News Release
UC San Diego Students Honored with Microsoft Ph.D. Fellowships
San Diego, Calif., Feb. 3, 2017 -- The University of California San Diego is the only campus to receive more than one Microsoft Ph.D. fellowship this year. The two students that earned the award are Bita Darvish Rouhani, an electrical and computer engineer, and computer scientist Mengting Wang.
Each year the research division of Microsoft awards Ph.D. fellowships to a small group of particularly deserving graduate students, and the competition is intense. Ten Ph.D. students across the nation receive the award each year.
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Bita Darvish Rouhani
Rouhani is a second-year Ph.D. student in the Department of Electrical and Computer Engineering at UC San Diego. She joined last year the research group of Professor Farinaz Koushanfar.
She plans to use her Microsoft Ph.D. Fellowship to pursue work in her chosen field of computer architecture and hardware. Her other current research interests include algorithms, machine learning and deep learning, distributed optimization, big-data analysis with low-dimensional models, reconfigurable computing and hardware/software co-design.
Rouhani completed her undergraduate degree at Iran’s Sharif University of Technology in 2013, and finished a master’s at Rice University in 2015 before enrolling in UC San Diego’s Jacobs School of Engineering.
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Mengting Wan
Wan plans to use her two-year fellowship to cover all her costs for tuition, travel, and living expenses that will take her through completing her Ph.D. in computer science, expected in 2019. Wan works in data mining, machine learning and computational social science, and her advisor is computer science professor Julian McAuley.
"The balance between mathematical rigor and real-world applications is the greatest strength of Mengting Wan’s research,” said McAuley, who leads the Artificial Intelligence Group. “Her combination of strengths and interests allows her to combine models from economics, machine learning and natural-language processing, while bringing a unique perspective to explain the relationship between problems that would never have occurred to me before collaborating with her."
Wan builds scalable, machine-learning algorithms to process massive (and heterogeneous) real-world human activity datasets, and applies it to areas including e-commerce, recommender systems (for example Amazon’s success in recommending future purchases based on the consumer’s previous orders on Amazon), and opinion-oriented question answering (QA) systems.
She joined the Jacobs School after completing a master’s in statistics at the University of Illinois at Urbana-Champaign in 2015. She did her undergraduate degree at Peking University, also in statistics, where she received her bachelor’s in 2013.
Last summer she did an internship at the Microsoft Research facility in Redmond, Wash.
Media Contacts
Doug Ramsey
Jacobs School of Engineering
858-822-5825
dramsey@ucsd.edu