Join us for the kickoff of our Fall Distinguished Speaker series with our first event featuring William Regli, a pioneering leader in artificial intelligence and national security whose career spanning DARPA, the Department of Defense, and the White House has shaped how the U.S. government understands, manages, and prepares for the risks and opportunities of emerging AI technologies.

Title: "Perspectives on AI Risk: How I Learned to Stop Worrying and Love AI"

In Voltaire's Candide, Dr. Pangloss is relentlessly optimistic in the face of novella's unflinching portrait of the human condition; his opposite, Martin, is pessimistic and cynical. Today's developments around Artificial Intelligence are being driven by similarly opposing forces. The Panglossian approach views AI as humanity's grasping of Promethean fire, whereas others see existential risk and threats to human safety, privacy, and wellbeing. We might hope that the reality is somewhere in between; and we might suspect that the reason for these extreme views is that we probably have the problems around AI framed incorrectly.

This presentation attempts to summarize my personal views regarding AI that I have developed during my decade away from academia in various forms of public service. First, as a member of the Defense Advanced Research Projects Agency's (DARPA) leadership team in the Defense Sciences Office (2014-2017); next as the founding director of the Applied Research Laboratory for Intelligence and Security, the Department of Defense's university-affiliated research center (UARC) for the social sciences and AI at the University of Maryland (2018-2023); and lastly as Senior Advisor for AI Risk Modeling for
Biden Administration's Office of Science and Technology Policy (2023-2024). The bottom line, upfront:

-- Current AI narratives are techno-philic and need to be re-framed because the thorniest problems are decidedly non-technical—they are mostly about AI's interaction with, and influence on, people and society;

-- Unlike physics and engineering, we do not yet have the required level of scientific understanding about AI and its effects on people and society needed to establish rigorous engineering practices and manage its use; and, lastly

-- The impacts of AI, operating at various levels in our society (ranging from individuals to our planetary community as a whole), are going to be uneven in scale, speed, and impact.

I would rather not merely admire these problems; hence, I will try to reframe them as inherently socio-technical. I will provide a practical methodology for identifying emerging scientific and engineering questions related to the ongoing integration of AI with humans and society. Using this approach, I will provide several examples of research questions that merit investigation. In the end, I hope to provide a unique perspective on recent developments in AI and a tangible means by which we might address these daunting emerging challenges.

Bio:

Dr. Regli is a computer scientist who has focused his career on interdisciplinary and use-inspired problems spanning artificial intelligence, engineering and manufacturing, and computational modeling. Dr. Regli's recent sponsored research activities include verification and validation of intelligent systems; intelligent computer networks; and the use of artificial intelligence in advanced manufacturing. He has published more than 250 technical articles, created two technology companies (one focused on mobile communications for public safety, the other on information management in edge networks), and produced five foundational U.S. Patents in the area of 3D CAD search.

From 2014 to 2017, Regli served on the leadership team of the Defense Advanced Research Projects Agency (DARPA), as Deputy Director (9/14-12/16) and Acting Director (1/17-7/17) of the Defense Sciences Office (DSO); then as Special Assistant to the DARPA Director (8/17-12/17). During his tenure, DSO initiated programs in areas as diverse as artificial intelligence, design and manufacturing, social science, applied mathematics, physical sciences and advanced sensing technologies; in his role leading DSO, he advanced the data management and retention plans for the agency, co-developed the Disruptioneering program template, expanded the DARPA Young Faculty Award, and was the Program Chair for the DARPA anniversary conference (9/2018). For his contributions, Regli received the Award for Excellence for Meritorious Service (2015) from the Undersecretary
of Defense (AT&L) and DARPA Meritorious Public Service Medal (2017).

Regli's other government service includes as a National Research Council Postdoctoral Fellow at the National Institute of Standards and Technology (NIST) (1995-1997); as a Scientific Adviser to the U.S. Department of Energy (DoE) in the areas of information technology and manufacturing (2010-2014;2018-); and as a member of the US Air Force Scientific Advisory Board (2019-2021; 2022-). His community service currently includes a role on the Computing Research Association (CRA) Computing Community Consortium (CCC) Advisory Board (2021-) as well as several editorial boards. Regli recently completed service as the founding Executive Director (2018-2023) of the University of Maryland's University-Affiliated Research Center for the Department of Defense: The Applied Research Laboratory for Intelligence and Security (ARLIS), the chartered DoD academic laboratory for the Intelligence and Security communities. For part of 2023-2024, Regli served in the Executive Offices of the President (EOP), White House Office of Science and Technology Policy (OSTP), as a Senior Advisor for AI Risk for the National AI Initiatives Office supporting a variety of activities.

Dr. Regli holds a Ph.D. in Computer Science from the University of Maryland at College Park and Bachelor of Science degree in Mathematics from Saint Joseph's University. He is an elected Senior Member of both the Association of Computing Machinery (ACM) and of the Association for the Advancement of Artificial Intelligence (AAAI); and a Fellow of the Computer Society of the Institute of Electrical and Electronics Engineers (IEEE) for his contributions to 3D search, design repositories and intelligent manufacturing, and a Fellow of the American Association for the Advancement of Science (AAAS) for work at the interface between science and government primarily at the Defense Advanced Research Projects Agency.

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Join us for an in-person Distinguished Speaker event featuring Jian Ma, a pioneering leader in computational biology and AI whose groundbreaking research has transformed our understanding of genome structure, cellular organization, and the molecular mechanisms that drive human health.

