and risks of the digital future, the reshaping we begin on campus today will challenge us to think deeply about how the technologies we invent can best serve, support and care for our global human family.

    I look forward to joining you all in this profoundly important work.

    In enthusiastic anticipation,

    L. Rafael Reif

    8:58a
    Provost's letter to the faculty about the MIT Stephen A. Schwarzman College of Computing

    The following email was sent today to the MIT faculty from Provost Martin Schmidt.

    Dear colleagues,

    As I trust you have seen, this morning Rafael wrote to the community to announce the creation of the MIT Stephen A. Schwarzman College of Computing. This is an historic day for the Institute.

    The idea for the College emerged from a process of consultation the administration conducted over the past year. In that time, we consulted with many faculty members, both on School Councils and in some departments with significant computing activities. How to handle the explosive growth in student interest in computing, on its own and across other disciplines, has been an administrative concern for some time. As we’ve seen in the sharp rise in majors “with CS,” individual departments have worked hard to respond. But through more than a year’s worth of thoughtful input from many stakeholders, we came to see that if MIT could take a single bold step at scale, we could create important new opportunities for our community.

    A central idea behind the College is that a new, shared structure can help deliver the power of computing, and especially AI, to all disciplines at MIT, lead to the development of new disciplines, and provide every discipline with an active channel to help shape the work of computing itself. Among those we have consulted so far, I sense a deep excitement for the power of this idea.

    Opportunities for input

    Today’s announcement has defined a vision for this College. Now, to realize its full potential, we are eager to launch a process that includes even more voices and perspectives. As a very first step, Rafael announced a set of community forums where we will share more detail on the vision and a process for moving forward. I hope you will join us for the faculty forum — October 18, 5:30–6:30 PM in 32-123 — so that we can learn from your feedback. The October 17th Faculty Meeting will also include discussion of the new College.

    The search for the Dean of the MIT Schwarzman College of Computing

    One immediate step is the search for the College’s inaugural dean. I am grateful to Institute Professor Ronald L. Rivest for agreeing to chair the search, and I am in the process of finalizing a search committee; we will announce the membership soon. I will ask the committee to recommend a short list of the best internal and external candidates by the end of November. It’s important that we work efficiently together to appoint a dean in the coming months, so that the new dean will be able to participle fully in implementing all aspects of the College.

    I invite you to share your advice with the committee, including your suggestions for candidates for this important position, by sending email to CollegeOfComputingImplementation@mit.edu. All correspondence will be kept confidential.

    The process moving forward

    The Chair of the Faculty Susan Silbey and I have discussed ideas for the best process moving forward. Even as we conduct a search for the new dean of the College, we can begin to make progress on several fronts.

    At this point, we believe we could form a number of working groups to advise the administration on important details of creating the College, perhaps following the process MIT used during the 2008 budget crisis, which actively engaged all key stakeholders at the Institute. The working groups can evaluate options and make recommendations on issues like the detailed structure of the college, how faculty appointments will be made, and how we envision new degrees and instructional support that cut across the Institute. Again, we welcome your comments, questions, and insights as we move forward with this process. Please feel free to contribute any input via CollegeOfComputingImplementation@mit.edu.

    We have much work ahead of us, and I look forward to the excitement and challenge of writing this new chapter of the Institute’s history. I welcome your feedback and advice.

    With my best regards,

    Marty

    11:00a
    When light, not heat, causes melting

    The way that ordinary materials undergo a phase change, such as melting or freezing, has been studied in great detail. Now, a team of researchers has observed that when they trigger a phase change by using intense pulses of laser light, instead of by changing the temperature, the process occurs very differently.

    Scientists had long suspected that this may be the case, but the process has not been observed and confirmed until now. With this new understanding, researchers may be able to harness the mechanism for use in new kinds of optoelectronic devices.

    The unusual findings are reported today in the journal Nature Physics. The team was led by Nuh Gedik, a professor of physics at MIT, with graduate student Alfred Zong, postdoc Anshul Kogar, and 16 others at MIT, Stanford University, and Skolkovo Institute of Science and Technology (Skoltech) in Russia.

    For this study, instead of using an actual crystal such as ice, the team used an electronic analog called a charge density wave — a frozen electron density modulation within a solid — that closely mimics the characteristics of a crystalline solid.

    While typical melting behavior in a material like ice proceeds in a relatively uniform way through the material, when the melting is induced in the charge density wave by ultrafast laser pulses, the process worked quite differently. The researchers found that during the optically induced melting, the phase change proceeds by generating many singularities in the material, known as topological defects, and these in turn affect the ensuing dynamics of electrons and lattice atoms in the material.

