TWed Lightning Talks (Fall 2020)

Plan to join us WEDS, 09 Dec for a very, VERY special TWed as the Tetherless World Constellation holds another "virtual" version of our end-of-term Graduate Research
"Lightning Talks." TWed Lightning Talks are a great way for the TWC community and friends to learn of the wide range of amazing research happening in the Tetherless World, and "a good time is had by all!"

Lightning talks are VERY short --- approx. 2-3 minute! --- summaries by our students of current research work, with no NO SLIDES and only brief "crib notes."
 

Privacy Attacks in the context of Machine Learning

This talk will be an introduction to the study of privacy attacks in the context of machine learning, aimed at those unfamiliar with the literature. We will discuss who the stakeholders are, what information may be attacked, how it may be attacked, and why. The “how” will be at a high level, illustrated through some specific examples of privacy attacks.

Tackling Health Inequity using Machine Learning Fairness, AI, and Optimization

Miao will discuss the tools and techniques used to assess, visualize, and improve equity in clinical trials. A set of novel equity metrics for clinical trials is constructed from Machine Learning (ML) Fairness Research to quantify inequities of various subgroups defined over multiple demographic or clinical characteristics, such as Hispanic female subjects who are underweight or no-Hispanic black male subjects aged over 64 and with high fasting glucose level.

App Developed at Rensselaer Can Help Guide COVID-19 Management on Any Campus

In the midst of the COVID-19 pandemic, as Rensselaer leaders prepared to bring students back to campus for the fall 2020 semester, they relied on a powerful algorithm to determine a testing schedule that, along with other tools, has helped maintain a safe environment on campus. That algorithm is now publicly available as a free online app.

Anonymous (not verified) Wed, 11/11/2020 - 19:00

MortalityMinder: A Web Tool for Visualizing and Investigating Social Determinants of Premature Mortality in the United States

Challenge: Midlife mortality rates are rising in the United States (US), while in many other nations, mortality rates are decreasing. For example, Stein et al. (2017) found that “Deaths of Despair” due to suicide and substance abuse have increased dramatically among white males between the ages of 25-64 particularly in rural America. The MortalityMinder (MM) app’s goal is to enable healthcare researchers, providers, payers, and policy makers to gain actionable insights into how, where, and why midlife mortality rates are rising in the US.System

Santiago Paternain

Santiago Paternain

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.

Education

Santiago Paternain received the B.Sc. degree in electrical engineering from Universidad de la República Oriental del Uruguay, Montevideo, Uruguay in 2012, the M.Sc. in Statistics from the Wharton School in 2018 and the Ph.D. in Electrical and Systems Engineering from the Department of Electrical and Systems Engineering, the University of Pennsylvania in 2018.

Focus Area

Control of Dynamical Systems, Machine Learning, Optimization

Selected Scholarly Works

Santiago Paternain and Alejandro Ribeiro. "Stochastic Artificial Potentials for Online Safe Navigation", IEEE Transactions on Automatic Control, vol: 65, issue: 5, May 2020,pp.1985-2000.

Luiz F.O. Chamon, Santiago Paternain, Miguel Calvo-Fullana and Alejandro Ribeiro. "The Empirical Duality Gap of Constrained Statistical Learning". In Proc. 45th International Conference on Acoustics, Speech, and Signal Processing, Barcelona, Spain, May 4-8 2020 (Best Student Paper award)..

Santiago Paternain, Miguel Calvo-Fullana, Luiz F.O. Chamon and Alejandro Ribeiro. "Constrained Reinforcement Learning Has Zero Duality Gap" In Proc. 33rd Conference on Neural Information Processing Systems, vol. 7553-7563. Vancouver, Canada, December 8-14,2019.

Santiago Paternain and Alejandro Ribeiro "Safe Online Navigation of Convex Potentials in Spaces with Convex Obstacles", In proc. 56th Annual Conference on Decision and Control, vol.24732478. Melbourne, Australia. December 12-16 2017 (Best Student Paper Award).

The Dengue Spread Information System (DSIS)

Mosquitoes are responsible for transfer of many vector-borne diseases. Dengue is one such viral infection that is transmitted by the Aedes mosquito. It is preventable but still the number of Dengue cases have risen 30-fold in the past 50 years. In several countries in south American continent and Asia, dengue is one of the leading causes of death. It is mainly found in tropical and sub-tropical regions, particularly surrounding urban and semi-urban areas.

TWed Talk: Henrique Santos (TWC) on "Making Sense of Common Sense"

DESCRIPTION: The goals of commonsense reasoning systems include being able to answer commonsense reasoning questions. In order to compare systems, a number of benchmark question sets have arisen. Leaderboards have emerged to act as hubs for hosting benchmarks and supporting infrastructure that accepts submissions of commonsense reasoning systems that then get scored against the benchmarks. These benchmarks vary in structure.

Privacy-Preserving Synthetic Health Data for Research and Education

The inability to share private health data can severely stifle research and innovation in health informatics. Studies based on unpublished electronic medical record (EMR) data cannot be reproduced, thus future researchers are not able to use them to develop and compare new research. This contributes to the reproduciblity crisis in biomedical research. Making open data available for research can spur innovation and research. The public Medical Information Mart for Intensive Care datasets, MIMIC-II and MIMIC-III, are widely used with over 2000 citations reported in Google Scholar in March 2020. But since MIMIC-II and MIMIC-III focus on Intensive Care Unit patients in Boston hospitals, the resulting research may be biased and have limited generalization. The cost and time required, along with re-identification risk concerns make de-identification only a partial solution to this problem.

Privacy-Preserving Synthetic Health Data for Research and Education

The inability to share private health data can severely stifle research and innovation in health informatics. Studies based on unpublished electronic medical record (EMR) data cannot be reproduced, thus future researchers are not able to use them to develop and compare new research. This contributes to the reproduciblity crisis in biomedical research. Making open data available for research can spur innovation and research.