Remarks at the World Congress on Computational Mechanics
World Congress on Computational Mechanics
I am delighted to be able to join you here at the 13th World Congress on Computational Mechanics. As a theoretical physicist, I feel that I am among my fellows—those people engaged in describing physical phenomena mathematically, in order to address the hard problems.
And I am extremely proud that the university I lead, Rensselaer Polytechnic Institute, is so strong in computational mechanics. Indeed, during my inaugural address as President in 1999, I presented to the Rensselaer community three crucial areas of focus for Rensselaer research that would allow us to undergird progress in science, engineering, and medicine. Those areas were information technology, biotechnology—and applied mathematics, the province of this audience.
I have been asked to talk about my career, and I will tell you what has led me to Rensselaer, and to roles in business and government that inform my academic leadership. I also will describe my vision for Rensselaer—indeed, what I believe a modern technological research university must be, in order to change the world for the better—which you may find intriguing.
So, let us begin at the beginning. I had wonderful parents, who emphasized education and the value of hard work. My mother taught my siblings and me to read before we went to kindergarten. My father, who was not a high school graduate, was nonetheless mathematically and mechanically gifted; and encouraged my interests in science and mathematics. My father was at Normandy on D-Day, in a segregated army unit. Many of the amphibious landing vehicles, ferrying troops and supplies to shore, lost their rudders. Using scrap metal and broken cables, my father fashioned a special splice to create new ruddering mechanisms for these boats. For this, he received a Bronze Star.
As a child, I also was very fortunate in the convergence of two events that allowed me to receive an excellent education. The first was the desegregation of the Washington, D.C., public schools in 1955, after the 1954 Brown v. Board of Education Supreme Court decision. This meant that I could attend a good school, right in my own neighborhood, with more competition, and with children from backgrounds different from mine, who introduced me to new perspectives.
The second event occurred two years later, when the Soviet Union launched Sputnik 1, the first artificial satellite, which made policymakers fear that the United States might be losing the Cold War—and which spurred a new emphasis on mathematics and science in the public schools. This offered me—and many of my peers—an opportunity to excel.
I was tested, and then placed in an accelerated honors academic program in the seventh grade, and when it became apparent that I would be valedictorian of my high school graduating class, it was not the vice principal for girls’ who encouraged me to apply to MIT, but my father, and the boys’ vice principal.
I must admit, my undergraduate experience at MIT was somewhat cold and unwelcoming, although I excelled academically. When I was considering majoring in physics, I sought out a distinguished professor for advice. He told me, “Colored girls should learn a trade.”
I was shocked and hurt by his low expectations for me, especially since I had the highest grades in his class. But I realized that I was faced with a choice: either to give in to ignorance, or stubbornly to pursue excellence. So, I chose the latter, and made physics my trade.
When I was a senior at MIT, deciding where to attend graduate school, the University of Pennsylvania Physics Department, which had admitted me to its doctoral program, invited me to visit in April of 1968. I fully intended to be a theoretical condensed matter physicist, and I was very interested in the work of Dr. John Robert Schrieffer, who was at Penn, and whose contributions to the BCS Theory of superconductivity would lead to his sharing a Nobel Prize in Physics with John Bardeen and Leon Cooper.
As I was leaving Penn after the visit, however, in a car with my sorority sister, on my way to the Philadelphia airport, the radio broadcast was interrupted, and we learned that the Reverend Dr. Martin Luther King Jr. had been shot, and later died. We nearly drove the car off the road.
By the time I got back to Cambridge, I knew that I would remain at MIT for graduate school. I was inspired by the courage of Dr. King; and MIT was the place where I felt that I would have the greatest possible opportunity to change things for the better.
Of course, MIT was an excellent place to study physics, but it was not as active in condensed matter physics at that time, so I changed my focus to elementary particle physics.
In the fall of 1968, a group of like-minded students and I formed the Black Students’ Union, and we presented a series of demands to the MIT administration—although we were diplomatic enough to call them “proposals.” Associate Provost Paul Gray, who later became President, listened, formed a Task Force on Educational Opportunity, and asked me to join it.
