Rising Stars in Machine Learning
The University of Maryland Center for Machine Learning invites graduate students and postdocs from underrepresented groups to apply to its Rising Stars in Machine Learning program. People who identify as women, Black, Latinx, Indigenous, LGBTQIA+ or living with disabilities are underrepresented in computer science and machine learning. The goal of this program is to support machine learning researchers from these underrepresented groups as they pursue new scientific discoveries and academic opportunities.
Due to the high volume of excellent applications this year, the search committee chose to recognize six winners. In addition to presenting their research as part of our virtual distinguished ML seminar series, each rising star in machine learning will receive a $1,000 honorarium.
For announcements regarding this program, signup for our email list. Rising Stars in Machine Learning is organized and led by Assistant Professor of Computer Science Soheil Feizi with the help of other CML faculty. Questions can be directed to ml@umiacs.umd.edu.
2022 Rising Stars
2021 Rising Stars
Tian Li
Doctoral Student at Carnegie Mellon University
"On Heterogeneity in Federated Settings"
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Xinyun Chen
Doctoral Student at the University of California, Berkeley
“Deep Learning for Program Synthesis: Towards Human-like Reasoning”
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Qi Lei
Associate Research Scholar at Princeton University
“Provable Representation Learning: The Importance of Task Diversity and Pretext Tasks"
Personal Page2020 Rising Stars
Diana Cai
Doctoral Student at Princeton University
“Probabilistic Inference Under Model Misspecification”
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Irene Chen
Doctoral Student at Massachusetts Insititute of Technology
“Machine Learning for Equitable Healthcare”
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Mahsa Ghasemi
Doctoral Student at The University of Texas at Austin
“Efficient Data Processing and Trustworthy Decision Making through Structured Task Representation”
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Nan Rosemary Ke
Doctoral Student at University of Montreal
"From 'What' to 'Why': Towards Causal Deep Networks”
Personal Page2019 Rising Stars
Surbhi Goel
Doctoral Student at The University of Texas at Austin
“Provably Efficient Algorithms for Learning Neural Networks”
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Adji Bousso Dieng
Doctoral Student at Columbia University
“Learning with Deep Probabilistic Generative Models”
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Karolina Gintare Dziugaite
Fundamental Research Scientist at Element AI
“PAC-Bayesian Approaches to Understanding Generalization in Deep Learning”
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