    These topological defects, Gedik explains, are analogous to tiny vortices, or eddies, that arise in liquids such as water. The key to observing this unique melting process was the use of a set of extremely high-speed and accurate measurement techniques to catch the process in action.

    The fast laser pulse, less than a picoseond long (trillionths of a second), simulates the kind of rapid phase changes that occur. One example of a fast phase transition is quenching — such as suddenly plunging a piece of semimolten red-hot iron into water to cool it off almost instantly. This process differs from the way materials change through gradual heating or cooling, where they have enough time to reach equilibrium — that is, to reach a uniform temperature throughout — at each stage of the temperature change.

    While these optically induced phase changes have been observed before, the exact mechanism through which they proceed was not known, Gedik says.

    The team used a combination of three techniques, known as ultrafast electron diffraction, transient reflectivity, and time- and angle-resolved photoemission spectroscopy, to simultaneously observe the response to the laser pulse. For their study, they used a compound of lanthanum and tellurium, LaTe3, which is known to host charge density waves. Together, these instruments make it possible to track the motions of electrons and atoms within the material as they change and respond to the pulse.

    Video above shows electron diffraction from the sample being studied. The smaller white spots close on either side of the central dot show the charge density wave, which is analogous to a crystal structure, as it "melts" when hit with an ultrafast laser pulse, and then "refreezes."

    Energy bands in the material are depicted in this video, where the density of high-energy electrons is plotted versus their momentum. Bright bands that appear and then disappear correspond to the decrease in order (melting) and the reappearance of that order (freezing).

    In the experiments, Gedik says, “we can watch, and make a movie of, the electrons and the atoms as the charge density wave is melting,” and then continue watching as the orderly structure then resolidifies. The researchers were able to clearly observe and confirm the existence of these vortex-like topological defects.

    They also found that the time for resolidifying, which involves the dissolution of these defects, is not uniform, but takes place on multiple timescales. The intensity, or amplitude, of the charge density wave recovers much more rapidly than does the orderliness of the lattice. This observation was only possible with the suite of time-resolved techniques used in the study, with each providing a unique perspective.

    Zong says that a next step in the research will be to try to determine how they can “engineer these defects in a controlled way.” Potentially, that could be used as a data-storage system, “using these light pulses to write defects into the system, and then another pulse to erase them.”

    Peter Baum, a professor of physics at the University of Konstanz in Germany, who was not connected to this research, says “This is great work. One awesome aspect is that three almost entirely different, complicated methodologies have been combined to solve a critical question in ultrafast physics, by looking from multiple perspectives.”

    Baum adds that “the results are important for condensed-matter physics and their quest for novel materials, even if they are laser-excited and exist only for a fraction of a second.”

    The work was carried out in collaboration between researchers at MIT, Stanford University, and Skoltech. It was supported by the U.S. Department of Energy, the Gordon and Betty Moore Foundation, the Army Research Office, and the Skoltech NGP Program.

    2:40p
    In pursuit of the elusive stem cell

    How does the body renew itself? How do cancer cells use the same or similar processes to form tumors and spread throughout the body? How might we use those processes to heal injuries or fight cancer?

    A new research program at MIT is tackling fundamental biological questions about normal adult stem cells and their malignant counterparts, cancer stem cells. Launched last spring with support from Fondation MIT, the MIT Stem Cell Initiative is headed by Jacqueline Lees, the Virginia and D.K. Ludwig Professor of Cancer Research, professor of biology, and associate director of the Koch Institute for Integrative Cancer Research. Other founding members of the initiative are Robert Weinberg, a professor of biology, Whitehead Institute member, and director of the Ludwig Center at MIT; and Omer Yilmaz, an assistant professor of biology.

    Rare power

    Normal adult stem cells have been defined for more than a half-century. Relatively rare, they are undifferentiated cells within a tissue that divide to produce two daughter cells. One remains in the stem cell state to maintain the stem cell population, a process called self-renewal. The second daughter cell adopts a partially differentiated state, then goes on to divide and differentiate further to yield multiple cell types that form that tissue. In many fully formed adult tissues, normal stem cells divide periodically to replenish or repair the tissue. Importantly, this division is a carefully controlled process to ensure that tissues are restricted to the appropriate size and cell content.

    Cancer stem cells are also of long-standing interest and share many similarities with normal adult stem cells. They perform the same division but, rather than differentiating, the additional cells produced by the second daughter cell amass to form the bulk of the tumor. Following surgery or treatment, cancer stem cells can regrow the tumor — and are frequently resistant to chemotherapy — making them especially dangerous. This unique ability of normal and cancer stem cells to both self-renew and form a tissue or tumor is referred to by researchers as “stemness,” and has important implications for biomedical applications.

