UNC Computer Science’s 55th anniversary year brings a new line-up of faculty and researchers

2019/2020 brings a prestigious group of faculty researchers to UNC Chapel Hill’s Department of Computer Science.

“We are proud to welcome an exceptional cohort to UNC Computer Science, adding to our already accomplished and internationally recognized faculty team,” states Gillian T. Cell Distinguished Professor of Computer Science and UNC CS Department Chair Kevin Jeffay.

“Together, we are home to several National Science Foundation CAREER awards, a Presidential Early Career Award for Scientists and Engineers (PECASE), DARPA Young Faculty Award and Director’s Fellowship, and many other notable awards. This new team will continue our long standing tradition in excellence and exemplifies our commitment to innovation, propelling students and research for the next 55 years.”

Meet the UNC Department of Computer Science 2019/20 faculty cohort:

Samarjit ChakrabortySamarjit Chakraborty

As a William R. Kenan, Jr. Distinguished Professor at UNC CS, Samarjit Chakraborty will continue his research on real-time and embedded systems for electric vehicles. From 2008 to 2019, Chakraborty was a professor of electrical engineering at the Technical University of Munich in Germany, where he served as chair of real-time computer systems. From 2011 to 2016 he also led a research program at the TUMCREATE Center for Electromobility in Megacities in Singapore, where he also served as a scientific advisor. He was an assistant professor of computer science at the National University of Singapore from 2003 to 2008. He obtained his doctorate in electrical engineering from ETH Zurich in 2003. Chakraborty has received many distinctions for his research, including the ETH Medal and the European Design and Automation Association’s Outstanding Dissertation Award in 2003 and best paper and demo awards at many of the top conferences in real-time and embedded systems. In addition to funding from several governmental agencies, his work has also been supported by grants from General Motors, Intel, Google, BMW, Audi, Siemens and Bosch.


Snigdha ChaturvediSnigdha Chaturvedi

Snigdha is excited about natural language understanding, with a focus on narratives and social aspects of language.

Prior to joining the Department of Computer Science, Chaturvedi was an assistant professor at the University of California, Santa Cruz (2018-2019) and a postdoctoral researcher at the University of Pennsylvania and University of Illinois at Urbana-Champaign. She received her doctorate from the University of Maryland, College Park in 2016. Snigdha is the recipient of the IBM PhD fellowship in 2014-15 and 2015-16; a best paper award at NAACL 2016; and the first prize at ACM Student Research Competition at GHC 2014.


Bo DaiBo Dai

Bo Dai’s research interest lies broadly in machine learning, especially in principled machine learning methods using optimization tools for reinforcement learning and representation learning on structured data, as well as various applications. Dai obtained his doctorate in computational science and engineering in 2018 at the Georgia Institute of Technology. He is the recipient of best paper awards at AISTATS 2016 and NIPS 2017 workshop on Machine Learning for Molecules and Materials.


Sridhar DuggiralaParasara Sridhar Duggirala

Sridhar Duggirala is developing scalable algorithms to verify complex interactions between the physical and cyber world. Before joining UNC as an assistant professor, he was an assistant professor in the Computer Science and Engineering Department and UTC Institute for Advanced Systems Engineering at the University of Connecticut from 2015 to 2018. He received his doctorate from the University of Illinois at Urbana-Champaign in 2015. Duggirala received the Best Paper Award at the International Conference on Embedded Software (EMSOFT) 2013, Most Promising Benchmark Result by Robert Bosch at ARCH Workshop in CPS Week 2015, and the Best Paper Award at ARCH Workshop in CPS Week 2017. He was selected as a Young Researcher to attend the Heidelberg Laureate Forum in 2014.


Colin RaffelColin Raffel

Colin Raffel’s research focuses on developing machine learning techniques, especially semi-supervised, unsupervised, and transfer learning methods for learning from limited labeled data. Raffel’s most recent work has been as a senior research scientist at Google Brain. He completed his doctorate at Columbia University, and holds a master’s degree in music, science and technology from Stanford University’s Center for Computer Research in Music and Acoustics. Raffel received the Best paper at the 16th International Society for Music Information Retrieval Conference in 2016, Best Poster at the 15th International Society for Music Information Retrieval Conference in 2015, and the NSF Integrative Graduate Education and Research Training Fellowship (2012-2015).


Shashank SrivastavaShashank Srivastava

Shashank Srivastava studies natural language processing, machine learning and interactive methods for AI. Srivastava received a doctorate from the Machine Learning Department at Carnegie Mellon University in 2018, and was an AI resident researcher at Microsoft Research in 2018-19. He previously received a master’s degree in language technologies from Carnegie Mellon in 2014. Shashank received the Yahoo! InMind Fellowship for 2016-17, and his research has been covered by popular media outlets including GeekWire Magazine and New Scientist.

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