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Welcome to the DS2 Research Lab

We are a research team of Data Science and Computer Science at the University of Virginia.

We research Data Systems for Data Science (DS2). Our aim is to explore and build better systems software to sustain the requirements of next-generation data-intensive applications.

We are interested in addressing challenges existing in real-world distributed and storage systems. Our research is driven by the complexities of modern data-intensive computer systems, and the need for more efficient and flexible approaches to manage such complexities. We aim for innovation in systems technologies that range from large-scale distributed systems to cross-layer software-hardware co-design.

Our current efforts are focused on: (1) LLM systems: making LLM applications elastic, scalable, and robust; (2) Serverless and FaaS: improving serverless computing using an end-to-end approach that cuts across the entire ecosystem stack, spanning applications, middleware, platforms, and low-level OS/HW; (3) Data reduction: rethinking data reduction techniques for large ML platforms like Hugging Face.

We are committed to training the next-gen of data systems researchers and developers. We are seeking Ph.D. students who are passionate about solving practical challenging problems in modern datacenter applications & systems. We are also open to working with Masters and undergrad students.

Lab Members Our Research

Lab News

January 2025

  • Congrats to Qichang on CIDRE accepted to ASPLOS 2025!
  • Congrats to Ruizhe on the IPFS data management work accepted to WWW 2025!

September 2024

  • Congrats to Redwan on FedCaSe on federated learning I/O caching and scheduling accepted to SoCC 2024!
  • 👋 A warm welcome to our newest members Zirui Wang and Tingfeng Lan! We're excited to have you both on board.
  • Thrilled to receive an NSF CSSI Elements grant on developing a sustainable and GPU-efficient cyberinfrastructure for Notebooks (w/ Co-PI Geoffrey Fox). Thanks, NSF!

July 2024

June 2024

  • Congrats to Yuqi and Ruizhe on ALPS accepted to USENIX ATC 2024! ALPS learns workload intelligence from the user space to inform serverless function scheduling in the kernel space.

May 2024

  • This summer Yuqi will be doing a student researcher internship at Google and Zhaoyuan will be doing a research internship at Samsung. Congrats!

April 2024

  • Excited to receive an NSF OAC Core grant on building a distributed graph learning cyberinfrastructure for large spatiotemporal prediction (w/ Liang Zhao from Emory). Thanks, NSF!

March 2024

  • Congrats to Ruizhe on the IPFS analysis work accepted to SIGMETRICS 2024! We answered questions about accessibility, content, and performance of IPFS in this research.
  • Congrats to Zhaoyuan, Ammar, and Zirui on their work accepted to VLDB 2024! In this work, Zhaoyuan analyzed a large dataset of real-world pre-trained ML models collected from Hugging Face. Based on the analysis study, he designed a new storage compression method for reducing the storage requirement of pre-trained models at scale.

February 2024

  • Congrats to Rui on his work accepted to VLDB 2024! In this work, Rui systematically studied the algorithmic complexity vulnerabilities of dynamic learned indexes.

January 2024

October 2023

  • 🏆 Excited to receive a Samsung GRO 2023 Award on New Storage for Large ML Training (w/ Ali Anwar from UMN). Thanks, Samsung Advanced Institute of Technology and Samsung Memory Solutions Lab, for the generous support on our research!
  • Serving as the general co-chair of ACM HotStorage'24. Consider submitting your exciting early ideas!

June 2023

  • 🎓 My first Ph.D. student Jingyuan Zhang successfully defended his Ph.D. dissertation. Congratulations, Dr. Zhang! Jingyuan will be joining the cloud-native infrastructure team @ ByteDance (San Jose, CA).

April 2023

  • Congrats to Ben, Runzhou, and Jingyuan on the acceptance of λFS to ASPLOS'23! The acceptance of λFS at ASPLOS'23 marks yet another significant milestone of our serverless storage project series. Don't forget to check out our projects: Episode I - InfiniCache, Episode II - InfiniStore, and our latest work, Episode III - λFS.

February 2023

  • Congrats to Jingyuan, Ben, and the team on the acceptance of InfiniStore to VLDB 2023!

December 2022

  • Congrats to Redwan, Ahmad, and Yuqi on their paper on deep learning I/O caching accepted to FAST 2023!

September 2022

August 2022

  • Our group moved to the University of Virginia in Fall'22.

July 2022

  • 🏅 SFS is nominated as a Best Student Paper Award Finalist at SC'22!! Congrats to Yuqi!

June 2022

  • Congrats to Yuqi on his paper on serverless function scheduling accepted to SC'22!

May 2022

  • This summer my students will intern at MSR (Ben Carver), ByteDance (Yuqi Fu, Jingyuan Zhang), and Argonne National Lab (Zhaoyuan Su)! Congrats!
  • Yue received an Outstanding Teacher Award from CS @ Mason!
  • Rui received an Outstanding GTA Award from CS @ Mason! Congratulations!

August 2021

August 2021

  • Congrats to Li and Haoliang on rKube accepted to SoCC'21!

June 2021

  • Congrats to Zheng on FedAT accepted to SC'21!

April 2021

  • Congrats to Ao on FaaSNet accepted to ATC'21!

March 2021

  • Yue received a gift from Adobe Research for our work on serverless computing! Thanks, Adobe!

Feburary 2021

  • Yue received an NSF CAREER Award for our work on building serverless cloud storage infrastructure. Thanks, NSF!

Research Talks