Dunn joined Rensselaer in 2008 as Vice Provost and Dean of Graduate Education and full Professor in the School of Engineering. Dunn’s experience includes developing university-wide initiatives in such areas as packaging engineering, water resource management, and homeland security. He also has extensive experience building academic programs, including overseeing the country’s first engineering-based clinical training program in prosthetics and orthotics. Dunn has mentored 14 Ph.D. students, 23 M.S. students, and many undergraduate students. These students have come from biomedical engineering, electrical and computer engineering, computer science, mathematics, dentistry, as well as the M.D./Ph.D. program. The author of three books and 150 papers on different subjects including digital subtraction radiography, Dunn is a fellow of the American Institute of Medical and Biological Engineering. He is the founding editor-in-chief of the Journal of Applied Packaging Research, and has served as an editor and officer of several journals and professional organizations.

Sibel Adali is a professor at Rensselaer Polytechnic Institute, which she joined in 1996 after obtaining her PhD from the University of Maryland. Her work concentrates on cross-cutting problems related to trust, information processing and retrieval, and social networks. She has worked as the ARL-lead Collaborative Technology Alliance (CTA) wide Trust Coordinator and the Social and Cognitive Networks Academic Research Center (SCNARC) Associate Director. She is the author of the book "Modeling Trust Context in Networks", which was published by Springer in 2013. At Rensselaer, Adali served as the Associate Head and Graduate Program Director of the Computer Science Department 2015-2018. She currently serves as the Associate Dean of Science for Research and Graduate Studies. She teaches the introductory problem solving course in Computer Science as well as courses in databases. In 2015, Adali received the Trustees' Outstanding Teacher Award, the highest teaching award given by Rensselaer Polytechnic Institute.  

Shekhar Garde is the Thomas R. Farino Jr. ’67 and Patricia E. Farino Dean of the School of Engineering and the Elaine S. and Jack S. Parker Chaired Professor of Chemical and Biological Engineering at Rensselaer Polytechnic Institute.  He received his bachelor's (University of Bombay, 1992) and PhD (University of Delaware, 1997) degrees in chemical engineering and was a director's fellow at Los Alamos National Labs (1997-1999), before joining Rensselaer in 1999. At RPI he was promoted to full Professor and named Elaine and Jack Parker Endowed Chair in Engineering in 2006, appointed Department Head of the Howard P. Isermann Department of Chemical and Biological Engineering in 2007, and named Dean of Engineering in 2014. His research focuses on understanding the role of water in biological interactions.  He has published over 100 papers (cited 12,500+ times) and presented 150 invited talks at leading universities and conferences. He received the National Science Foundation NSF CAREER Award, Rensselaer Early Career Award, and was the 2011 Robert W. Vaughan Lecturer at CalTech. He is a Fellow of the American Institute of Medical and Biological Engineers and of the American Association for the Advancement of Science. Garde co-leads the award-winning Molecularium Project, which has produced digital dome and IMAX movies and a web-based gaming portal for children. In 2011, Garde was honored with the Explore-Discover-Imagine Award by the Children's Museum of Science and Technology in the Capital District (Albany), NY.

Shaowu Pan received his B.E. in Aerospace Engineering and B.S. in Applied Mathematics from Beihang University, China in 2013. After that, he received M.S. and Ph.D. in Aerospace Engineering and Scientific Computing from the University of Michigan, Ann Arbor in April 2021. Then he started as a Postdoctoral Scholar in the AI Institute in Dynamic Systems at the University of Washington, Seattle from 2021 to 2022. His research interests lie in the intersection between computational fluid dynamics, data-driven modeling of complex systems, scientific machine learning, generative AI, and dynamical systems. 

