Akash Dhasade
PhD student at the EPFL, Switzerland
I am a PhD student at the Scalable Computing Systems (SaCS) Lab at EPFL advised by Prof. Anne-Marie Kermarrec. I completed my bachelors in Computer Science & Engineering at the Indian Institute of Technology Tirupati.
My research is focused on improving algorithmic efficieny, privacy and systems cost of distributed and decentralized machine learning.
Experience
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Associate Software Engineer, iManage, Bangalore, India (Aug 2019 - Dec 2020)
As a software engineer at iManage, I had the wonderful opportunity to work with and be mentored by Balamurugan Seenivasan and Manoj David. A signficant one of my projects involved systematic migration of the on-premise server’s codebase from python2 to python3 as python2 reached end of it’s life in January 2020.
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Research Intern, Very Large Scale Computing Lab, EPFL, Switzerland (May 2019 - Jul 2019)
I have interned at Very Large Scale Computing Lab, EPFL Switzerland where I was mentored by Stuart Byma and Prof. James Larus. I worked on the optimization of cluster-merge, a scalable and precise clustering algorithm to recover significantly similar pairs among a set of elements.
Our paper titled Parallel and scalable precise clustering for protein matching was accepted in PACT’20.
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Research Intern, TCS Innovation Labs, Chennai, India (May 2018 - July 2018)
During my internship at TCS, I was mentored by Dr. Mohan Raj VK. Our comprehensive survey on forest fire mitigation techniques was published in the Elsevier journal of Applied Geography.
Awards
I was awarded the President’s gold medal for the best academic performance across all branches at IIT Tirupati for my CGPA of 9.75/10.0. I was also awarded the Institute gold medal for standing first in the Department of Computer Science & Engineering over all four years.
Please find a short clip of the award here.
Some of my notable undergraduate projects
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Attendance System using face recognition
In my Btech thesis, I worked on the practical implementation of face recognition for classroom attendance where we tried to bridge the gap between years of face recognition research and its utility in real world applications.
We designed an end to end framework with several optimizations for streamlined and accurate performance. The system is operational in three classrooms at IIT Tirupati.
Find the video demo here.