    Because of the key role they play in tissue maintenance and regeneration, normal stem cells hold great promise for use in repairing damaged tissues. Cancer stem cells, correspondingly, are the lifeblood of tumors. Although relatively rare within tumors, they are particularly important because they possess the ability to create tumors and are also chemotherapy-resistant. As a result, cancer stem cells are thought to be responsible for tumor recurrence after remission, and also for the formation of metastases, which account for the majority of cancer-associated deaths. Accordingly, an anti-cancer stem cell therapy that can target and kill cancer stem cells is one of the holy grails of cancer treatment — a means to suppress both tumor recurrence and metastatic disease.

    Hiding in plain sight

    One of the fundamental challenges to studying normal and cancer stem cells, and to ultimately harnessing that knowledge, is developing the ability to identify, purify, and propagate these cells. This has often proved tricky, as another key similarity between normal and cancer stem cells is that neither is visibly different from other cells in a tissue or tumor. Thus, a major goal in stem cell and cancer stem cell research is finding ways to distinguish these rare specimens from other cells, ideally by identifying unique surface markers that can be used to purify stem cell and cancer stem cell populations and enable their study.

    The MIT Stem Cell Initiative is applying new technologies and approaches in pursuit of this goal. More specifically, the program aims to:

    • identify the stem cells and cancer stem cells in various tissues and tumor types;
    • determine how these cells change during aging (in the case of normal stem cells) or with disease progression (in the case of degenerative conditions and cancer); and
    • determine the similarities and differences between normal and cancer stem cells, with the goal of finding vulnerabilities in cancer stem cells that can be viable and specific targets for treatment. 


    Ultimately, the ability to identify, purify, and establish various populations of stem cells and cancer stem cells could help researchers better understand the biology of these cells, and learn how to utilize them more effectively in regenerative medicine applications and target them in cancer.

    When biology meets technology

    MIT Stem Cell Initiative studies focus on normal and cancer stem cells of epithelial tissues. Epithelia are one of four general tissue types in the body; they line most organs and are where the vast majority of cancers arise. Epithelial cells from different organs share some biological properties, but also have distinct differences reflecting the organ’s specific role and/or environment. In particular, the MIT Stem Cell Initiative has focused on the breast and colon, as these tissues are quite different from each other, yet each constitutes a major portion of cancer incidence.

    New technologies are enabling the researchers to make significant headway in these investigations, progress that was not feasible just a few years ago. Specifically, they are using a combination of specially cultured cells, sophisticated and highly controllable mouse models of cancer, and single-cell RNA sequencing and computational analysis techniques that are uniquely suited to extracting a great deal of information from the relatively small number of stem cells.

    While breast and colon work is ongoing, MIT Stem Cell Initiative members are planning studies of additional tissues and recruiting collaborators for pilot projects. The results of the researchers’ studies will advance understandings of stem cell regulation and may ultimately lead to advances in tissue regeneration and/or cancer analysis and treatment.

    3:03p
    Technique quickly identifies extreme event statistics

    Seafaring vessels and offshore platforms endure a constant battery of waves and currents. Over decades of operation, these structures can, without warning, meet head-on with a rogue wave, freak storm, or some other extreme event, with potentially damaging consequences.

    Now engineers at MIT have developed an algorithm that quickly pinpoints the types of extreme events that are likely to occur in a complex system, such as an ocean environment, where waves of varying magnitudes, lengths, and heights can create stress and pressure on a ship or offshore platform. The researchers can simulate the forces and stresses that extreme events — in the form of waves — may generate on a particular structure.

    Compared with traditional methods, the team’s technique provides a much faster, more accurate risk assessment for systems that are likely to endure an extreme event at some point during their expected lifetime, by taking into account not only the statistical nature of the phenomenon but also the underlying dynamics.

    “With our approach, you can assess, from the preliminary design phase, how a structure will behave not to one wave but to the overall collection or family of waves that can hit this structure,” says Themistoklis Sapsis, associate professor of mechanical and ocean engineering at MIT. “You can better design your structure so that you don’t have structural problems or stresses that surpass a certain limit.”

    Sapsis says that the technique is not limited to ships and ocean platforms, but can be applied to any complex system that is vulnerable to extreme events. For instance, the method may be used to identify the type of storms that can generate severe flooding in a city, and where that flooding may occur. It could also be used to estimate the types of electrical overloads that could cause blackouts, and where those blackouts would occur throughout a city’s power grid.