As a result of our recommendations, MIT began, for the first time, to actively recruit minority students, faculty, and staff in significant numbers. It also initiated a six-week summer program, called Project Interphase, that helped incoming freshmen, whose high school preparation was not the best, to ready themselves for the rigors and the culture of MIT. The program was open to all who needed it, and although I was still a student, I was asked to teach in, and later to design, the physics curriculum.
The students I helped to bring to MIT—and helped to adjust to its culture—truly excelled. They proved to the world that scientific and engineering talent is not restricted to one race, or one sex, or one story of origin.
I was proud to contribute to this transformation of the culture of science and engineering in the United States, while, of course, completing my doctorate. My doctoral thesis concerned a multi-peripheral model for many particle scattering: I did numerical limit studies, converting a “one-particle inclusive reaction” into a 3-body problem, using certain conservation laws.
After obtaining my Ph.D., I accepted a postdoctoral position at the Fermi National Accelerator Laboratory, where I was able to develop an exact solution for the problem posed in my thesis, after understanding that certain kinds of symmetries inherent in the problem were Lie Group relevant.
At Fermilab, I had the privilege of getting to know a fellow theorist, Dr. Mary K. Gaillard, who was visiting from the European Organization for Nuclear Research (CERN). She persuaded me to spend the next year working with her in Switzerland, where I collaborated with her on a paper on neutrinos—and gained the invaluable perspective offered by living abroad.
After CERN, I returned to Fermilab to complete my second post-doctoral year, when a practical reality intruded. Jobs were hard to come by in high-energy physics—in physics, generally. But there were a few opportunities in my original field of interest—theoretical condensed matter physics. And, another door opened.
At an American Physical Society meeting in Atlanta, I had dinner with Dr. T. Maurice Rice of the great Bell Labs in Murray Hill, New Jersey, who invited to me to Bell Labs to deliver a colloquium. After I described my work on neutrinos, and I explained how I intended to apply my interest in the topological properties of solutions to non-linear field theories to certain models of condensed matter systems, I won a limited-term appointment that became permanent a year later.
I had a number of successes at Bell Labs, developing theories to explain charge density waves in layered transition metal dichalcogenides, the polaronic aspects of electrons in two-dimensional systems, and the optical and electronic properties of strained-layer semiconductor superlattices. Because of this research, I achieved recognition within the greater community of scientists, and was elected a fellow of American Physical Society, and the American Academy of Arts and Sciences. I subsequently served on the governing council of the American Physical Society, and on the Executive Committee of the American Institute of Physics.
Two other windows opened for me during my time as a researcher at Bell Labs, that set me down new paths, and changed my life. First, I was asked to join the Board of Directors of PSEG, or Public Service Enterprise Group, which owned or co-owned five nuclear reactors. Because of my background in elementary particle physics, I sat on, and later chaired for a number of years, the PSEG nuclear oversight committee, visiting its nuclear power plants often.
Second, I was asked by New Jersey Governor Tom Kean to join the New Jersey Commission on Science and Technology, as a founding member. The Commission created partnerships among industry, government, and academia in disciplines important to the New Jersey economy, such as advanced biotechnology and medicine. The position was unpaid, but required State Senate confirmation—the first of what would be a number of government roles in my career.
I am unsure how my name arose when President Bill Clinton was looking, in 1994, for a Commissioner for the U.S. Nuclear Regulatory Commission—or NRC—which licenses, regulates, and safeguards (vis-à-vis nuclear non-proliferation) the use of nuclear reactors, nuclear materials, spent nuclear fuel, and nuclear wastes. However, given my scientific background, government service in New Jersey, and familiarity with nuclear power plants from PSEG, I was ready for this leap.
After I interviewed for a spot as one of five NRC commissioners, President Clinton offered me the job of Chairman.
Three years earlier, having missed teaching and advising students, I had switched from full-time to part-time at Bell Labs and accepted a position at Rutgers University as a tenured full professor of physics. So I stepped away from a tenured academic position to take on the NRC role, which required some temerity.
Suddenly, I had a staff of 3,000 people, a budget of over $500 million, and responsibility for an organization that oversaw a multi-hundred-billion dollar set of enterprises, at a time of growing public concerns about the safety of nuclear power—especially in the aftermath of the accident at the Chernobyl Nuclear Power Plant in the Ukraine in 1986.
