a Professor in the
Computer Science and Engineering
at the University of Minnesota, Twin
interests are in the areas of Operating Systems and Distributed Systems.
I co-lead the
Distributed Computing Systems Group in the department.
My research focuses on resource management and performance in distributed systems, such as Clouds, Data centers, Edge computing, and Mobile platforms, with the goal of achieving higher reliability, scalability, and manageability. Much of my focus in recent years has been on designing and optimizing systems for data-driven computing in the cloud and at the edge, especially for data generated at the edge of the network (near the users). This focus has involved research in geo-distributed data analytics, social analytics, and mobile and IoT data analytics.
Currently, I am working on a number of projects related to these areas, investigating issues in
data-intensive computing, edge computing, mobile and IoT systems, and social computing.
I am currently serving as the General Co-chair for
ACM HPDC 2022 and Steering Committee Co-Chair for IEEE IC2E. Please consider submitting and participating in these conferences.
In recent past, I have served as the Program Co-chair for IEEE ICDCS 2021, IEEE IC2E 2018 and ACM HPDC 2018 conferences. I was also the TPC Vice chair for the Edge Computing Track for IEEE ICDCS 2020 and IEEE ICDCS 2018.
Office: Rm 4-209, Keller Hall
Ph: (612) 626-1283
Fax: (612) 625-0572
Email: chandra AT umn DOT edu
Note: Email is the best way to contact me as I check it frequently. Mailing Address:
Department of Computer Science and Engineering
University of Minnesota
4-192 Keller Hall,
200 Union St. SE
Minneapolis, MN 55455
Our paper on Geo-distributed Join Approximation accepted to ACM SOCC'23.
Our SQuBA paper with PhD student Yixuan Wang as the first author won the at IEEE Edge 2023. Congrats Yixuan!
Best Student Paper Award
Our AggFirstJoin paper won the at CCGrid 2023.
Best Paper Award
We received a to investigate the scalability of edge computing systems. Thanks, Cisco!
new research grant from Cisco
Our paper on Efficient Edge Sampling presented at IC2E'22.
Our paper on Elasticity in Heterogeneous Edge-dense Environments presented at ICDCS'22.
Prof. Chandra serves as held in Minneapolis.
General Co-Chair for ACM HPDC 2022 conference
Our Network Cost-aware GDA paper published in IEEE TPDS journal.
Our paper on Heterogeneity-Aware Federated Learning presented at IPDPS'22.
Our paper on Distributed Join Sampling presented at EdgeSys'22.
PhD student . Congrats, Dhruv!!
Dhruv Kumar passes his PhD thesis defense
Our Aggnet paper presented at ACM/IEEE SEC'21.
Prof. Chandra serves as .
Program Co-Chair for IEEE ICDCS 2021 conference
Our DLion paper presented at ACM HPDC'21.
Our paper on Accelerated Federated Learning appears at EdgeSys'21.
Our WASP paper appears at Middleware'20.
Our poster on Data-Aware Edge Sampling wins the at SEC'20.
Best Poster Award
Our Vision paper on Edge-native storage appears in SEC'20.
Prof. Chandra chairs the panel on Data Science Project Management at the VAIBHAV Summit: A global summit for Overseas and Resident Indian Scientists and Academicians.
Our paper on
Network Cost-aware Geo-distributed Data Analytics System appears at CCGrid'20.
Our paper on Wiera geo-distributed storage system published in IEEE TPDS.
We received a for a project on building an edge-based IoT framework. Thanks, NSF!
new NSF grant
PhD students . Congrats, Kwangsung and Albert!
Kwangsung Oh and Albert Jonathan pass their PhD thesis defense
Our papers on DLion, DeCaf and Constellation systems presented at HotCloud and HotEdge workshops.
Our paper on MESH Hypergraph processing system nominated as a in IC2E'19.
Best Paper Finalist
Our paper on TTL-based streaming analytics presented at SIGMETRICS'19.
Our paper on multi-query optimization in wide-area stream processing presented at SOCC'18.
Our posters on deep learning and streaming analytics in geo-distributed environments presented at SOCC'18 and OSDI'18 respectively.
Our paper on adaptability in wide-area stream processing presented at HotCloud'18.
Source code for TensorFlow-based decentralized distributed deep learning framework released.
Recent alum (Ph.D. 2016) was honored as a runner-up for Benjamin Heintz . Congrats, Ben!
SPEC’s 2017 Kaivalya Dixit Distinguished Dissertation Award