Dorit Nevo is a Professor of Management Information Systems at the Lally School of Management. She joined RPI in 2012, and prior to that was an Associate Professor at the Schulich School of Business in Toronto. Professor Nevo obtained her BA and MS in Economics and PhD in Management Information Systems. Since joining RPI, she held the roles of program director for the MS in Business Analytics, Acting Associate Dean for the Lally school of Management, and MS and MBA programs director. Dorit’s research focuses on interactions between computers and their users within the business environment. This work was published in leading academic and business journals including MIS Quarterly, Information Systems Research, Journal of Management Information Systems, Sloan Management Review, and the Wall Street Journal. She also examines how news readers receive the advice of fake news algorithms. This work received media attention from the ACM and IEEE among others. On the teaching front, Dorit mostly teaches Statistics and Data Science at the Lally School of Management. She is the recipient of the RPI Trustees’ Outstanding Teacher Award and the David M. Darrin ’40 Counseling Award in Celebration of CLASS.

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.

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

Curt Breneman was born in Santa Monica, California in 1956, and went on to earn a B.S. in Chemistry at UCLA in 1980 followed by a Ph.D. in Chemistry at UC Santa Barbara (with an emphasis on Physical Organic and Computational Chemistry) in 1987. Following two years of post-doctoral research at Yale University, Dr. Breneman joined the faculty of the Department of Chemistry at Rensselaer Polytechnic Institute (RPI) and began a program in molecular recognition and computational chemistry based on his concept of "Transferable Atom Equivalents", or TAEs, as building blocks for describing the electronic and reactive character of molecules. Dr. Breneman currently holds the rank of Full Professor in the RPI Department of Chemistry and Chemical Biology, and is the Director of the NIH RECCR Center. He later served as Head of the Department of Chemistry & Chemical Biology and now as Dean of the School of Science. The Breneman research group primarily specializes in the development of new molecular property descriptors and machine learning methods that can be applied to a diverse set of physical and biochemical problems. Of paramount interest are methods that can increase the information content of molecular descriptors, and machine learning techniques that can exploit this data for the creation of fully validated, predictive property models. Current application areas include pharmaceutical ADME prediction, virtual high-throughput screening of drug candidates, protein chromatography modeling (HIC and ion-exchange), as well as polymer property prediction.

Deborah McGuinness is a leading expert in knowledge representation and reasoning languages and systems and has worked in ontology creation and evolution environments for over 20 years. Most recently, McGuinness is best known for her leadership role in semantic web research, and for her work on explanation, trust, and applications of semantic web technology, particularly for scientific applications. “I am interested in making smart systems that help people and machines function better,” said McGuinness. “My slant on this work is to research, develop, and use semantic technologies that allow people and machines to represent, reason with, visualize, and explain information in ways that support understanding and (re)use.   My application areas cover a wide range of domain areas, but often in earth and space science informatics and health informatics.”

Jen Pazour is a Professor and the PhD Program Director in the department of Industrial and Systems Engineering at Rensselaer Polytechnic Institute (RPI) in Troy, NY. Her research and teaching focus on the development and use of mathematical models to guide decision making for logistics and supply chain challenges. Modern supply chain systems need to fulfill a wide variety of requests quickly with little warning in small units to many dispersed locations at low costs. These characteristics are fundamentally different than yesterday’s demand that aggregated at given locations. In the face of this disconnect, her team's research thinks differently about how supply chain resources are acquired, managed, and allocated to fulfill customer requests. In doing so, her team's contributions span a diverse array of applications, including resource sharing platforms, peer-to-peer transportation systems, on-demand warehousing platforms, and crowdsourced order fulfillment systems, as well as facility logistics and transportation systems. Methodologically, they are modelers, whose core intellectual strength is in the development of mathematical and computational representations of sociotechnical systems and processes. Their research approach is to (1) create optimization models encompassing the primary system and decision trade-offs, (2) discover solution approaches and algorithms to efficiently solve the optimization models, (3) use the developed models and approaches to better understand the implications of the sociotechnical system’s design and operation, and then (4) through theoretical results, computational experiments, and statistical analysis provide managerial insights and policy recommendations. Her team has created a wide range of operations research tools, including integer linear programs, bi-level optimization formulations, queuing models, and analytical models. Jen is a recipient of a National Science Foundation Faculty Early Career Development (CAREER) Award, a Johnson & Johnson Women in STEM2D Scholars Award, a National Academies of Science Gulf Research Program Early-Career Fellowship, and a Young Investigator Award from the Office of Naval Research. She was awarded the Rensselaer Alumni Teaching Award, the IISE Logistics and Supply Chain Division Teaching Award, and the IISE Dr. Hamed K. Eldin Outstanding Early Career IE in Academia Award. She is an Associate Editor of Transportation Science, IISE Transactions, Military Operations Research, and OMEGA. She has served professional societies, for example, as a speaker and session organizer at the NAE Frontiers of Engineering Symposium, as the chair of the INFORMS professional recognition committee, chair of the INFORMS undergraduate operations research prize, chair of INFORMS TSL Facility Logistics SIG, the communications chair of the IISE Logistics and Supply Chain division and is on the IISE Transaction Social Media Team. She proudly holds three degrees in Industrial Engineering (a B.S. from South Dakota School of Mines and Technology, and a M.S. and Ph.D. from the University of Arkansas). More information can be found at her research and teaching blog: http://jenpazour.wordpress.com/

Dr. Lin joined the Rensselaer faculty as an Assistant Professor of Economics in Fall 2017. Her research interests include topics in Health Economics, Industrial Organization, and Applied Econometrics.  She currently focuses on issues related to health information technology (IT) adoption, as well as how health IT impacts hospital financial and quality performance.