I recognized that the NRC needed to reaffirm its fundamental health and safety mission, enhance its regulatory effectiveness, and position itself for change. So I held public meetings, listened to community concerns, and led the development of a strategic plan for the NRC—its first ever—as well as a planning, budgeting, and performance management system (PBPM), which is still is in use at the NRC today.
We also put in place the first license renewal process to extend the operating lives of nuclear reactors, and introduced risk-informed, performance-based regulation—which persists in nuclear regulation to this day, and which influenced the nuclear codes and standards of the American Society of Mechanical Engineers (ASME).
After meeting, early in my tenure at the NRC, with my senior nuclear regulatory counterparts from around the world, I saw another window of opportunity: the need for even greater international cooperation to avoid disasters such as Chernobyl, in the future. So, I spearheaded the formation of the International Nuclear Regulators Association (INRA) as a high-level forum to allow nations to assist each other in promoting nuclear safety, with an initial membership comprising Canada, France, Germany, Japan, Spain, Sweden, the U.K., and the U.S. At the NRC, we also pushed for an international Convention on Nuclear Safety—clearly needed in the aftermath of Chernobyl. Initially, the U.S. Congress (Senate) was hostile to this convention, but we did manage to get it ratified. I also had the experience of representing the U.S. Government vis-à-vis nuclear safety, and certain aspects of nuclear non-proliferation, in two bilateral commissions: the Gore-Chernomyrdin (U.S.-Russian Federation) Commission, and the Gore-Mbeki (U.S.-South Africa) Commission.
Four years later, another unforeseen opportunity arose, and another decision. I was asked to assume the Presidency of Rensselaer Polytechnic Institute by its Board of Trustees, who were looking for a change agent after a difficult period during which Rensselaer had five presidents in 14 years.
I felt that I could help Rensselaer to reach its promise—to become a world-class technological research university with global reach and global impact. Rensselaer has had a rich history, since 1824, of producing outstanding graduates, who designed and built much of the early physical and digital infrastructure of the United States, and always has had high-quality faculty—but in 1999, it was not living up to its full potential, particularly in its research enterprise.
I promised the Rensselaer community that, together, we would develop a Rensselaer Plan that would steer our choices, and allow us to reach the goals we wanted to achieve. Guided by the Rensselaer Plan, later refreshed as the Rensselaer Plan 2024, we put in place the people, programs, platforms, and partnerships that have elevated our profile as a major technological research university, and have strengthened our undergraduate and graduate curricula—with new degree programs and new academic concentrations, and research of fundamental significance in the 21st century in:
- computational science and engineering;
- biotechnology and the life sciences;
- nanotechnology and advanced materials;
- energy, the environment, and smart systems; and
- media, the arts, science, and technology.
As a result, many of our programs today are top-ranked, the number of students applying to join our freshman class has quadrupled, twenty two new academic degree programs have been created, sponsored research awards and expenditures have tripled, and the physical campus has been transformed with key new facilities, and expanded and/or upgraded existing ones.
In taking on the Presidency of Rensselaer, I nonetheless have kept my fingers on the pulse of industry by serving on the boards of leading corporations, including IBM, FedEX, Medtronic, and PSEG; and leading non-profits and associations, including the Smithsonian Institution, where I was Vice Chair of the Board of Regents; and the American Association for the Advancement of Science, where I served both as President and as Chairman.
I also have maintained my commitment to policymaking in science and national security. In 2009, President Barack Obama appointed me to the President’s Council of Advisors on Science and Technology, or PCAST, where I served for over five years. From 2014 to 2017, I served as co-chair of the President’s Intelligence Advisory Board (PIAB), which assesses issues pertaining to the quality, quantity, and adequacy of United States intelligence activities. In addition, I served on the U.S. Department of State International Security Advisory Board—from 2011 to 2017; and the U.S. Secretary of Energy Advisory Board—from 2013 to 2017, where I co-chaired the development of a report on next-generation high-performance computing, which has served as a road map for advances in data-centric, AI-enabled supercomputer systems.
Most recently, I served as co-Chair of the Global Future Council on International Security for the World Economic Forum.
