Yogesh Simmhan
Assistant Professor
Yogesh's Mugshot Department of Computational and Data Sciences (CDS)
Indian Institute of Science (IISc), Bangalore
simmhan@cds.iisc.ac.in | skype:simmhan | @dreamlabin
Work:+91 80 2293 3421 | Cell: +91 9790 750137
CDS 206 | Nilgiri Marg, Mathikere, Bangalore 560012 | Map
Yogesh Simmhan is an Assistant Professor at the Department of Computational and Data Sciences at the Indian Institute of Science, Bangalore. Previously, he was a Research Assistant Professor in the Electrical Engineering Department (Computer Engineering) at the University of Southern California, Los Angeles and Associate Director of the USC Center for Energy Informatics.
His research explores abstractions, algorithms and applications on distributed systems. These span Cloud and Edge Computing, Distributed Graph Processing Platforms and Elastic Stream Processing to support emerging "Big Data" and Internet of Things (IoT) applications. His research advances fundamental knowledge, and offers a practitioner's insight, on building scalable and resilient systems. He has won the IEEE/ACM Supercomputing HPC Storage Challenge Award in 2008 and IEEE TCSC SCALE Challenge Award in 2012. He is a Senior Member of IEEE and ACM, Associate Editor of IEEE Transactions on Cloud Computing and a member of the IEEE Future Directions Initiative on Big Data.
Yogesh has a Ph.D. in Computer Science from Indiana University and was earlier a Postdoc at Microsoft Research, San Francisco.


Google Scholar



University of Southern California

Indiana University

Microsoft Research

Indian Institute of Science


Recent updates


My research is on distributed and scalable data platforms to support Big Data and Internet of Things (IoT) applications on novel computing infrastructure, such as Clouds and Edge devices. I lead the DREAM:Lab - Distributed Research on Emerging Applications and Machines - at CDS. Details of various research activities of the lab is available at the lab webpage


A new course on Scalable Systems for Data Science is being offered in the Jan semester starting from 2016 at the CDS department. This is expected to be a 3:1 credit course from Jan 2017. The course covers platforms and tools required for developing algorithms, and programming and analyzing Big Data.

The SE252: Introduction to Cloud Computing (3:1) is occasionally offered as an elective course in the Aug semester. The course covers topics on parallel and distributed computing; IaaS/PaaS/SaaS Clouds; Big Data processing patterns on Clouds; Runtime execution models on Clouds; and Performance evaluation of Cloud applications. A programming project is an essential part of the course, with students provided on public and private Cloud computing resources.

I teach the DS286: Data Structures and Programming (2:1) core course in the Aug semester, sometimes with Prof. Venkatesh Babu.

I co-taught the SE292: High Performance Computing (3:0) core course in the Aug 2014 semester, along with Prof. Govindarajan


Recent Refereed Publications (2015 – )

