Swapnil Gandhi

M.Tech (Research) · IISc · [email protected]

I am currently a Research Intern at Microsoft Research India, where I work with Bhargav Gulavani and Karthik Ramachandra on Scalar UDF Inlining in SQL Server.

In recent past, I was a master's student advised by Prof. Yogesh Simmhan at DREAMLab, Indian Institute of Science (IISc) . At IISc, my research focused on distributed system software which leverage specialized abstraction and optimizations to accelerate the convergence time of temporal graph algorithms.


[Google Scholar]


  • 1. An Interval-centric Model for Distributed Computing over Temporal Graphs
    Swapnil Gandhi and Yogesh Simmhan
    IEEE 36th International Conference on Data Engineering (ICDE) in Dalas, Texas 2020 (In Press)

    [Abstract]      PDF

    Algorithms for temporal property graphs may be time-dependent (TD), navigating the structure and time concurrently, or time-independent (TI), operating separately on different snapshots. Currently, there is no unified and scalable programming abstraction to design TI and TD algorithms over large temporal graphs. We propose an interval-centric computing model (ICM) for distributed and iterative processing of temporal graphs, where a vertex’s time-interval is a unit of data-parallel computation. It introduces a unique time-warp operator for temporal partitioning and grouping of messages that hides the complexity of designing temporal algorithms, while avoiding redundancy in user logic calls and messages sent. GRAPHITE is our implementation of ICM over Apache Giraph, and we use it to design 12 TI and TD algorithms from literature. We rigorously evaluate its performance for diverse real-world temporal graphs - as large as 131M vertices and 5.5B edges, and as long as 219 snapshots. Our comparison with 4 baseline platforms on a 10-node commodity cluster shows that ICM shares compute and messaging across intervals to out-perform them by up to 25x, and matches them even in worst-case scenarios. GRAPHITE also exhibits weak-scaling with near-perfect efficiency.


  • 1. Wave : A Substrate for Distributed Incremental Graph Processing on Commodity Clusters October 2019
    Swapnil Gandhi
    ACM Student Research Competition (SRC) at 27th Symposium on Operating Systems Principles (SOSP), Ontario, Canada
    Bronze Medal

  • 2. From "Think Like a Vertex" to "Think Like an Interval" January 2019
    Swapnil Gandhi and Yogesh Simmhan
    Young Researcher’s Symposium (YRS) at 6th ACM IKDD CoDS and 24th COMAD, Kolkata, India

  • 3. Distributed Querying over Compressed Property Graphs December 2018
    Swapnil Gandhi, Sayandip Sarkar, Abhilash Sharma, Yogesh Simmhan
    Student Research Symposium (SRS) at 24th IEEE International Conference on High Performance Computing, Data and Analytics (HiPC), Jaipur, India
    Best Poster Award


Indian Institute of Science

M.Tech (Research) · Department of Computational and Data Science

CGPA: 9.2/10.0
Courses taken : Topics in Database Systems, Scalable Systems for Data Science, Database Management Systems, Linear Algebra and Applications, Introduction to Scalable Systems, Research Methods

August 2017 - Jan 2020

Bharati Vidyapeeth

B.Tech in Computer Engineering

Graduated with Department Honors
Course-work Grade : First Class with Distinction (Highest Attainable Grade)

July 2010 - June 2014


  • Bronze Medal - ACM Student Research Competition (Graduate Category), SOSP 2019 October 2019

  • Won 12th IEEE International TCSC Scalable Computing (SCALE) Challenge, Larnaca, Cyprus May 2019

  • Won Best Poster Award - 10th EECS Research Students Symposium at Indian Institute of Science (IISc) Bangalore April 2019

  • Won Best Student Research Symposium (SRS) Poster Award - 24th IEEE HiPC, Jaipur, India Dec 2017

  • Department Honors (Class 2010 - 2014) - Bharati Vidyapeeth, India Jun 2014

  • Won TCS Popular Student Project Award - Bharati Vidyapeeth, India May 2014

  • Won Best Undergraduate Project Award in Software Research & Development (SWRD) Department - TRDDC, India April 2014