I have been fortunate to have been recognized along my career path for what I have done, most notably, through election to the U.S. National Academy of Engineering, the Royal Academy of Engineering of the U.K., and through being honored with the National Medal of Science by President Obama in 2016.
People sometimes ask me, “How can you do so much?”
I always answer, “How could I not?”
My various roles have put me in the middle of academic, industry, and government partnerships. I am able to stay at the very forefront of what is important in basic science and engineering, public policy, national and global economic vitality, and national and global security. I am able to support exciting new discoveries and innovations, and the people generating them, while helping to solve global challenges in ways that uplift lives.
The diversity of my interests and experiences has contributed to my strong vision for Rensselaer, and indeed, what I believe is a paradigm for the modern technological research university.
Two factors are paramount in this paradigm:
First, is the fact that the challenges humanity faces are increasingly complex, interconnected, and global. These include issues surrounding our food, water, and energy supplies; human health and the mitigation of disease; a changing climate; our need for sustainable infrastructure; the intelligent allocation of natural resources; national and global security; and diverging demographics between aging developed nations and young developing nations with rapidly growing populations.
The networked nature of these challenges—as well as our interconnectedness—make all of us susceptible, when there is a triggering event, to intersecting vulnerabilities with cascading consequences.
We know what can happen in cyber space.
But consider this: changing environmental and/or geopolitical conditions—such as the natural disasters and extreme weather provoked by climate change, or the rise of hostile state and non-state actors—are likely to yield many cascading events. For example, the record-setting drought in Syria, between 2007 and 2010, forced many rural residents to move to urban centers, setting the conditions for instability.
After protests during the Arab Spring met with a harsh crackdown by the Syrian government, widespread unrest was sparked. The conflict escalated into a proxy war between the U.S., Russia, and a number of other nations, as well as a war against ISIS—ultimately creating 5.6 million refugees, and a migrant crisis that has altered politics in the European Union— contributing to new global tensions.
Fortunately, as well as new vulnerabilities, humanity also has new sources of strength. The second factor influencing our thinking at Rensselaer is the rise of remarkable new tools of analysis, discovery, invention, and prediction—such as genomics and all the other “-omics,” and CRISPR gene editing in the realm of biology, for example—as well as spectacular advances in sensor technologies, machine learning, and computation—of which this audience is keenly aware. These tools have applications across almost every field of endeavor.
Both our challenges and our opportunities are so great that they cannot be addressed by the most talented person working alone, nor even by a single discipline, sector, or nation.
What is required is a new model for teaching, learning, and research, which we have termed “The New Polytechnic.” As you know, the word “polytechnic” comes from the Greek for skilled in many arts. As The New Polytechnic, Rensselaer acts as a great crossroads for talented people from everywhere. We do everything possible to encourage collaborations across disciplines, sectors, regions, and generations in order to address the most complex problems, using the most advanced tools and technologies.
At Rensselaer, we have developed a remarkable computational ecosystem to enable such collaborations, including our petascale supercomputer, the Advanced Multiprocessing Optimized System, or AMOS—an IBM Blue Gene Q system that is the most powerful supercomputer at an American private university. AMOS gives our experts in computational mechanics the firepower they require for the most advanced modeling and simulation, enabling them to address important challenges in…
- energy and energy efficiency;
- materials design;
- advanced manufacturing, including biomanufacturing;
- the design of complex engineered systems of all kinds, drastically reducing costly trial and error experimentation; and
- biology and medicine, including predicting protein structure, devising virtual surgeries to train physicians, and using imaging to create non-invasive diagnostic approaches.
Currently, for example, Dr. Mark Shephard, our Johnson Professor of Engineering and Director of our Scientific Computation Research Center (SCOREC), is developing tools for the Department of Energy—on the most powerful supercomputers—to model fusion energy systems across multiple scales, thereby moving us further toward realization of this important potential energy source.
Professor Jeffrey Banks, the Eliza Ricketts Foundation Career Development Chair in our Department of Mathematical Sciences, addresses the mathematical underpinnings of the computationally difficult subject of fluid interactions with solids. His work is yielding advanced simulation tools for applications that include improving mechanical heart valves and optimizing green energy devices.
