About

I am an Inria research scientist within the STACK team. Before joining Inria, I was a staff scientist in the SCI Institute at the University of Utah. I also worked as a Research Associate at the Rutgers Discovery Informatics Institute led by Manish Parashar, where I investigated programming support and resource management for data-driven analytics and edge computing applications (2017-2021). I received a Ph.D. degree from the Ecole Normale Superieure de Lyon in France (2016) under the supervision of Eddy Caron and Laurent Lefevre as part of the Inria Avalon Team. My PhD research focused on implementing tradeoff mechanisms between performance and energy consumption for large scale cloud applications. I've extented this work as a visiting fellow at Mahindra Ecole Centrale in Hyderabad, India (2015). Before that, I worked as a Junior Engineer at Inria, the French Institute for Research in Computer Science (2011-2013) and interned at the National Institute of Informatics in Tokyo, Japan (2009-2010).

Open positions

Postdoc positions available. Please contact me for further information.

Research Interests

My research interests are broadly in the areas of distributed computing. My current research is focused on the control and advanced use of Edge computing systems in regard to the content of the data, the cost of computations, and the urgency of the results. Cyberinfrastructures, AI/ML applications, and data-centric/middleware systems are some of the applications of this research.

Recent Highlights

[Scientific Animation]

• Workshop chair of QuickPar 2023 - The 1st Workshop on Urgent Analytics for Distributed Computing co-conducted with Euro-Par2023 (Aug 28-29, Limassol, Cyprus)
• Publicity chair for ICPP23 (Aug7-10, Salt Lake City, Utah).

[Programme Committees] PC member for Euro-Par 2023, IEEE/ACM SuperComputing 2023 Reproducibility challenge, ICCS 2023.
[Service] 2022: Panelist for NSF CSSI Elements.
[Tutorial] Oct 2022: Tutorial on streaming application development on the Edge-to-Cloud Continuum in collaboration with WiFire (UC San Diego) @eScience2022.
[Funding] Sept 2022: I received an NSF grant for managing urgent analytics on advanced cyberinfrastructure.
[Programme Committees] 2022: I am serving as a PC member for IEEE/ACM CCGrid 2022 (Artificial intelligence, Machine Learning and Deep Learning Track), IEEE/ACM SuperComputing 2022 Reproducibility challenge and ICCS 2022.
[PhD Defense] 2021: My first PhD student, Zeina Houmani, has successfully defending her thesis: Data-driven microservices architectures.
[Impact] 2021: Our joint work with Inria on Earthquake Early Warning was cited by Le Monde.
[Award] 2020: Outstanding paper award in Artificial Intelligence for Social Impact, 34th AAAI Conference on Artificial Intelligence (AAAI-20, A* rank)

Current Projects

     

Past projects on my former page.

About

I am an Inria research scientist within the STACK team. Before joining Inria, I was a staff scientist in the SCI Institute at the University of Utah. I also worked as a Research Associate at the Rutgers Discovery Informatics Institute led by Manish Parashar, where I investigated programming support and resource management for data-driven analytics and edge computing applications (2017-2021). I received a Ph.D. degree from the Ecole Normale Superieure de Lyon in France (2016) under the supervision of Eddy Caron and Laurent Lefevre as part of the Inria Avalon Team. My PhD research focused on implementing tradeoff mechanisms between performance and energy consumption for large scale cloud applications. I've extented this work as a visiting fellow at Mahindra Ecole Centrale in Hyderabad, India (2015). Before that, I worked as a Junior Engineer at Inria, the French Institute for Research in Computer Science (2011-2013) and interned at the National Institute of Informatics in Tokyo, Japan (2009-2010).

Supervision

[2023 - ] Sangshin Park. PhD candidate.
Subject: Intelligent services across the Computing Continuum.

[2018 - 2021] Zeina Houmani. PhD candidate in joint supervision with ENS Lyon, France.
Subject: A Data-driven microservices architecture for Deep Learning applications.

Teaching

Programming for Engineers | Graduate course (School of Computing, Univ. of Utah, 2022)
Principles of Data and Information Management (Rutgers University, 2019)
Introduction to Computer Science (Rutgers University, 2018|2019)
Parallel Systems | Graduate course (Lyon 1, France, 2016)
Operating Systems | Undergraduate course (Lyon 1, France, 2014, 2015)
Software Engineering | Graduate course (Lyon 1, France, 2014, 2015)
Databases | Undegraduate course (Lyon 1, France, 2014, 2015)
Project Management and Software Engineering | Graduate course (Lyon 1, France, 2014|2015|2016)
Network and OS Programming | Applied graduate course (IUT Lyon1, France, 2016)
Initiation to Windows | Applied graduate course (IUT Lyon1, France, 2015)