Geri Louise Dimas is a Ph.D. Candidate in the Data Science Program at Worcester Polytechnic Institute, and Co-Director of the Institute for the Qualitative Study of Inclusion, Diversity, and Equity (QSIDE) Stopping Trafficking And Modern-day Slavery Project (STAMP) Lab. Her research focuses on applications of applied analytics and data science at the intersection of societal issues such as immigration, anti-human trafficking, and homelessness.

A widely respected neuroscientist, Jean King joined the WPI community as the Peterson Family Dean of Arts and Sciences in 2017. In addition to her duties as dean, she is a professor in the Department of Biology and Biotechnology. Dr. King’s research uses functional magnetic resonance imaging (fMRI) to identify and monitor neuronal plasticity associated with addiction, ADHD, depression, fearfulness, anxiety, autism and neurological disorders (PD and TBI) in animal models with the hope of finding clues to help us understand these conditions in humans. Dr. King has published over 60 original scientific papers in highly respected international scientific journals, over 10 chapters in books and review articles in major neurophysiology journals, and is an editor of New York Academy of Sciences Publication – Roots of Mental Illness in Children. Prior to joining WPI, she was vice provost for biomedical research at the University of Massachusetts Medical School; a tenured professor of psychiatry, radiology, and neurology; and director of the university’s Center for Comparative Neuroimaging.

Tasha is a Research Associate at the Colorado School of Mines working to better understand high latitude ocean and glacier change and how it will impact the planet. She received her PhD in Geography at the University of Colorado Boulder studying glaciology, but also has an interdisciplinary research background in paleoceanography and marine ecology. Her current work focuses on how oceans interact with glaciers in Greenland and Antarctica, and she is developing new ways to apply satellite thermal infrared imagery to study these systems. She specializes in remote sensing, machine learning, and open science. One of her most exciting projects at the moment is leading the CryoCloud cloud-computing project (cryointhecloud.com) to help usher NASA Cryosphere communities into the cloud and build open-source science infrastructure and community best practices. Aside from her research interests, she is a veteran of the US Navy and is passionate about helping others to develop more inclusive leadership skills in academia. 

Laureen Elgert is an Associate Professor of International Development and Environmental Policy, currently serving as Head of the Department of Integrative and Global Studies (DIGS) at WPI. Laureen’s research and teaching interests focus on the environment-development nexus, where tensions between sustainability and livelihoods often lead to contentious policy debates. My work on soy production and land inequality, expert roundtables and certification, and sustainability rating systems for cities, advanced ideas around how expert, global discourses about sustainable agriculture and sustainability indicators take shape, are mobilized, and have influence at the local level, impacting social, political, and environmental systems. Laureen is co-editor of “Social Movements and the Struggles for Rights, Justice, and Democracy in Paraguay” (Springer, 2022).

 

 

Dr. Chaitra Gopalappa is an associate professor of industrial engineering and operations research at the Department of Mechanical and Industrial Engineering and Commonwealth Honors College at the University of Massachusetts, Amherst. She is also a guest researcher at the U.S. Centers for Disease Control and Prevention. Her work is in the area of simulation, simulation-based optimization, reinforcement learning and machine learning, and stochastic processes. Her lab focusses on developing mathematical and computational models to inform public health policies. Recent work includes use of machine learning methods to capture the interactions between interrelated sexually transmitted diseases and social determinants of health, to subsequently quantify disease risk attributed to social and economic conditions, understand social needs of persons at risk of disease, and inform structural interventions. Her lab is funded by grants from the National Institutes of Health, the National Science Foundation, the U.S. Centers for Disease Control and Prevention, and the World Health Organization.

Dynamic simulation models are a critical tool to evaluate the impact of alternative disease intervention combinations to identify the strategy that is most optimal at controlling an outbreak.  The fundamental building blocks of most infectious disease models are to simulate human behaviors such as contact networks, and testing and treatment behaviors. However, data show that disease cases are concentrated among populations in low socio economic conditions and further that social and economic factors are drivers of behaviors that increase risk of diseases. While behaviors are fundamental mathematical mechanisms for predicting the spread of diseases, modeling behaviors alone without the factors that drive them can enormously misrepresent intervention needs. These data also suggest that social factors are common risk factors of multiple diseases, and as such, the need for a method to jointly modeling related diseases to inform optimal allocation of resources through a unified approach to disease prevention. I will discuss some of our work in use of machine learning methods to address the challenges associated with building such a multi-disease model and simulating behaviors as functions of social determinants, related to sexually transmitted diseases.

Lab website: https://diseasemodeling.github.io/

Talk Title: Follow the data: social factors are among key drivers of disease risk. Building disease prediction models informed by data

Dr. Astitha is an Associate Professor and the Associate Department Head for Graduate Education, Equity and Inclusion at the Department of Civil and Environmental Engineering, University of Connecticut (UConn). Dr. Astitha has 15 years of experience in atmospheric numerical modeling systems from regional to global scales. She is leading the Atmospheric Modeling and Air Quality Group (https://airmg.uconn.edu/) since joining UConn in 2013. The group currently consists of PhD, MS and undergraduate students in Environmental Engineering conducting research on extreme weather prediction, air quality modeling systems, and integration of numerical models with machine learning algorithms for error reduction and new model development (weather and water quality applications). Dr. Astitha’s group is also conducting research related to renewable energy (offshore wind farms) and storm forecasting that impacts power distribution in the NE US. Dr. Astitha is committed to support, mentor, and inspire the next generation of engineers to innovate, lead and thrive in solving complex environmental problems and sustain a healthy society in the years to come.

Group website: airmg.uconn.edu

Talk Title: Environmental modeling for extreme weather, offshore wind farms and lake water quality: how to integrate physics-based models with machine learning