Professor Antoinette Maniatty of our Department of Mechanical, Aerospace, and Nuclear Engineering develops simulations to predict the key properties and quality of metallic parts produced by additive manufacturing—enabling the promise of 3-D printing in quickly generating custom parts, or replacement parts in an emergency.
Dr. Suvranu De, our Jonsson Distinguished Professor of Engineering and Director of the Center for Modeling, Simulation, and Imaging for Medicine, and his student Hanglin Ye, currently, are developing a non-invasive diagnostic test using ultrasound elastography to classify injured tissues in burn victims.
At our Center for Flow Physics and Control, Professor Onkar Sahni, an expert in computational fluid dynamics, and Professor Miki Amitay, the Decker Endowed Chair in Aerospace Engineering, and an expert in active flow control systems, are developing models for aircraft, wind turbines, and vehicles that incorporate, as part of the design process, actuators that react in real-time to decrease aerodynamic drag or vibrations, increasing fuel efficiency and longevity. This truly is important work, as we seek to mitigate carbon emissions. At highway speeds, aerodynamic drag accounts for more than half of the fuel consumed by tractor-trailers.
As the world approaches exascale computing, our ascending ability to model using different kinds of physics, scales, and phases is going to allow us to address even more difficult problems and to make even more accurate predictions.
New opportunities also will arise from bringing together previously separate disciplines. Given how little we understand, for example, about the human body as a multiscale system, increasingly, the scientists who comb through a haystack of genomic data, looking for disease correlations and other connections, will combine ideas and methods with the scientists who model, for example, the folding of proteins encoded by those genes.
Clearly, the volume of digital data that humanity now is generating represents an astonishing new natural resource—whether the data comes from genomics, from the sensor-connected devices that compose the Internet of Things, from the instruments of Big Science, from social media, or from computational simulations themselves.
As we address large-scale problems such as climate change—add socioeconomic dimensions to our carbon emissions scenarios—and attempt to quantify uncertainty—we will need to employ every possible computational strategy—and to use data analytics and machine learning to improve our models and vice versa.
That is why several years ago, we launched The Rensselaer Institute for Data Exploration and Applications—or, The Rensselaer IDEA—directed by Dr. James Hendler, our Tetherless World Professor of Computer, Web, and Cognitive Sciences. The Rensselaer IDEA supports research in every discipline by bringing together people in web science, data science, cognitive computing, high-performance computing, and visualization technologies—for applications in engineering, and in the physical, life, and social sciences.
Students in every field will need to learn how to use diverse datasets to define and address complex challenges. Therefore, we recently have introduced a “data dexterity” requirement into our core curriculum. All students at Rensselaer must complete two “data-intensive” courses; one to establish the foundations of data modeling and analysis, and a second course that applies modern data analytics within their academic disciplines.
Please allow me to offer an example of the value of our focus on data science in education: At our Data Interdisciplinary Challenges Intelligent Technology Exploration Laboratory, or Data INCITE Lab, which introduces our students to real-world data analytics problems, a junior in our accelerated Bachelor of Science-Ph.D. program (Hannah De Los Santos) took on a project proposed by Rensselaer Professor Jennifer Hurley. Professor Hurley is an expert in the circadian clock—the molecular timer that tunes our biological processes to the 24-hour day/night cycle. Given the increasingly well-understood connections between the circadian clock, its disruption, and human health and disease, her explorations are truly significant.
With the fungus Neurospora crassa as a model system, Professor Hurley was examining which genes were regulated by the circadian clock, using vast amounts of experimental data measuring gene expression and protein levels. The “field standard” computational models she employed identified those genes regulated by the clock, by comparing the levels of the relevant transcripts and proteins with a harmonic oscillator with fixed amplitudes over time.
But Hannah and Professor Kristin Bennett, Associate Director of the Rensselaer IDEA, noticed that there were genes whose outputs were damped oscillations that declined over a number of days, or driven oscillations that increased, and these were not detected by the model.
They were able to see something previously unseen because—remarkably enough—they also were studying sensor data from semiconductor manufacturing that had the same wave shape. Adapting methods they were developing to detect anomalies in smart manufacturing to circadian biology, they identified new circadian genes that were previously missed by the field. The genes they discovered appear to be connected to cellular metabolic regulation—suggesting new avenues of investigation into the influence of the circadian clock on the human metabolic system.