    Sapsis and Mustafa Mohamad, a former graduate student in Sapsis’ group, currently assistant research scientist at Courant Institute of Mathematical Sciences at New York University, are publishing their results this week in the Proceedings of the National Academy of Sciences.

    Bypassing a shortcut

    Engineers typically gauge a structure’s endurance to extreme events by using computationally intensive simulations to model a structure’s response to, for instance, a wave coming from a particular direction, with a certain height, length, and speed. These simulations are highly complex, as they model not just the wave of interest but also its interaction with the structure. By simulating the entire “wave field” as a particular wave rolls in, engineers can then estimate how a structure might be rocked and pushed by a particular wave, and what resulting forces and stresses may cause damage.

    These risk assessment simulations are incredibly precise and in an ideal situation might predict how a structure would react to every single possible wave type, whether extreme or not. But such precision would require engineers to simulate millions of waves, with different parameters such as height and length scale — a process that could take months to compute. 

    “That’s an insanely expensive problem,” Sapsis says. “To simulate one possible wave that can occur over 100 seconds, it takes a modern graphic processor unit, which is very fast, about 24 hours. We’re interested to understand what is the probability of an extreme event over 100 years.”

    As a more practical shortcut, engineers use these simulators to run just a few scenarios, choosing to simulate several random wave types that they think might cause maximum damage. If a structural design survives these extreme, randomly generated waves, engineers assume the design will stand up against similar extreme events in the ocean.

    But in choosing random waves to simulate, Sapsis says, engineers may miss other less obvious scenarios, such as combinations of medium-sized waves, or a wave with a certain slope that could develop into a damaging extreme event.

    “What we have managed to do is to abandon this random sampling logic,” Sapsis says.

    A fast learner

    Instead of running millions of waves or even several randomly chosen waves through a computationally intensive simulation, Sapsis and Mohamad developed a machine-learning algorithm to first quickly identify the “most important” or “most informative” wave to run through such a simulation.

    The algorithm is based on the idea that each wave has a certain probability of contributing to an extreme event on the structure. The probability itself has some uncertainty, or error, since it represents the effect of a complex dynamical system. Moreover, some waves are more certain to contribute to an extreme event over others.

    The researchers designed the algorithm so that they can quickly feed in various types of waves and their physical properties, along with their known effects on a theoretical offshore platform. From the known waves that the researchers plug into the algorithm, it can essentially “learn” and make a rough estimate of how the platform will behave in response to any unknown wave. Through this machine-learning step, the algorithm learns how the offshore structure behaves over all possible waves. It then identifies a particular wave that maximally reduces the error of the probability for extreme events. This wave has a high probability of occuring and leads to an extreme event. In this way the algorithm goes beyond a purely statistical approach and takes into account the dynamical behavior of the system under consideration.

    The researchers tested the algorithm on a theoretical scenario involving a simplified offshore platform subjected to incoming waves. The team started out by plugging four typical waves into the machine-learning algorithm, including the waves’ known effects on an offshore platform. From this, the algorithm quickly identified the dimensions of a new wave that has a high probability of occurring, and it maximally reduces the error for the probability of an extreme event.

    The team then plugged this wave into a more computationally intensive, open-source simulation to model the response of a simplified offshore platform. They fed the results of this first simulation back into their algorithm to identify the next best wave to simulate, and repeated the entire process. In total, the group ran 16 simulations over several days to model a platform’s behavior under various extreme events. In comparison, the researchers carried out simulations using a more conventional method, in which they blindly simulated as many waves as possible, and were able to generate similar statistical results only after running thousands of scenarios over several months.

    MIT researchers simulated the behavior of a simplified offshore platform in response to the waves that are most likely to contribute to an extreme event. Courtesy of the researchers

    Sapsis says the results demonstrate that the team’s method quickly hones in on the waves that are most certain to be involved in an extreme event, and provides designers with more informed, realistic scenarios to simulate, in order to test the endurance of not just offshore platforms, but also power grids and flood-prone regions.

    “This method paves the way to perform risk assessment, design, and optimization of complex systems based on extreme events statistics, which is something that has not been considered or done before without severe simplifications,” Sapsis says. “We’re now in a position where we can say, using ideas like this, you can understand and optimize your system, according to risk criteria to extreme events.”

    This research was supported, in part, by the Office of Naval Research, Army Research Office, and Air Force Office of Scientific Research, and was initiated through a grant from the American Bureau of Shipping.

    3:03p
    Computer model offers more control over protein design

    Designing synthetic proteins that can act as drugs for cancer or other diseases can be a tedious process: It generally involves creating a library of millions of proteins, then screening the library to find proteins that bind the correct target.

