Shivaram Venkataraman

Assistant Professor, Computer Science, University of Wisconsin-Madison

Office: 7367 CS. Email: shivaram at

I am an Assistant Professor in the Computer Science Department at University of Wisconsin, Madison. My research interests are in designing systems and algorithms for large scale data analysis and machine learning. My dissertation research looked at abstractions that make it easier to express new machine learning algorithms and systems that can improve their performance.

Before coming to Madison, I was a post-doctoral researcher in the Systems Research Group at Microsoft Research in Redmond. Previously, I completed my PhD from UC Berkeley where I was advised by Ion Stoica and Mike Franklin. I also have a Masters from University of Illinois at Urbana-Champaign and worked in the Systems Research Group, with Prof. Roy Campbell.


CS 537 Intro to OS: Spring 2020 Spring 2019

CS 744 Big Data Systems: Fall 2020 Fall 2019 Fall 2018


  • Pengfei Zheng (Post-doc, co-advised with Aditya Akella)
  • Saurabh Agarwal (Phd Student, co-advised with Dimitris Papailiopoulos)
  • Jason Mohoney (Phd Student, co-advised with Theodoros Rekatsinas)
  • Konstantinos Kanellis (Phd Student)
  • Yuhan Liu (Undergraduate researcher)
  • Rui Pan (Undergraduate researcher)
  • Lynn Liu (Undergraduate researcher)
  • Prasoon Sinha (Undergraduate researcher)

Recent Publications


Jason Mohoney, Roger Waleffe, Yiheng Xu, Theodoros Rekatsinas, Shivaram Venkataraman Marius: Learning Massive Graph Embeddings on a Single Machine - OSDI 2021

Saurabh Agarwal, Hongyi Wang, Kangwook Lee, Shivaram Venkataraman, Dimitris Papailiopoulos Accordion: Adaptive Gradient Communication via Critical Learning Regime Identification - MLSys 2021

Le Xu, Shivaram Venkataraman, Indranil Gupta, Luo Mai and Rahul Potharaju Move Fast and Meet Deadlines: Fine-grained Real-time Stream Processing with Cameo - NSDI 2021

Yuhan Liu, Saurabh Agarwal, Shivaram Venkataraman AutoFreeze: Automatically Freezing Model Blocks to Accelerate Fine-tuning - arXiv preprint code


Vaishaal Shankar, Karl Krauth, Kailas Vodrahalli, Qifan Pu, Ion Stoica, Benjamin Recht, Jonathan Ragan-Kelley, Eric Jonas, Shivaram Venkataraman Serverless Linear Algebra - SoCC 2020

Konstantinos Kanellis, Ramnatthan Alagappan, Shivaram Venkataraman. Too Many Knobs to Tune? Towards Faster Database Tuning by Pre-selecting Important Knobs - HotStorage 2020

Kshiteej Mahajan, Arjun Balasubramanian, Arjun Singhvi, Shivaram Venkataraman, and Aditya Akella, Amar Phanishayee, Shuchi Chawla. Themis: Fair and Efficient GPU Cluster Scheduling - NSDI 2020

Guanhua Wang, Shivaram Venkataraman, Amar Phanishayee, Nikhil Devanur, Jorgen Thelin, Ion Stoica Blink: Fast and Generic Collectives for Distributed ML - MLSys 2020


Jack Kosaian, K.V. Rashmi, Shivaram Venkataraman Parity Models: Erasure-Coded Resilience for Prediction Serving Systems - SOSP 2019

Myeongjae Jeon, Shivaram Venkataraman, Amar Phanishayee, Junjie Qian, Wencong Xiao, Fan Yang Analysis of Large-Scale Multi-Tenant GPU Clusters for DNN Training Workloads - USENIX ATC 2019

John Emmons, Sadjad Fouladi, Ganesh Ananthanarayanan, Shivaram Venkataraman, Silvio Savarese, Keith Winstein Cracking open the DNN black-box: Video Analytics with DNNs across the Camera-Cloud Boundary - Hot Topics in Video Analytics and Intelligent Edges (HotEdgeVideo 2019)

Qifan Pu, Shivaram Venkataraman, Ion Stoica Shuffling, Fast and Slow: Scalable Analytics on Serverless Infrastructure - NSDI 2019


Anand Padmanabha Iyer, Zaoxing Liu and Xin Jin, Shivaram Venkataraman, Vladimir Braverman, Ion Stoica ASAP: Fast, Approximate Pattern Mining at Scale - OSDI 2018

Kevin Hsieh, Ganesh Ananthanarayanan, Peter Bodik, Shivaram Venkataraman, Paramvir Bahl, and Matthai Philipose, Phillip B. Gibbons, Onur Mutlu Focus: Querying Large Video Datasets with Low Latency and Low Cost - OSDI 2018

Luo Mai, Kai Zeng, Rahul Potharaju, Le Xu, Steve Suh, Shivaram Venkataraman, Paolo Costa, Terry Kim, Saravanam Muthukrishnan, Vamsi Kuppa, Sudheer Dhulipalla, Sriram Rao Chi: A Scalable and Programmable Control Plane for Distributed Stream Processing Systems - VLDB 2018


Shivaram Venkataraman System Design for Large Scale Machine Learning - PhD Dissertation

Shivaram Venkataraman, Aurojit Panda, Kay Ousterhout, Michael Armbrust, Ali Ghodsi, Michael J. Franklin, Benjamin Recht, Ion Stoica Drizzle: Fast and Adaptable Stream Processing at Scale - SOSP 2017

Eric Jonas, Qifan Pu, Shivaram Venkataraman, Ion Stoica, Benjamin Recht Occupy the Cloud: Distributed Computing for the 99% - SoCC 2017 - arxiv version

Stephen Tu, Shivaram Venkataraman, Ashia C. Wilson, Alex Gittens, Michael I. Jordan, Benjamin Recht Breaking Locality Accelerates Block Gauss-Seidel - ICML 2017 arxiv version

Evan R. Sparks, Shivaram Venkataraman, Tomer Kaftan, Michael J. Franklin, Benjamin Recht KeystoneML: Optimizing Pipelines for Large-Scale Advanced Analytics - ICDE 2017 arxiv version

Omid Alipourfard, Jianshu Chen, Hongqiang Liu, Shivaram Venkataraman, Minlan Yu, Ming Zhang Cherry Pick: Adaptively Unearthing the Best Cloud Configurations for Big Data Analytics - NSDI 2017

Please see here for a complete list.