Dr. Johnson Samuel has been serving as a faculty in the mechanical, aerospace and nuclear engineering department of Rensselaer Polytechnic Institute (RPI), since the Spring of 2011. As director of the Nano/Micro-scale Manufacturing and Material Design Lab (NanoM3 Design Lab) at Rensselaer, he leads research and education efforts in the areas of advanced manufacturing and material design. His research has attracted funding from multiple agencies including the National Science Foundation, New York State Energy Research and Development Authority, Defense Health Program, Army Research Lab, DARPA and The Boeing Company. He is the recipient of the U.S. National Science Foundation CAREER award for his proposal titled “Microstructure-specific machining strategies for bone” (2014), The Outstanding Young Alumni Award, MechSe Dept. Univ. of Illinois- Urbana  Champaign (2016), Rensselaer School of Engineering Research Excellence Award (2016), and the World Economic Forum Young Scientist Cohort (2016) Besides research, Dr.Samuel is also passionate about training and developing the next generation of manufacturing engineers in the US. He was awarded the Rensselaer Class of 1951 Outstanding Teaching Award (2014) and the School Of Engineering Education Innovation Award (2015) in recognition of his manufacturing education efforts at Rensselaer.

Mei Si is primarily interested in is artificial intelligence and its application in virtual and mixed realities. In particular, her research concentrates on computer-aided interactive narratives, embodied conversational agents and pervasive user interface, elements that make virtual environments more engaging and effective. Si has been using her research to develop virtual environments and intelligent conversational agents for serious games. In one example of her work, Si helped to develop the Tactical Language Training System, a large-scale (six to twelve scenes each for three languages) award-winning project funded by the U.S. military for rapid language and culture training. The system has been used by thousands of military personnel. “Computer-aided interactive narrative is a new form of media that allows the user to play a role in a story and interact with other characters controlled by an automated system. The user’s choices of actions affect the development of the story,” said Si. Narrative itself is a central part of the human experience. Its power to shape people's minds and affect people's behavior has been recognized throughout recorded history. The support for user interactivity distinguishes interactive narrative from other narrative forms. By allowing the user to interact, the experience is richer and potentially more engaging. Moreover, interactivity can promote intrinsic motivation in learning, and support learning in context and replay. Therefore, interactive narrative can be potentially a more effective media than traditional narrative.” Si regularly presents and publishes her work. She has recently presented on “Activating Narcissus: Cognitive and Affective Systems Transformed Through "Serious" Game Play” at the International Conference on the Philosophy of Computer Games; “Foreign language learning in immersive virtual environments” at the IS&T/SPIE Electronic Imaging conference, and “Modeling Rich Characters in Interactive Narrative Games” and GAMEON-ASIA. Her recently published work includes “D.V. Modeling Appraisal in Theory of Mind Reasoning” in the Journal of Agents and Multi-Agent Systems, and book chapters “ Virtual Interactive Interventions for Reducing Risky Sex: Adaptations, Integrations, and Innovations” in  Interactive Health Communication Technologies: Promising Strategies for Health Behavior, and “Modeling Theory of Mind and Cognitive Appraisal with Decision-Theoretic Agents” in Social emotions in nature and artifact: Emotions in human and human-computer interaction.

Marjorie McShane develops cognitive models of intelligent agents that can collaborate with people in task-oriented, dialog applications. While at heart a linguist, she is particularly interested in the integration of functionalities that are often treated in isolation, such as physiological simulation, emotion modeling, and the many aspects of cognition. One aspect of cognition to which she has devoted particular attention is natural language processing, approached from a cross-linguistic perspective and with the goal of producing machine-tractable descriptions that can support sophisticated conversational agents. She has also worked extensively on cognitive modeling in the medical domain, to support the configuration of intelligent agents playing the roles of virtual patients and tutors in training applications such as the Maryland Virtual Patient system.McShane has (co-)authored four books: Agents in the Long Game of AI: Computational cognitive modeling for trustworthy, hybrid AI (MIT Press, 2024), Linguistics for the Age of AI (MIT Press, 2021), A Theory of Ellipsis (Oxford University Press, 2005), and An Innovative, Practical Approach to Polish Inflection (Lincom Europa, 2003). She has published extensively on linguistics, natural language processing, cognitive modeling, and knowledge representation.