    MIT biologists have now come up with a more refined approach in which they use computer modeling to predict how different protein sequences will interact with the target. This strategy generates a larger number of candidates and also offers greater control over a variety of protein traits, says Amy Keating, a professor of biology and biological engineering and the leader of the research team.

    “Our method gives you a much bigger playing field where you can select solutions that are very different from one another and are going to have different strengths and liabilities,” she says. “Our hope is that we can provide a broader range of possible solutions to increase the throughput of those initial hits into useful, functional molecules.”

    In a paper appearing in the Proceedings of the National Academy of Sciences the week of Oct. 15, Keating and her colleagues used this approach to generate several peptides that can target different members of a protein family called Bcl-2, which help to drive cancer growth.

    Recent PhD recipients Justin Jenson and Vincent Xue are the lead authors of the paper. Other authors are postdoc Tirtha Mandal, former lab technician Lindsey Stretz, and former postdoc Lothar Reich.

    Modeling interactions

    Protein drugs, also called biopharmaceuticals, are a rapidly growing class of drugs that hold promise for treating a wide range of diseases. The usual method for identifying such drugs is to screen millions of proteins, either randomly chosen or selected by creating variants of protein sequences already shown to be promising candidates. This involves engineering viruses or yeast to produce each of the proteins, then exposing them to the target to see which ones bind the best.

    “That is the standard approach: Either completely randomly, or with some prior knowledge, design a library of proteins, and then go fishing in the library to pull out the most promising members,” Keating says.

    While that method works well, it usually produces proteins that are optimized for only a single trait: how well it binds to the target. It does not allow for any control over other features that could be useful, such as traits that contribute to a protein’s ability to get into cells or its tendency to provoke an immune response.

    “There’s no obvious way to do that kind of thing — specify a positively charged peptide, for example — using the brute force library screening,” Keating says.

    Another desirable feature is the ability to identify proteins that bind tightly to their target but not to similar targets, which helps to ensure that drugs do not have unintended side effects. The standard approach does allow researchers to do this, but the experiments become more cumbersome, Keating says.

    The new strategy involves first creating a computer model that can relate peptide sequences to their binding affinity for the target protein. To create this model, the researchers first chose about 10,000 peptides, each 23 amino acids in length and helical in structure, and tested their binding to three different members of the Bcl-2 family. They intentionally chose some sequences they already knew would bind well, plus others they knew would not, so the model could incorporate data about a range of binding abilities.

    From this set of data, the model can produce a “landscape” of how each peptide sequence interacts with each target. The researchers can then use the model to predict how other sequences will interact with the targets, and generate peptides that meet the desired criteria.

    Using this model, the researchers produced 36 peptides that were predicted to tightly bind one family member but not the other two. All of the candidates performed extremely well when the researchers tested them experimentally, so they tried a more difficult problem: identifying proteins that bind to two of the members but not the third. Many of these proteins were also successful.

    “This approach represents a shift from posing a very specific problem and then designing an experiment to solve it, to investing some work up front to generate this landscape of how sequence is related to function, capturing the landscape in a model, and then being able to explore it at will for multiple properties,” Keating says.

    Sagar Khare, an associate professor of chemistry and chemical biology at Rutgers University, says the new approach is impressive in its ability to discriminate between closely related protein targets.

    “Selectivity of drugs is critical for minimizing off-target effects, and often selectivity is very difficult to encode because there are so many similar-looking molecular competitors that will also bind the drug apart from the intended target. This work shows how to encode this selectivity in the design itself,” says Khare, who was not involved in the research. “Applications in the development of therapeutic peptides will almost certainly ensue.” 

    Selective drugs

    Members of the Bcl-2 protein family play an important role in regulating programmed cell death. Dysregulation of these proteins can inhibit cell death, helping tumors to grow unchecked, so many drug companies have been working on developing drugs that target this protein family. For such drugs to be effective, it may be important for them to target just one of the proteins, because disrupting all of them could cause harmful side effects in healthy cells.

    “In many cases, cancer cells seem to be using just one or two members of the family to promote cell survival,” Keating says. “In general, it is acknowledged that having a panel of selective agents would be much better than a crude tool that just knocked them all out.”

    The researchers have filed for patents on the peptides they identified in this study, and they hope that they will be further tested as possible drugs. Keating’s lab is now working on applying this new modeling approach to other protein targets. This kind of modeling could be useful for not only developing potential drugs, but also generating proteins for use in agricultural or energy applications, she says.

    The research was funded by the National Institute of General Medical Sciences, National Science Foundation Graduate Fellowships, and the National Institutes of Health.

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