From a variety of locations in the Capital Region, and throughout the country, Rensselaer Polytechnic Institute faculty, students, and staff are pressing their knowledge and machinery to work making personal protective equipment for those on the front lines of the pandemic.
The Rensselaer IDEA Health INCITE program is excited to announce immediate openings for six- and twelve-week undergraduate research opportunities for the Summer 2020 Term. All work will be done remotely. We are seeking students to work on data analytics research related to the COVID-19 pandemic. This work will include data analytics, web app development, and creation of social media content.
Attempting to use real medical data in a classroom setting is hard to do without limiting yourself to specific datasets. Through the research being presented we work to create an end-to-end workflow for generating synthetic health data and testing the synthetic data for privacy, resemblance, and utility. This includes creating a novel generation method called HealthGAN and defining metrics for measuring the privacy and resemblance of the generated data. The utility of the data is then measured in the context of the analysis task the dataset was designed to accomplish.
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 and social and communication networks. He enjoys poker, bridge, squash, tennis and badminton. For a full bio and more details, please visit his web page.
B.S., Physics, Yale University, 1993. M.S., Physics California Institute of Technology, 1995. PhD., EE/Physics, California Institute of Technology, 1998.
Rensselaer Polytechnic Institute researcher Malik Magdon-Ismail tailored the robust machine learning models he is developing for the COVID pandemic to work with sparse data points, like those available during the early phase in a pandemic or in smaller cities, which ordinarily make trend-spotting difficult.
Using daily updated data, COVIDMinder, a new data visualization tool, examines how and why COVID-19 impacts regions differently by comparing community risks, mediation tools, and outcomes related to COVID-19 by state across the United States, and by county within New York state.
On June 5-6, 2018 The Lally School of Management, the Rensselaer Institute for Data Exploration and Applications (IDEA) / Health INCITE, the Center for Global Communication+Design (Comm+D), and the Cognitive and Immersive Systems Lab (CISL) presented the 2018 Rensselaer Cognitive and Immersive Data Insights Application Challenge. More than 40 RPI undergrad and grad students competed in this inaugural challenge to create immersive, multimodal, collaborative applications using health and business datasets.
Marge 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.
Guided by the functional needs of such agents, McShane has been working on modeling “mindreading” (otherwise known as mental model ascription), defined as inferring features of another human or artificial agent that cannot be directly observed, such as that agent's beliefs, plans, goals, intentions, personality traits, mental and emotional states, and knowledge about the world. This capability is essential if intelligent agents are to engage in sophisticated collaborations with people.
McShane has authored two books, A Theory of Ellipsis (Oxford University Press, 2005) and An Innovative, Practical Approach to Polish Inflection (Lincom Europa, 2003), and recently co-authored a third, Linguistics for the Age of AI (with Sergei Nirenburg; MIT Press, 2021). Beyond books, she has published extensively on linguistics, natural language processing, cognitive modeling, and knowledge representation.
PhD, Slavic Languages and Literatures, Princeton University
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