Optimization, Probability and Learning (OPAL) Lab


PhD Students


Jianyu Wang

Jianyu joined the PhD program at CMU in 2017. He received a Bachelor degree in Electronic Engineering at Tsinghua University, China. During his undergraduate program, he has spent three months in UC Berkeley as a visiting researcher and two years working with professor Yuan Shen. His research at CMU focuses on distributed machine learning.





Ankur Mallick

Ankur joined the PhD program at CMU in 2017. He received a B.Tech. in Electrical Engineering and a M.Tech. in Communications and Signal Processing, both in 2016, from the Indian Institute of Technology Bombay. Following this he spent a year at Sony Corporation, Japan, as an R&D engineer working on signal processing and machine learning algorithms for image sensors. His research interests are broadly in machine learning, distributed computing, and information theory. He has been awarded the Qualcomm Innovation Fellowship 2019 for his work on edge machine learning.



Samarth Gupta

Samarth (co-advised with Prof. Osman Yagan) joined the PhD program at CMU in 2017. Before that he received his BTech and MTech from Indian Institute of Technology Bombay. He is interested in working on online learning and statistical machine learning problems, with applications to recommendation systems, experiment design, dynamic pricing, data analytics and privacy-preserving learning. During summer 2019, he worked as an intern with the prediction team at Uber ATG to develop safety-oriented predictions for traffic actors around an autonomous vehicle.



Yae Jee Cho

Yae Jee joined the PhD program at CMU in 2019. She received both her M.S. and B.S. in Electrical & Computer Engineering at Yonsei University. Her research interests are in distributed machine learning and optimization theory, including federated learning.






Tuhinangshu Choudhury

Tuhinangshu (co-advised with Prof. Osman Yagan) joined the PhD program at CMU in 2019. He received his Bachelors and Masters degree in Electrical Engineering from Indian Institute of Technology Bombay. His interest lies in performance analysis of computer systems, statistical learning and random graphs.




Ting-Wu (Rudy)Chin

Rudy (co-advised with Prof. Diana Marculescu) joined the Ph.D. program at CMU in 2017. He received both a Bachelor's and a Master's degree in Computer Science at National Chiao Tung University, Taiwan. He is interested in making deep neural networks faster and less resource-consuming with applications in computer vision. More specifically, his research focuses on improving the training algorithms for resource-efficient deep nets (e.g., structurally-sparse networks), and on optimization methods that search for resource-efficient deep nets that train well.




Ahmet Inci

Ahmet (co-advised with Prof. Diana Marculescu) joined the PhD program at CMU in 2017. He received his B.Sc. degree in Electronics Engineering at Sabanci University, Turkey. He is interested in machine learning, computer architecture, and hardware-efficient deep learning to improve the accuracy of deep learning models and increase the energy efficiency of machine learning infrastructure. His current research focuses on designing hardware-efficient deep neural networks using DNN-HW co-design techniques and neural architecture search methods.




Masters Students


Chaitanya Dwivedi

Shreyas Chaudhari

Hao Liang

Dhruva Kaushal

Summer Interns


Divyansh Jhunjhunwala, 2019

Subhojyoti Ghosh, 2019

Chaitanya Dwivedi, 2019

Sanghamitra Dutta, 2017 (at IBM Research)

Alumni


Zhouyi Yang CMU ECE M.S. June 2020

Sai Bhargav Yalamanchi: CMU ECE M.S. Dec 2018 → Uber

Souptik Sen: CMU INI M.S. Jun 2018 → LinkedIn

Mani Swetha Mandava: CMU ECE M.S. Dec 2018 → NVIDIA

Malhar Chaudhari: CMU ECE M.S. Dec 2017 → Oracle