ORCID: 0000-0003-4140-7774 | Google Scholar | DBLP

  1. Shantenu Jha, Daniel S. Katz Andre Luckow, Omer Rana and Yogesh Simmhan amd Neil Chue Hong, Introducing Distributed Dynamic Data-intensive (D3) Science: Understanding Applications and Infrastructure, Concurrency and Computation: Practice and Experience , 2016 [To Appear]
  2. Ravikant Dindokar, Neel Choudhury and Yogesh Simmhan, A Meta-graph Approach to Analyze Subgraph-centric Distributed Programming Models, IEEE International Conference on Big Data (Big Data) , 2016 [To Appear]
  3. Ravikant Dindokar and Yogesh Simmhan, Elastic Partition Placement for Non-stationary Graph Algorithms, IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing (CCGrid) , 2016 [Short Paper [Core A]]
  4. Nitin Jamadagni and Yogesh Simmhan, GoDB: From Batch Processing to Distributed Querying over Property Graphs, IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing (CCGrid) , 2016 [[Core A]]
  5. Anshu Shukla and Yogesh Simmhan, Benchmarking Distributed Stream Processing Platforms for IoT Applications, TPC Technology Conference on Performance Evaluation & Benchmarking (TPCTC) , 2016 [To Appear]
  6. Saima Aman, Yogesh Simmhan and Viktor Prasanna, Holistic Measures for Evaluating Prediction Models in Smart Grids, IEEE Transactions on Knowledge and Data Engineering (TKDE) , 27(2), 2015, pp. 475-488 [[IF 2.476, CORE A]]
  7. Alok Gautam Kumbhare, Yogesh Simmhan, Marc Frincu and Viktor K. Prasanna, Reactive Resource Provisioning Heuristics for Dynamic Dataflows on Cloud Infrastructure, IEEE Transactions on Cloud Computing (TCC) , 3(2), 2015, pp. 105-118
  8. Prasant Misra, Yogesh Simmhan and Jay Warrior, Towards a Practical Architecture for Internet of Things: An India-centric View, IEEE Internet of Things Newsletter , 2015, pp. 1-2
  9. Saima Aman, Marc Frincu, Charalampos Chelmis, Muhammad Noor, Yogesh Simmhan and Viktor K. Prasanna, Prediction Models for Dynamic Demand Response: Requirements, Challenges, and Insights, IEEE International Conference on Smart Grid Communications (SmartGridComm) , 2015, pp. 1-6
  10. Ravikant Dindokar, Neel Choudhury and Yogesh Simmhan, Analysis of Subgraph-centric Distributed Shortest Path Algorithm, International Workshop on Parallel and Distributed Computing for Large Scale Machine Learning and Big Data Analytics (ParLearning) , 2015, pp. 1185-1190
  11. Alok Kumbhare, Marc Frincu, Yogesh Simmhan and Viktor K. Prasanna, Fault-Tolerant and Elastic Streaming MapReduce with Decentralized Coordination, IEEE International Conference on Distributed Computing Systems (ICDCS) , 2015, pp. 328 - 338 [[Core A]]
  12. Anshu Shukla, Tarun Sharma and Yogesh Simmhan, Characterizing Distributed Stream Processing Systems for IoT Applications, Workshop on Architectural Support and Middleware for InfoSymbiotics/ Dynamic Data Driven Applications Systems (DDDAS), co-located with High Performance Computing Conference (HiPC) , 2015, pp. 1-1 [Extended abstract]
  13. Yogesh Simmhan, Neel Choudhury, Charith Wickramaarachchi, Alok Kumbhare, Marc Frincu, Cauligi Raghavendra and Viktor Prasanna, Distributed Programming over Time-series Graphs, IEEE International Parallel & Distributed Processing Symposium (IPDPS) , 2015, pp. 809 - 818 [[Core A]]
  14. Yogesh Simmhan, Anshu Shukla and Arun Verma, Benchmarking Fast Data Platforms for the Aadhaar Biometric Database, Workshop on Big Data Benchmarking (WBDB) (arxiv:1510.04160), 2015, pp. 1-9, CoRR.

All Publications

Students and Staff

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Staff and Interns

IISc Alumni

Former Staff and Students at IISc

Former Students at USC

Prospective Students & Projects

Applied systems research requires hands-on programming skills to validate research ideas. Students interested in working with my lab should have demonstrated experience with programming and algorithms, preferably in Java, through online coding contest and Hackathons, such as CodeChef, SPOJ, HackerEarth, etc. Knowledge of Big Data platforms like Hadoop/Spark/Storm, Cloud fabrics like OpenStack and experience with Open Source projects will help too.

I welcome Ph.D. and M.Sc. research students at CDS interested in working with me. You are encouraged to view the lab's research activities, review relevant literature and our recent papers, and contact me with specific research areas and problems that you are passionate about.