Title: Learning Cellular Organization and Function Across Scales

Abstract: Despite major advances in high-throughput genomics and cell biology, a predictive understanding of human cell diversity and tissue function remains out of reach. A central challenge is integrating heterogeneous measurements across molecular, cellular, and tissue scales. Recent advances in AI and machine learning offer new ways to model cellular systems across these scales, learn biologically grounded representations from increasingly rich multimodal data, and generate predictions and hypotheses about complex cellular processes. I will present our recent work on modeling gene regulation and genome organization from single-cell epigenomic data, as well as cellular interactions and tissue dynamics from spatial molecular profiles. I will also discuss how generative and agentic AI can extend these approaches to predictive modeling and iterative scientific discovery. Together, these approaches provide new insights into how cellular states are established, coordinated, and perturbed in health and disease.

Jian Ma is the Ray and Stephanie Lane Professor of Computational Biology in the School of Computer Science at Carnegie Mellon University. His group develops AI and machine learning methods to study the structural and functional complexity of the human genome and cellular organization. He founded the Center for AI-Driven Biomedical Research (AI4BIO) at CMU to advance AI approaches integrated with autonomous experimentation for decoding the molecular language of cellular behavior. His honors include the NSF CAREER Award, Guggenheim Fellowship, Allen Newell Award for Research Excellence, and election as Fellow of the American Association for the Advancement of Science (AAAS), the International Society for Computational Biology (ISCB), and the Association for Computing Machinery (ACM).

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Manufacturing with Embodied AI

Celebrating manufacturing-related R&D achievements and their business impacts on National Manufacturing Day!

Leadership Remarks
-Northwestern University President Mung Chiang
-National Center for Manufacturing Sciences President and CEO Lisa Strama
-Northwestern University Provost Erik Luijten

Corporate Panel, Stan Rendon, 3M VP of R&D, Yu Cao, Applied Materials Chief AI Officer and Amey Deosthali, AMD Head of Robotics, Industrial & Healthcare (Physical AI)

NU Faculty Panel, Prof. Jian Cao, Prof. Ed Colgate, Prof. Mark Hersam, Prof. John Rogers

Founders/SME Panel, Jason Sebastian, Executive VP QuesTek Innovation, Demeng Che, co-Founder & CEO Converge Lab, Gino Domel, CEO HiDeNN-AI, Joe Mullenbach, co-founder Fluid Reality

Ecosystems Panel, Tom Kurfess, CTO, NCMS & Executive Director of Mfg Institute at Georgia Tech, Berardino Baratta, CEO MxD, Allison Fisher, Chief of Staff mHUB

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Join us for an in-person Distinguished Speaker event featuring Xiao-Li Meng, an internationally renowned statistician, data scientist, and former Dean of the Harvard Kenneth C. Griffin Graduate School of Arts and Sciences. Widely recognized for his pioneering contributions to statistical science, data analysis, and interdisciplinary research, Meng has helped shape statistics and data science through groundbreaking scholarship, academic leadership, and innovative approaches to understanding uncertainty in an increasingly data-driven world.

Lecture title and abstract will be made available in the coming weeks!

Xiao-Li Meng is the Whipple V. N. Jones Professor of Statistics at Harvard and Founding Editor-in-Chief of Harvard Data Science Review. He received his BS in mathematics from Fudan University in 1982 and his PhD in statistics from Harvard in 1990. After serving on the University of Chicago faculty (1991–2001), he returned to Harvard, where he chaired the Department of Statistics (2004–2012) and served as Dean of the Graduate School of Arts and Sciences (2012–2017). His research spans foundations of statistical inference—including interactions among Bayesian, fiducial, and frequentist perspectives; standard, imprecise, and quantum probability; data utility and privacy; and multi-source, multi-phase, and multi-resolution inference—statistical methodology and computation, including posterior predictive p-values, EM, MCMC, bridge and path sampling, and heavy-tail approximations; and applications across natural, social, and medical sciences and engineering, including complex modeling in astronomy and astrophysics, disparities in mental health services, and statistical information in genetic studies. In 2001, Meng received the COPSS President’s Award, recognizing the outstanding statistician under age 40, and in 2020 was elected to the American Academy of Arts and Sciences.

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Join us for an in-person Distinguished Speaker event featuring Guillaume Fontaine, Director of the McGill RISE³ Implementation Science Lab and Assistant Professor at McGill University. An internationally recognized leader in implementation science, Fontaine's research advances the use of evidence-based frameworks and methodologies to improve healthcare outcomes, with a particular focus on integrating artificial intelligence into implementation research and practice. Through his leadership roles across major national and international research networks, he has helped shape the evolving intersection of implementation science, data science, and healthcare innovation.

Lecture title and abstract will be made available in the coming weeks!

Dr. Guillaume Fontaine (PhD, MSc, RN) is the Director of the McGill RISE³ Implementation Science Lab and an Assistant Professor at McGill University in Montreal, Canada. He is a Principal Investigator in the Centre for Clinical Epidemiology at the Lady Davis Institute, and holds visiting appointments in the Viral Hepatitis Clinical Research Program at the Kirby Institute, UNSW Sydney, and the Centre for Implementation Research, Ottawa Hospital Research Institute. He co-leads the Implementation Science Research Pillar for the Canadian Network on Hepatitis C, co-leads the Methods Think Tank for the Pan-Canadian HIV/AIDS Clinical Trials Research Network, serves on the Steering Committee of Knowledge Translation Canada, and co-chairs the Global Network on Implementation and Data Sciences. His research program focuses on applying and advancing implementation science frameworks and methodologies to improve healthcare outcomes, , with particular emphasis on the integration of AI into implementation research and practice.

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