UMD Center for Machine Learning Announces 2020 Class of Rising Stars

The University of Maryland Center for Machine Learning will host four female researchers this fall as part of a program that encourages and supports underrepresented doctoral candidates whose scientific work is focused on machine learning.

Diana Cai, Irene Chen, Mahsa Ghasemi and Nan Rosemary Ke (pictured clockwise from top left) were recently selected as this year’s Rising Stars in Machine Learning based on their novel research, academic accomplishments and exceptional work experience.

The Rising Stars program, launched by the center last year, is focused on supporting upper-level graduate students from disadvantaged or underrepresented groups as they pursue new scientific discoveries and academic opportunities in machine learning.

This year’s cohort—who hail from Princeton University, the Massachusetts Institute of Technology, the University of Texas at Austin and the University of Montreal—were chosen from a competitive pool of 17 applicants.

"After extensive review, we chose these four candidates based on their record of excellence in research and scholarship,” said Soheil Feizi, assistant professor of computer science and a core faculty member in the Center for Machine Learning. “We are very excited to have these candidates visit us [virtually] and present their work at our distinguished seminar series."

The four Rising Stars will each present their research as part of this semester’s Machine Learning Seminar Series, a set of virtual talks that highlight theoretical and applied aspects of machine learning, artificial intelligence and related topics.

In light of the COVID-19 pandemic, the winners will receive a financial award in lieu of travel expenses to visit the University of Maryland campus.

For announcements on the Rising Stars in Machine Learning speaker schedule, follow the UMD Center for Machine Learning on twitter @ml_umd; or, signup for the center’s email list here.

See brief bios below for each of the 2020 Rising Stars is Machine Learning:

Diana Cai is a fourth-year doctoral student in computer science at Princeton University. Her research is focused on developing and analyzing methods aimed at robustness for model misspecification, computational limitations, and data quality and availability. She is a recipient of Google’s Ph.D. Fellowship in Machine Learning, and interned at the Google research office in New York last summer.

Irene Chen is a is a fifth-year doctoral student in computer science and electrical engineering at the Massachusetts Institute of Technology. Her research is at the intersection of machine learning, healthcare and inequality. She audits and improves existing healthcare algorithms on discrimination and inequality, in addition to developing new algorithms for patients from disadvantaged groups. Chen previously worked at Dropbox as a data scientist, chief of staff and a machine learning engineer.

Mahsa Ghasemi is a fourth-year doctoral student in electrical and computer engineering at the University of Texas at Austin. The objective of her research—which intersects at control, machine learning and information theory—is to enable autonomous robots to make good decisions. In other words, she develops algorithms that equip autonomous agents with intelligent ways of efficiently incorporating data into decision-making.

Nan Rosemary Ke is a fifth-year doctoral student the University of Montreal, and a recipient of Facebook’s machine learning fellowship. The ultimate goal of her work is to build algorithms that can utilize past experiences to systematically generalize and transfer to new problems easily and efficiently. Ke has interned at Google Deepmind, Facebook AI Research, and Microsoft Research.

—Story by Maria Herd

The University of Maryland Center for Machine Learning, supported in part by financial and technology leader Capital One, is one of five major centers in the University of Maryland Institute for Advanced Computer Studies (UMIACS).