In other words, data science improved on both the computational and the biological model, which now includes damped and driven harmonic oscillators. And the tool developed is being shared with scientists studying other kinds of biological rhythms, such as the seasonal flight patterns of birds.
If you ask Professor Bennett what data scientists offer to the work of other researchers, she will tell you, “Other scientists look for the things they are looking for. Data scientists just look.” Deductive, inductive, abductive—each approach improves the other.
Multi-faceted problem solving—and feedback among theory, experimentation, modeling, and data science—are the future of science and engineering. There is great value in tools that combine advances in high-performance computing, modeling, and simulation with data analytics, web science, immersive technologies of all kinds, and both perceptual and associative artificial intelligence.
Our Cognitive and Immersive Systems Laboratory, a partnership with IBM, is developing such approaches now: through the development of smart Situations Rooms intended to radically enhance group design and decision-making. These are spaces that recognize, see, hear, and interpret their occupants—that use hierarchies or communities of cognitive agents to anticipate occupants’ need for information, and to express it in the most compelling ways—allowing a group to arrive, together, at a better answer.
Of course, to address the most expansive questions, we will need new heterogenous architectures for high-performance computing that combine powerful capabilities in modeling and simulation with an ability to find answers within massive amounts of non-mathematical data, using machine intelligence. Indeed, Summit, the world’s most powerful supercomputer, recently unveiled at the Oak Ridge National Laboratory, was designed by IBM with a hybrid IBM CPU and NVIDIA GPU architecture that addresses both computational and data-intensive problems, such the genetics that may underlie opioid addiction. Summit recently performed the world’s first exascale computation on genomic data, using mixed-precision operations, which are employed in extreme-scale deep learning applications.
We are very proud of the work of our faculty and alumni in laying the groundwork for this new age in computation and machine intelligence: Rensselaer Trustee, Dr. John E. Kelly III, of the Rensselaer Classes of 1978 and 1980—and Senior Vice President for Cognitive Solutions and Research at IBM—led a team that included a number of Rensselaer alumni to create Watson, a breakthrough in associative artificial intelligence. Rensselaer Board of Trustees Secretary Curtis R. Priem, of the Rensselaer Class of 1982, based on his graphics chip designs, co-founded NVIDIA—whose GPUs today enable astonishing breakthroughs in perceptual artificial intelligence.
And at Rensselaer, Professor Christopher Carothers, Director of our Center for Computational Innovations, is using our AMOS supercomputer to simulate the next generation of hybrid architectures for supercomputers, including those that use neuromorphic chips to reduce energy usage and boost pattern recognition—and to model next-generation networks for exascale computing.
As you know, when we start performing simulations at exascale, the data generated is going to approach that generated by the Large Hadron Collider at CERN—and to be effectively unstorable in total. So in situ data analytics and uncertainty quantification will be required. Computation and data analytic techniques will work together as part of the same exascale compute job by leveraging new advances in solid-state storage technologies.
But even more than a new kind of computing power—we need a culture shift. The members of the International Association for Computational Mechanics will have a key role to play in working with those in other parts of the computational ecosystem to address great challenges—ideally lending the tremendous sophistication of your methods to data science, immersive technologies, machine learning, and artificial intelligence.
As I mentioned earlier, the organizers of this event asked me to tell my own story—which truly is about walking through windows of opportunity when they appear unexpectedly, even abruptly, and even when they seem to lead in unfamiliar directions. The perspectives I have gained as a scientist, as someone who became part of an international community of scientists, as an advisor and leader in government and in business, and as an academic leader, have given me the wonderful life and career I have had.
These perspectives have shaped my views of what a modern technological education must be. They also inform my views of what the combined breakthroughs in computation, data science, and artificial intelligence will allow us to address in domains that we have, heretofore, not been able to access; and to tackle entirely new challenges using foundational knowledge from multiple arenas to solve increasingly complex problems.
I would urge all of you, as well, to take on unexpected roles, if they offer you a new context for your efforts—and to consider unlikely collaborations if they offer the potential for progress. This audience already addresses the very hardest problems in science, engineering, and medicine. I would urge you only to amplify your efforts by welcoming others into this remarkable community.