Prof. Tomek Strzalkowski research interests span a wide spectrum of human language technology including computational linguistics and sociolinguistics, socio-behavioral computing, interactive information retrieval, question-answering, human-computer dialogue, serious games, social media analytics, formal semantics, and reversible grammars. He has directed research sponsored by IARPA, DARPA, ARL, AFRL, NSF, the European Commission, NSERC, as well as a number of industry-funded projects. He was involved in IBM’s Jeopardy! Challenge in advanced question answering. Dr. Strzalkowski has published over a hundred and fifty scientific papers, and is the editor of several books, including Advances in Open Domain Question Answering. He serves on the Editorial Board of the journal of Natural Language Engineering.   Prior to joining RPI, Dr. Strzalkowski was Professor of Computer Science at SUNY Albany. At SUNY, he was the founding Director of the Institute for Informatics, Logics, and Security Studies with research budget of more than $35 million. He came to SUNY from GE CRD where he was a Natural Language Group Leader and Principal Scientist. At GE, Dr. Strzalkowski directed projects on automated technical manuals, medical informatics, speech recognition, automated summarization, as well as multimedia processing including language and video. Before coming to GE, he was a research faculty at the Courant Institute of New York University, where he worked on applications of natural language processing to information retrieval.   Current projects include research into social dimensions of information spread online, internet ethnography, and building effective AI defenses against disinformation and exploitation of human socio-cognitive vulnerabilities online, including social engineering attacks. Some example projects include: GATOR: The Goal-oriented Autonomous Dialogue System. We develop a new type of human-machine dialogue system that uses deep learning technologies (such as transformers) to learn how to recognize and generate dialogue plans, i.e., semantic and pragmatic structures that represent one party’s goals and intentions, as well as the impact these are having on the other party. Unlike the current transformer-driven chatbots, the core learning is not to transform one language expression (input) into another language expression (response) but instead to construct a response plan that would properly address the plan in the input and the history of interaction. Consequently, the learning process takes three types of information: (1) the input utterance; (2) its semantic-pragmatic plan, i.e., the plan that was used to produce the utterance, and (3) the history of interaction up to this point. Furthermore, the cumulative history of the dialogue is not merely the memory of the utterances exchanged earlier, but it captures, in a condensed semantic form, the evolving state of the parties’ objectives as well as the emerging sociolinguistic behavioral patterns of both (all) parties. Personalized AutoNomous Agents Countering Social Engineering Attacks (PANACEA) protects online users against current and future forms of social engineering. PANACEA serves as an intermediary between attackers (human, automated, hybrid, coordinated) and the potential victim(s) they target. Depending upon the nature and source of communication, PANACEA either handles it autonomously, or allows the user to proceed with an exchange while monitoring the conversation and intervening as needed by (1) inserting or modifying users’ messages, (2) instructing the user how best to respond, while at the same time (3) initiating an investigation to identify the attacker. (DARPA ASED Program) COMETH (Computational Ethnography from Metaphors and Polarized Language). The objective of this project is to develop a methodology and accompanying software tools for constructing dynamic socio-behavioral models of communities based on online content that their members produce. A community can be defined by the set of salient concepts that its members recognize, along with the values they assign to them. The resulting causal models are then applied to derive culturally biased interpretations of novel information by prototyping the process by which such new information is adapted to fit into the community current model. (DARPA UGB) Social Convos: A New Approach to Modeling Information Diffusion in Social Media. In this project, we recast our understanding of all social media as a landscape of collectives, or “convos”: sets of users connected by a common interest in an (possibly evolving) information artifact, such as a repository in GitHub, a subreddit in Reddit or a group of hashtags in Twitter. Convos are represented by the collections of features that capture their internal social dynamics. Furthermore, convos are basis for modeling large and small internet-based communities as “hybrid organisms” that interact in various ways with one another and react collectively to external stimuli, including information and disinformation campaigns. (DARPA SocialSim)

Trevor David Rhone received a liberal arts education from Macalester College in Saint Paul. He went on to pursue his doctoral studies at Columbia University in the city of New York where he did experimental studies of two-dimensional electron systems in the extreme quantum limit. Trevor David spent several years at NTT Basic research laboratories in Japan.  During a research stint at the National Institute of Materials Science in Japan, he transitioned to materials informatics research - exploiting machine learning tools to perform materials research. He continued this work at Harvard University where he used machine learning tools to search for new 2D magnetic materials. Trevor David Rhone's research interests involve using machine learning tools for materials discovery and knowledge discovery. Materials discovery could manifest in the search new 2D materials with exotic properties, the prediction of the outcome of industrially relevant catalytic reactions or for other compelling research problems. In addition, data analytics tools will be used to aid in developing a better understanding of physical systems.

