I am an Assistant Professor in the Computer Science and Engineering Department at the University of Minnesota. My research covers a range of topics, including distributed systems, machine learning systems, serverless and cloud computing, storage systems, operating systems, high-performance computing, and quantum computing. My current research focuses on designing scalable, high-performance, and easy-to-use computer systems that manage and process a huge volume of data.

Currently, I am working on (1) Systems for ML, enhancing computing and storage systems to support distributed ML more effectively; (2) Federated Learning: addressing the challenge of heterogeneity across the stack to optimize Federated Learning systems; (3) Serverless and FaaS: innovating serverless computing with an integrated approach encompassing the entire software-hardware spectrum; (4) Quantum Computing: developing robust communication systems for quantum computing; (5) Enhancing AI Safety: crafting distributed modeling architectures to bolster the safety and reliability of ML systems.

My work has received recognition with four Best Paper awards. I have also received multiple awards from IBM, and I am a co-inventor on more than 15 US patents. Additionally, I have received the Samsung GRO award and the Pratt Fellowship award. Before joining UMN, I worked at IBM Research Almaden as a Research Staff Member in the AI Platforms team. I received my Ph.D. degree in Computer Science from Virginia Tech, working with Dr. Ali R. Butt. During my Ph.D. I spent three summers at IBM Research. In my earlier years, I gained invaluable experience working as a tools developer on several open-source projects (GNU GDB, Embedded Linux, U-Boot, and BusyBox).

Recent Papers and Awards

• A new preprint focusing on LLM finetuning is now available on arXiv!
• Paper accepted in VLDB’24 on Storage Compressibility of Pre-Trained ML Models. Congratulations to Zhaoyuan, Ammar, and the team!
• Paper accepted in MSST’24 on Balancing Costs and Durability for Serverless Data. Congratulations to Alex, Xinran, and the team!
• Two new preprints focusing on LLM caching and storage are now available on arXiv!
• Paper accepted in EuroSys’24. Congratulations to Ahmad, Azal, Sam, and the team!
• Paper accepted in Transactions on Storage. Congratulations to Nannan and the team!
• 🏆 Excited to receive a Samsung GRO 2023 Award on New Storage for Large ML Training (w/ Yue Cheng from UVA). Thanks, Samsung Advanced Institute of Technology, for the generous support on our research!
• Paper accepted in IEEE BigData’23. Congratulations to Ahmad and Xinran!
• 🏆 Best paper award from ACM SYSTOR’23 for our work on serving files efficiently in serverless computing.
• Paper Proposal accepted in I2Q (ISCA’23). Congratulations to Xinran and Connor!
• Extended Abstract accepted in QCCC (HPDC’23). Congratulations to Xinran and Connor!
• Paper accepted in Systor’23. Congratulations to Alex and the team!
• Paper accepted in VLDB’23. Congratulations to Jingyuan, Ben, and the team!
• 2x papers accepted in CCGrid’23. Congratulations to Sixing and Syed!
• Paper accepted in ICSE’23. Congratulations to Waris!
• Paper accepted in ASILOMAR’22. Congratulation to Qi!
• Paper accepted in IEEE BigData’22. Congratulations to Jingoo!
• Paper accepted in SC’22. Congratulations to Sixing and Phuong!
• 🏆 Best paper award from IEEE Cloud’22 for our work on privacy-preserving Federated Learning.
• 2x papers accepted in IEEE Cloud’22. Congratulations to Jingoo and Ahmad!
• Paper accepted in USENIX FAST’21. Congratulations to Alex!
• Paper accepted in SC’21. Congratulations to Zheng!
• Paper accepted in AAAI’21. Congratulations to Syed!
• Paper accepted in IEEE Cloud’21. Congratulations to Kamala!
• 🏆 Best paper award from ePart’21 for our work on accountable Federated Learning.
• 2x papers accepted in TPDS. Congratulations to Nannan and Ali!
• Paper accepted in USENIX ATC’20. Congratulations to Nannan!
• Paper accepted in USENIX FAST’20. Congratulations to Ao!
• Paper accepted in SoCC’20. Congratulations to Benjamin!
• Paper accepted in HPDC’20. Congratulations to Zheng, Syed, and Ahsan!
• Paper accepted in HotStorage’20. Congratulations to Alex!

Recent External Services

• 2024 PC: FAST’24, ICDCS’24, IEEE BigData’24, ATC’24.
• 2024: Serving on NSF Proposal Review Panels.
• 2024: Publicity Co-Chair for HPDC’24.
• 2024: Serving as General Co-Chair for IEEE Special Technical Community on Operating Systems (STCOS).
• 2023: Serving as Department of Energy Proposal Reviewer.
• 2023 PC: HPDC’23, Cluster’23, IPDPS’23, IEEE BigData’23, FedVision’23, FL-ICML’23, DistributedML’23.
• 2023: Serving on NSF Proposal Review Panel.
• 2023: Serving as General Co-Chair for HotStorage’23.
• 2023: Serving as General Co-Chair for IEEE Special Technical Community on Operating Systems (STCOS).
• 2023: Serving as Grants Co-Chair for HPDC’23.
• 2022 PC: ICDCS’22, HPDC’22, FL-NeurIPS’22, FedVision’22, IEEE BigData’22, FL-AAAI’22.
• 2022: Serving as General Co-Chair for HotStorage’22.
• 2022: Serving as publicity Co-Chair for HPDC’22.