CSE DSI Research Support

The CSE DSI is able to provide seed funding for small projects at the initial stage of research that bring college faculty in data science and science and engineering together.

This funding is in the form of graduate student fellowships where the student is participating in the research and is mentored by at least two faculty from different departments. The initial results from these small projects are expected to form the basis for future larger research proposals.

The call for proposals is usually announced as part of our community-building exercises around a specific topic area chosen in response to interests expressed by our affiliated faculty. The announcement will be circulated to all CSE DSI affiliates.

The table below shows the range of projects supported to date.

Research TopicFellowsFaculty

Towards Unconstrained Multi-sensor “State-of-the-Heart” Monitoring and Disease Prediction

Xiangzhen (Raven) Kong
Yijun Lin

Alena Talkachova (BME)
Yao-Yi Chiang (CS&E)

Large Scale Data Extraction from Population Sampling of Dispersed Waterborne Photovoltaic Microparticles

Tianqi Luo
Yijun Lin

Joey Talghader (ECE)
Yao-Yi Chiang (CS&E)
Daniel Bond (Microbiology)

Can Physically Informed Deep Generative Models Improve Seasonal Predictability of Global Precipitation?

Reyhaneh Rahimi

Ardeshir Ebtehaj (CEGE)
Vipin Kumar (CS&E)

Sharp Analysis of Atomic-Resolution STEM Data via Deep Learning

Zhong Zhuang
Hengkang Wang

Ju Sun (CS&E) 
Andre Mkhoyan (CEMS)

Constrained Deep Learning for the Efficient Discovery of Stable Solid-State Materials

Jane Schlesinger
Ryan Devera

Chris Bartel (CEMS) 
Ju Sun (CS&E)

Accelerating Novel 2D Material Discovery Through Machine Learning

Wei Ren
Kyle Noordhoek

Ke Wang (Physics) 
Chris Bartel (CEMS)

Learning Using Privileged Information (LUPI) for Materials Discovery

Eng Hock Lee

Vladimir Cherkassky (ECE)
Tony Low (ECE) 
Ellad Tadmor (AEM) 
Eric Fuemmeler (AEM)

Integrated Molecular Simulations and Machine Learning Tools to Uncover the Treasure Trove of Hidden Structures during Crystallization

Steven Hall

Sapna Sarupria (CHEM)
Michael Steinbach (CS&E)

Computationally Efficient Bayesian Inference for Population Properties of AstrophysicalXiao-Xiao KouGalin Jones (STAT)
Vuk Mandic (PHYS)
Accelerating Electromagnetic Design and Simulations with Physics-Informed Artificial IntelligenceBinyao Guo
Samuel Dietterich
Qizhi He (CEGE)
Shaul Hanany (PHYS)
Event Identification from the Sun throughout the Solar SystemJangHyeon Lee
William Setterberg
Yao-Yi CHiang (CSE)
Lindsay Glesener (PHYS)
Post-processing Techniques in Neural Gradient Networks with Applications to Inverse Problems in AstrophysicsAndrew Toivonen
Akshay Kumar
Michael Coughlin
Jarvis Haupt
Vuk Mandic
Building Multi-modal Foundation Models for Supernovae DataFelipe Fontinele Nunes
Wenya Xie
Ray Liu
Michael Coughlin