Liu Liu has been with the Department of Electrical, Computer, and Systems Engineering at Rensselaer Polytechnic Institute (RPI) as an assistant professor since July 2022. He has a Ph.D. in Computer Science at University of California, Santa Barbara. His research interests reside in the intersection between computer architecture and machine learning, towards high-performance, energy-efficient, and robust machine intelligence. He leads the research on Elastic Processing & Hardware Architectures, with publications in top-tier conferences on machine learning and computer architecture (e.g., ICML, ICLR, MICRO, and ASPLOS). He earned an M.S. in Electrical and Computer Engineering from UC Santa Barbara in 2015. He is a recipient of the Peter J Frenkel Fellowship from the Institute of Energy Efficiency at UCSB.

Lirong Xia is an assistant professor in the Department of Computer Science at Rensselaer Polytechnic Institute (RPI). Prior to joining RPI in 2013, he was a CRCS fellow and NSF CI Fellow at the Center for Research on Computation and Society at Harvard University. He received his PhD in Computer Science and MA in Economics from Duke University. His research focuses on the intersection of computer science and microeconomics, in particular computational social choice, game theory, mechanism design, and prediction markets. He is an associate editor of Mathematical Social Sciences and is on the editorial board of Journal of Artificial Intelligence Research. He is the recipient of an NSF CAREER award, a Simons-Berkeley Research Fellowship, and was named as one of "AI's 10 to watch 2015" by IEEE Intelligent Systems.

Hull joined RPI in January 2008 to assume the positions of the Head of the Materials Science and Engineering Department and the Henry Burlage Professor of Engineering. Prior to that he spent about a decade at Bell Laboratories in the Physics Research Division, and twelve years at the University of Virginia, where he was the Director of an NSF MRSEC Center and Director of the UVA Institute for Nanoscale and Quantum Science. He received his PhD in Materials Science from Oxford University in 1983. Hull is highly active in engineering and materials science societies and professional groups. He is a fellow of the American Physical Society and of the Materials Research Society, and in 1997 served as president of the Materials Research Society. He has also chaired a Gordon Research Conference on Thin Films, and chaired the Committee of Visitors for the National Science Foundation’s Division of Materials Research. Within the realms of materials and nanoscience, Hull’s research focuses on the relationships between structure and property in electronic materials, fundamental mechanisms of thin film growth, and the self-assembly of nanoscale structures. Other areas of interest include degradation modes in electronic and optoelectronic devices, the properties of dislocations in semiconductors, nanoscale fabrication techniques, nanoscale tomographic reconstruction techniques, development of new nanoelectronic architectures, and the theory and application of electron and ion beams.  

He is currently an Assistant Professor in the Department of Electrical Computer and Systems Engineering at the Rensselaer Polytechnic Institute. Prior to joining Rensselaer, Dr. Paternain was a postdoctoral Researcher at the University of Pennsylvania. His research interests lie at the intersection of machine learning and control of dynamical systems. Dr. Paternain was the recipient of the 2017 CDC Best Student Paper Award and the 2019 Joseph and Rosaline Wolfe Best Doctoral Dissertation Award from the Electrical and Systems Engineering Department at the University of Pennsylvania.

See http://kryten.mm.rpi.edu/selmerbringsjord.html for latest CV and Bio. Info re. Bringsjord's Rensselaer AI & Reasoning (RAIR) Lab, now going strong for over two decades, available here: https://rair.cogsci.rpi.edu/.

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)

 He is presently engaged in research on the application of agent based technology to problems in incident management and emergency response, issues in trust and ethical decision making, resilience supply networks, and in studying emergent and improvisational behavior in social media immediately before and following a disaster.  Professor Wallace’s research has been supported by agencies and organizations such as the U.S. National Science Foundation, U.S. Department of Homeland Security (including the U.S, Coast Guard), U.S. Department of Transportation and Army Research Office, and has resulted in over 200 archival publications. He was a member of the National Research Council's Board on Infrastructure and the Built Environment and served on the National Research Council Committee on Social Science Research on Disasters.  Professor Wallace received the International Emergency Management and Engineering Conference Award for Outstanding Long-Term Dedication to the Field of Emergency Management, The Institute of Electrical and Electronics Engineers (IEEE) Third Millennium Medal and is a Fellow of the IEEE, and received the 2004 INFORMS President’s Award for work that advances the welfare of society. In addition, he was either Project Director or co-Project Director for research that resulted in the ITS-America “Best of ITS” award in the area of Research and Innovation and four project of the year awards from ITS-New York.  

Tianyi Chen has been with Rensselaer Polytechnic Institute (RPI) as an assistant professor since August 2019. Dr. Chen is the inaugural recipient of IEEE Signal Processing Society Best PhD Dissertation Award in 2020, a recipient of NSF CAREER Award in 2021 and a recipient of 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 and at IEEE ICASSP in 2021. Dr. Chen's current research focuses on theoretical and algorithmic foundations of optimization, machine learning, and statistical signal processing.