Dr. Ghosal is Professor and Department Head of Economics, and Virginia and Lloyd W. Rittenhouse Chaired Professor of Humanities and Social Sciences. He was the Acting Dean, School of Humanities Arts and Social Sciences, from January-July 2023. He is an Affiliated Faculty member at Rensselaer's Center for Biotechnology and Interdisciplinary Studies (CBIS), and at the Institute for Data Exploration and Applications (IDEA).Professor Ghosal's current research and policy interests include: (1) Artificial Intelligence Markets focusing on Big-Tech partnerships, antitrust and regulations; (2) Biopharmaceuticals markets focusing on innovation, pricing and FDA regulations; and (3) Antitrust laws and enforcement. Currently he teaches the course "Economics of Biotechnology and Medical Innovations."Before joining Rensselaer in 2016, he was the Mary and Richard Inman Chaired Professor at the School of Economics at Georgia Institute of Technology. At Georgia Tech., he was Director of the MS (2011-2016) and PhD (2012-2016) programs. Prior to his position at Georgia Tech., he was a Senior Economist at the Economic Analysis Group, Antitrust Division, U.S. Department of Justice (1998-2001). In this position, he worked on mergers and acquisitions, horizontal and vertical market power, tying agreements, joint ventures, regulatory reform, and innovation and efficiency. Some of the markets he investigated include electricity, energy (nuclear, natural gas, oilfield drilling and services), information technology, media markets, and international mail services.Professor Ghosal has published two edited books: The Political Economy of Antitrust (Elsevier, 2007); and Reforming Rules and Regulations: Laws, Institutions and Implementation (MIT Press, 2010). He has published in peer-reviewed journals in Economics, Management, and Law & Economics, including: Review of Economics and Statistics; Journal of Law and Economics; Journal of Industrial Economics; International Journal of Industrial Organization; Research Policy; Small Business Economics; Managerial and Decision Economics; Business Strategy and the Environment; Journal of Competition Law & Economics; Review of Industrial Organization; Review of Law & Economics; Journal of Economics and Business; Illinois Law Review; China Economic Review; and Harvard Public Health Review. His research has also been published as book chapters by publishers such as: MIT Press; Stanford University Press; Elsevier Science; Edgar Elgar; Routledge; and Springer. His recent writing on "Big Tech Investments in AI Startups Do Not Raise Competitive Red Flags" appeared in the Big Tech-AI Investment Symposium published by ProMarket (University of Chicago). Dr. Ghosal's international appointments have included Visiting Professor (2010-2018) at the European Business School (Wiesbaden, Germany) where he conducted research and lectured on regulations and business strategy, with emphasis on environmental regulations, sustainability, and innovation in the automobile and other manufacturing industries. He was a Visiting Professor (2010-2016) at the joint Organization for Economic Cooperation and Development (OECD, Paris) and Korea Development Institute School of Public Policy and Management (Seoul, South Korea) international program on regulatory reform and competition policy. In this position he provided executive education lectures and workshops to international public policy professionals. On topics related to antitrust, competition law and enforcement, regulations, and mergers and acquisitions, he has delivered executive education lectures in Taipei, Lima, Seoul, New Delhi, Amsterdam, and Tokyo. He has taught Summer graduate school workshops at the University of Amsterdam, Ludwig Maximilians University (Munich), and Central European University (Budapest).Professor Ghosal's grants, contacts and research have included industries such as: automobiles; high-speed rail; healthcare; transportation; information technology; telecommunications and media; energy and electricity; and paper & paperboard. His externally funded research grants have included issues related to: regional economic and business development; infrastructure investments; public-private partnerships; impact of environmental regulations; regulatory assessments; and innovation and efficiency. The organizations he has received funding from include: U.S. Department of Transportation; Georgia Department of Transportation; Sloan Foundation; Ragnar Soderberg's Foundation (Sweden); Woodruff Foundation; Organization for Economic Cooperation and Development (OECD, Paris); and Scripps Foundation.He worked as an expert with the Organization for Economic Cooperation and Development (OECD, Paris, 2005-2012) on developing the Competition Assessment Toolkit which served as an international framework adopted by many countries for identifying and revising regulations and their impact on competition. As part of this OECD initiative, Dr. Ghosal traveled to several countries to present professional training workshops to national government agencies, public policy and regulatory professionals to help with implementation of the framework.Professor Ghosal has been a consultant for international organizations, governments, consulting firms and companies on issues related to antitrust, regulatory reform, business and economic modeling of markets, industry studies, and statistical and econometric modeling. He has provided project and expert reports, and testimony.

