/Several faculty members from around the U.S. named Google Research Scholars (via Qpute.com)
Several faculty members from around the U.S. named Google Research Scholars

Several faculty members from around the U.S. named Google Research Scholars (via Qpute.com)

Nihar Shah, Carnegie Mellon University. Photo: cs.cmu.edu

Google AI announced April 7, 2021 the recipients of its Research Scholar Program to support early-career professors who are pursuing research in fields relevant to Google.

13 professors from the U.S and one from India, who are working on cutting edge research across many research areas in computer science, including machine learning, human-computer interaction, health research, systems and more, are among the 86 award recipients in the first year of the program representing 15+ countries and over 50 universities, according to a press release from Google.

Srinath Sridhar, Brown University. Photo: cs.brown.edu

The Research Scholar Program provides unrestricted gifts to support research at institutions around the world, and is focused on funding world-class research conducted by early-career professors.

Introduced in March 2020, the program is an effort focused on developing collaborations with new professors and encouraging the formation of long-term relationships with the academic community.

Ashok Ajoy, University of California, Berkeley. Photo: chemistry.berkeley.edu

Faculty awardees with their proposals –

Pravesh K. Kothari, Carnegie Mellon University
Efficient Algorithms for Robust Machine Learning

Srinath Sridhar, Brown University
Perception and Generation of Interactive Objects

Arvind Satyanarayan, Massachusetts Institute of Technology
Generating Semantically Rich Natural Language Captions for Data Visualizations to Promote Accessibility

Tanushree Mitra, University of Washington. Photo: ischool.uw.edu

Tanushree Mitra, University of Washington
Supporting Scalable Value-Sensitive Fact-Checking through Human-AI Intelligence

Aravindan Vijayaraghavan, Northwestern University and Sivaraman Balakrishnan, Carnegie Mellon University
Principled Approaches for Learning with Test-time Robustness

Nihar Shah, Carnegie Mellon University
Addressing Unfairness in Distributed Human Decisions

Aruna Balasubramanian, State University of New York – Stony Brook
AccessWear: Ubiquitous Accessibility using Wearables

Aurojit Panda, New York University
Bertha: Network APIs for the Programmable Network Era

Rachit Agarwal, Cornell University
Designing Datacenter Transport for Terabit Ethernet

Ashok Ajoy, University of California, Berkeley
Accelerating NMR spectroscopy with a Quantum Computer

Shruti Puri, Yale University
Surface Code Co-Design for Practical Fault-Tolerant Quantum Computing

Adwait Jog, College of William & Mary
Enabling Efficient Sharing of Emerging GPUs

Vineeth N Balasubramanian, Indian Institute of Technology Hyderabad
Bridging Perspectives of Explainability and Adversarial Robustness


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