Nikita Mishra

Machine learning leader with 8+ years of experience in personalization, search, and recommender systems. Currently managing an Applied Science team at Twitch, delivering state-of-the-art foundational models powering discovery and feed ranking. Published in top-tier venues (ASPLOS, MICRO, UAI) with a strong track record of turning research into impactful ML products.

• IEEE Micro Top Picks Honorable Mention 2019: Honorable Mention for our paper in the Top Picks from the Computer Architecture Conferences, in its May/June 2019 issue.
• University unrestricted(UU) fellowship 2015: Research fellowship in Computer Science at The University of Chicago.
• Best thesis award in Integrated Masters in Statistics at IIT Kharagpur 2012: Awarded for best thesis for thesis title Clustering and Classification Techniques for Directional and Mixture Datasets, among students in Integrated Masters of Science in Statistics and Informatics at Indian Institute of Technology Kharagpur.
• McCormick Fellowship 2012: Selected for McCormick fellowship during admission at The University of Chicago, PhD program in Computer Science.
• CRUISE Scholarship 2011: Selected as research Intern in School of Computing, Georgia Institute of Technology.
• Kishore Vigyanik Protsahan Yojana Scholarship 2007: Selected as a fellow in Science stream under KVPY by Indian Institute of Science.
• Google Travel Award at WWW-2011

• Proteus: Language and Runtime Support for Self-Adaptive Software Development - S Barati, FA Bartha, S Biswas, ... Nikita Mishra (Alphabetical list of authors) in IEEE Software, 2019.
• Controlling AI Engines in Dynamic Environments - Nikita Mishra, Connor Imes, John D. Lafferty, Henry Hoffmann, in (SysML-2018), February 2018.
• CALOREE: Learning Control for Predictable Latency and Low Energy. - Nikita Mishra, Connor Imes, John D. Lafferty, Henry Hoffmann, International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS-2018).
• Memory cocktail therapy: a general learning-based framework to optimize dynamic tradeoffs in NVMs. Deng, Zhaoxia, Lunkai Zhang, Nikita Mishra, Henry Hoffmann, and Frederic T. Chong. IEEE/ACM International Symposium on Microarchitecture (MICRO-2017).
• ESP: A Machine Learning Approach to Predicting Application Interference. Nikita Mishra, John D Lafferty, Henry Hoffmann - IEEE International Conference on Autonomic Computing (ICAC-2017).
• (Nearly) Optimal Differentially Private Stochastic Multi-Arm Bandits- Nikita Mishra, Abhradeep Thakurta, To Appear in the Proceedings of the 31th International Conference on Conference on Uncertainty in Artificial Intelligence (UAI-2015), July 2015.
• A Probabilistic Graphical Model-based Approach for Minimizing Energy Under Performance Constraints- Nikita Mishra, Huazhe Zhang, John D. Lafferty, Henry Hoffmann, in Proceedings of the 20th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS-2015), March 2015.
• Private Stochastic Multi-arm Bandits: From Theory to Practice- Nikita Mishra, Abhradeep Thakurta, in ICML 2014 Workshop on Learning, Security and Privacy.
• Unsupervised query segmentation using only query logs- Nikita Mishra, Rishiraj Saha Roy, Niloy Ganguly, Srivatsan Laxman, and Monojit Choudhury, in Proceedings of the Twentieth International World Wide Web Conference (WWW 2011), Companion Volume, Hyderabad, March 28-Apr 1, 2011.