Risky Business? Deep Dives into DeFi

We seek to investigate current patterns of usage in DeFi lending protocols, and quantify risk and user behaviors across various protocols. Our strategy is to exploit powerful AI models and technology developed for transaction data such as those arising in health and commerce. For example, we can utilize temporal clustering to characterize different types of users and then use these in a dashboard to understand how usage of lending protocols changes over time.

IDEA Cluster Details

The IDEA Cluster is a high performance computing environment consisting of five Intel Xeon and two AMD compute servers in various configurations ranging from 24-40 cores (48-80), 256GB-1TB RAM, and up to four GPUs per machine (Tesla K40m or Titan RTX). The IDEA Cluster includes two dedicated storage servers totaling more than 40TB of usuable space. The IDEA Cluster is designed for dedicated data mining, machine learning, and neural computing-intensive jobs using popular toolkits.

Oak Ridge Scientists Mentor ITWS Students erickj4 Thu, 11/10/2022 - 13:24

Data analytics students at Rensselaer Polytechnic Institute have the opportunity to partner with scientists at Oak Ridge National Laboratory (ORNL) to address global challenges.

Predicting Responses to Public Health Messaging erickj4 Fri, 11/04/2022 - 14:42

By Debjani Ray-Majumder, Ph.D. candidate of decision science and engineering systems

RPIrates: Michael Liu on "The Cohoes Floating Solar Explorer" (05 Oct 2022)

Michael Liu takes us on a tour of the Floating Solar Explorer, an interactive, GIS-based R Shiny web app that visualizes water reservoirs alongside economic data and political boundaries. Along with the website itself, the presentation explores certain aspects of the data generation process using R and provide an introduction to R Shiny.

William Wallace

Professor Emeritus
 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.  

Oshani Seneviratne

Assistant Professor and Associate Director of Tetherless World Constellation

Oshani Seneviratne is the Associate Director of the Tetherless World Constellation and an Assistant Professor in Computer Science. She was previously the Director of Health Data Research at the Rensselaer Institute for Data Exploration and Applications. Oshani obtained her S.M. and Ph.D. degrees in Computer Science from the Massachusetts Institute of Technology (MIT) under the supervision of Sir Tim Berners-Lee, the inventor of the World Wide Web. Before Rensselaer, Oshani worked at Oracle, specializing in knowledge representation, provenance, and healthcare-related research. 

Oshani's research interests span data integration in knowledge graphs, artificial intelligence, decentralized systems (web and blockchain), and health informatics. At MIT, Oshani conducted research on Accountable Systems for the Web. As part of her Ph.D. at MIT, Oshani developed a novel web protocol called HyperText Transfer Protocol with Accountability.

Oshani co-founded and co-organized the AIChain workshop series co-located with the IEEE Blockchain conference, the Personal Health Knowledge Graph workshop series, the Healthcare and Life-Sciences Symposium, the Decentralized Knowledge Graph track at the Knowledge Graph Conference, and the AAAI Fall Symposium series on Artificial Intelligence for Social Good. Oshani has served in the organizing committees of the International Semantic Web Conference and Web Science conference in various roles. Oshani is a co-editor of the Semantic Technologies for Data and Algorithmic Governance issue at the Semantic Web Journal and the Personal Health special issue at the Data Intelligence journal. She also actively reviews the journals such as Web Semantics, Semantic Web, Medical Internet Research, Biomedical and Health Informatics, and many conferences, including the International Semantic Web Conference, Web Conference, Web Science Conference, IEEE Blockchain Conference, and IEEE Decentralized Applications Conference.

Liu Liu

Assistant Professor

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.

Shaowu Pan

Assistant Professor

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, and dynamical systems. He has published his work in journals like the Journal of Fluid Mechanics, AIAA Journal, SIAM Applied Dynamical Systems, Chaos, Computer Methods in Applied Mechanics and Engineering, Computational Mechanics, etc.