Five SCS Students Named Siebel Scholars
Wednesday, September 29, 2021 - by Aaron Aupperlee
Five graduate students at Carnegie Mellon University's School of Computer Science have received Siebel Scholars awards for 2022. Karan Ahuja, Priya Donti, Yasmine Kotturi, Ryan Shi and Kayo Yin will each receive $35,000 as part of the program.
"Every year, the Siebel Scholars continue to impress me with their commitment to academics and influencing future society. This year's class is exceptional, and once again represents the best and brightest minds from around the globe who are advancing innovations in healthcare, artificial intelligence, financial services and more," said Thomas M. Siebel, chairman of the Siebel Scholars Foundation. "It is my distinct pleasure to welcome these students into this ever-growing, lifelong community, and I personally look forward to seeing their impact and contributions unfold."
Ahuja is a Ph.D. candidate in the Human-Computer Interaction Institute (HCII) whose research focuses on machine learning and sensing. Using computer vision, signal processing and applied machine learning, Ahuja creates novel sensing and interaction technologies. His work has applications in areas such as augmented and virtual reality, health monitoring, activity recognition and context-aware computing.
Donti, a Ph.D. candidate in the Computer Science and Engineering and Public Policy departments, focuses on using machine learning to tackle climate change. Her research incorporates the physics and hard constraints associated with power grids into neural networks to guarantee the safety of the systems, and to increase their efficiency through machine learning. Donti co-founded Climate Change AI and was recently named to MIT Technology Review's list of 35 Innovators Under 35.
Kotturi, a Ph.D. candidate in the HCII, focuses on co-designing a more inclusive future of work for minority workers. Kotturi creates peer-to-peer software systems that leverage both human and machine intelligence to scaffold skill, identity and career development among individuals engaged in nontraditional, alternative working arrangements. Kotturi's research informs new design methods for an inclusive future of work for vulnerable workers and contributes two open-source software systems that introduce novel algorithms and interaction design paradigms to support human-machine collaboration.
Shi, a Ph.D. candidate in the Institute for Software Research, studies how AI can help people. His research areas include online learning, game theory and reinforcement learning. Shi develops AI-based tools to help with the operations of nonprofit organizations in food security, wildlife conservation and public health. Some of his projects are already in use. He also helped organize the 2021 AI for Social Good Symposium.
Yin is a master's student in the Language Technologies Institute, where she researches multilingual natural language processing. Her long-term research goal is to break down communication barriers between people and between computers and people through NLP technologies. She wants to improve how computers understand and respond to different languages so more people can benefit from the technology. Yin's paper on including signed languages in NLP won the Best Theme Paper award at this year's Annual Meeting of the Association for Computational Linguistics.
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