Projects on state-of-the-art topics on Big Data and Cloud+Edge systems are available for M.Tech. by coursework students. These projects will place an emphasis on innovative research ideas as well as practical grounding through software prototyping and benchmarking on Cloud and distributed clusters. Students will be expected to publish a research paper as a project outcome. Sample projects topics are available from our lab's webpage. If you are interested, send me an email to schedule a meeting by Dec/Jan. Students must take the SE252:Introduction to Cloud Computing Course or SE256:Scalable Systems for Data Science Course as a pre-requisite.

Limited undergraduate summer internships are available to highly motivated students interested in pursuing research as part of their final year project. Students must be able to spend a semester in addition to summer (9-12 months) at IISc. Applications are open on a rolling basis starting the December before the internship term (e.g. Dec 2014 for May-Dec 2015).

Research associate and project staff positions are available in the area of Cloud Computing, Big Data platforms and Internet of Things. The position is for a minimum of 1 year, and offers a chance to work on research projects, collaborate with students, and publish research papers. Applicants should have a Masters' or Ph.D. degree in Computer Science; in exceptional cases, those with just a B.E. or B.Tech. degree in Computer Science will be considered. Demonstrated programming experience, through work on large open source projects, coding challenges (Googe SOCC, CodeChef) or hackathons, is required.

Students interested in applying to IISc should review the admission guidelines for IISc and CDS. IISc offers a world-class research environment, is consistently ranked the best research university in India, by Times Higher Education, ARWU and QS World University Rankings. CDS offers a unique 2-year M.Tech.(Computational and Data Science) program by coursework and project, in addition to research degrees of M.Tech.(Research) and Ph.D. Research students interested in working with me should select the Computer Systems Stream (CDS-CS) and prepare for the interview topics for the DREAM:Lab, as listed in the research admissions brochure. The admission process is highly competitive and requires a GATE exam score for those with a Bachelors' degree, besides onsite interviews.

Recent Professional Service

  • Associate Editor, IEEE Transactions on Cloud Computing (2013-Present)
  • Editorial Board Member, Services Transactions on Internet of Things (STIOT) (2016-Present)
  • Guest Co-Editor Journal of Parallel and Distributed Computing (JPDC) - Special Issue on Scalable Systems for Big Data Management and Analytics (2013-14)
  • Guest Editor Concurrency and Computation: Practice and Experience Journal (CPE) - Special Issue on Cloud Computing for Data-driven Science and Engineering (2012-2015)
Conferences & Workshops
  • Academic-Research Liaison Co-Chair, IEEE International Parallel and Distributed Processing Symposium (IPDPS) (2015-2016)
  • SCALE Challenge Co-Chair, IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid) (2015)
  • Academic Liaison Co-Chair, IEEE International Conference on High Performance Computing (HiPC) (2014-2016)
  • General Co-Chair, Indian Symposium on Computer Systems (IndoSys) (2014-2016)
  • Workshop Vice-Chair IEEE International Parallel and Distributed Processing Symposium (IPDPS) (2014)
  • Workshop Co-Chair IEEE International Conference on High Performance Computing (HiPC) (2013)
  • General Co-Chair Workshop on Scientific Cloud Computing (ScienceCloud), Co-located with HPDC (2012-2013)
  • Doctoral Symposium Co-Chair IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid) (2012-2013)
  • Program Committee Member in various years for IEEE International Parallel and Distributed Processing Symposium (IPDPS), IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), International Conference on Supercomputing, IEEE International Conference on Big Data (BigData), IEEE International Conference on eScience (eScience), IEEE International Conference on Web Services (ICWS), IEEE High Performance Computing Conference (HiPC), ACM Symposium on Applied Computing (SAC), IEEE Cloud Computing for Emerging Markets (CCEM), and ACM India Compute Conference (Compute) among others.
  • Member, IEEE Future Directions Initiative on Big Data (2015-)
  • Chair, Education & Research Task Force, Cloud Computing Innovation Council of India (CCICI) (2014-2015)
  • Invited Expert W3C Provenance Working Group (2011 - 2013)
  • Serving/Served on grant review panels for India's DeitY, US NSF, Austrian FWF and Brazilian FAPESP

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