Chris Carothers is a Professor in the Computer Science Department at Rensselaer Polytechnic Institute. His research interest are in massively parallel systems focusing on modeling and simulation systems of all sorts. Prof. Carothers is an NSF CAREER award winner and is currently active in the DOE Exascale Co-Design Program associated with designs for next generation exascale storage systems as well as the NSF PetaApps Program, and the Army Research Center's Mobile Network Modeling Institute

Dr. Bennett brings over 30 years of research experience in artificial intelligence, machine learning, and their applications to problems in health, science, and industry. Her research specialty is working with people with problems and data and then developing novel machine learning and AI models and work flows to solve their problems. She serves as Associate Director of Institute of Data Exploration and Applications (IDEA). Her role is to both lead major data science research projects, develop and lead teams for new research projects, and create data science research education programs. Her work with industry includes projects with GE (PI) and Global Foundries (co-Pi). She have been PI or Co-Pi on many data science research projects funded by GE (PI), Global Foundries (co-PI), Albany Capital District Physicians Health Plan (HMO, PI), IBM (co-PI), United Health Foundation/OPTUM Labs (PI), HBI Solutions (Healthcare Data Science, PI), Albany Medical Center (Hospital, PI), Bill and Melinda Gates Foundation (co-PI), NIH (PI and co-PI) and NSF (PI and co-PI). She has worked with electronic medical records and public health data to develop solutions to problems such as Treatment Effect Estimation, Emergency Department Readmission, Critical Care Management, and High Cost Medicare Patients. She works in emerging research areas such as health equity, ML fairness, and synthetic health data. She has been program chair and area chair, PC member and/or organizer for conferences in machine learning, data mining, and operations research including KDD, AAAI, Intl. Conf. on Continuous Optimization, International Conference on Machine Learning, NIPS, IEEE Conf. on Data Mining, COLT, INFORMS, and SIAM ICDM. She has over 130 research publications. She has been a plenary speaker at major conferences including AAAI, IJCNN, and IEEE BIBM. She founded and directs the Data INCITE Lab which does novel applied data analytics research. Data INCITE fully integrates education and research. Over 250 undergrad students have done research in Lab on real problems for actual clients resulting in publications and applications. Recent awards from her group include “MortalityMinder” https://mortalityminder.idea.rpi.edu which was a winner in the AHRQ Visualization of Social Determinants of Health Contest, 2019 and Best Student paper at ACM BCB 2021.

Dr. Magdon-Ismail has been a Professor of Computer Science since 2000. After degrees at Yale and Caltech, Dr. Magdon-Ismail was a research scholar at Caltech before joining Rensselaer as Assistant Professor of Computer Science. His interests are in decision making from data in complex systems, including machine learning, computational finance networked systems and quantum computing. He enjoys poker, bridge, squash, tennis and badminton. For more details, please visit his web page.