Dr. Relyea completed his PhD at the University of Michigan in 1999 and spent the next 15 years as a professor at the University of Pittsburgh. In 2014, he moved to Rensselaer to become the Director of the Darrin Fresh Water Institute and the Director of The Jefferson Project at Lake George. In July 2022, he stepped down from being a director to go on a sabbatical. Complete list of published journal articles Complete list of published textbooks

Prior to joining Rensellaer as an Assistant Professor of Computer Science, Radoslav was a postdoctoral fellow at the University of Pennsylvania, where he worked with Dr. George Pappas and Dr. Rajeev Alur. Radoslav defended his PhD dissertation in 2017 at the University of Pennsylvania under the supervision of Dr. Insup Lee and Dr. James Weimer. His research lies broadly in the field of safe and secure autonomy. The natural application domains of his work are safety-critical cyber-physical systems (CPS) such as automotive CPS and medical CPS. The fields relevant to his research are safe autonomy, neural network verification, CPS security, control theory and sensor fusion.

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.  

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.

Dr. Boleslaw K. Szymanski is the Claire and Roland Schmitt Distinguished Professor at the Department of Computer Science and the Director of the ARL Social and Cognitive Networks Academic Research Center at the Rensselaer Polytechnic Institute. He received his Ph.D. in Computer Science from National Academy of Sciences in Warsaw, Poland, in 1976. Dr. Szymanski published over four hundred scientific articles. He is a foreign member of the National Academy of Science in Poland, an IEEE Fellow and a member of the IEEE Computer Society, and Association for Computing Machinery for which he was National Lecturer. He received the Wiley Distinguished Faculty Award in 2003 and the Wilkes Medal of British Computer Society in 2009. His research interests cover the broad area of network science with current focus on social and computer networks.

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.

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.

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)

Tianyi Chen has been with Rensselaer Polytechnic Institute (RPI) as an assistant professor since August 2019. Dr. Chen is the inaugural recipient of the IEEE Signal Processing Society Best PhD Dissertation Award in 2020, a recipient of the NSF CAREER Award in 2021, and a recipient of the Amazon Research Award in 2022. He is also a co-author of the Best Student Paper Award at the NeurIPS Federated Learning Workshop in 2020, the IEEE Signal Processing Society Flagship Conference ICASSP in 2021, and the IEEE Signal Processing Society Young Author Best Paper Award in 2024. Dr. Chen's current research addresses the theoretical and algorithmic aspects of bilevel optimization and multi-objective optimization and their applications to AI and learning problems: meta-learning (now ICL), LLMs fine-tuning and alignment, and AI-integrated NextG wireless systems.