PhD @ Zuse Institute Berlin | ML Systems, Efficiency and Evaluations. | Former UdS MPI, CISPA, MIT Media Lab, AWS |
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MSc Visual Computing student at Universitat Des Saarlandes. My research focus in on building data and compute efficient computer vision systems. I work towards this goal through a combination of research in distributed deep learning, learning theory and representation learning. I did my B.Tech in ECE at SRMIST, Chennai and studied at MIT during the Fall 2018 semester.
Universität des Saarlandes
Master of Science - MS, Visual Computing
October 1, 2025 – Present
Massachusetts Institute of Technology
Undergraduate Special Student, Course 6 - Electrical Engineering and Computer Science
January 1, 2018 – January 1, 2018
SRM IST Chennai
Bachelor of Technology - BTech, Electronics and Communication Engineering
January 1, 2016 – January 1, 2020
Zuse Institute Berlin
Doctoral Researcher
November 1, 2025 – Present
Berlin, Germany · On-site
Amazon
Applied Scientist Intern
November 1, 2024 – May 1, 2025
Tübingen, Baden-Württemberg, Germany · On-site
Max Planck Institute for Informatics
Graduate Research Assistant
August 1, 2024 – October 1, 2024
Saarbrücken, Saarland, Germany · On-site
CISPA Helmholtz Center for Information Security
Graduate Research Assistant
August 1, 2023 – July 1, 2024
Saarbrücken, Saarland, Germany
CISPA Helmholtz Center for Information Security
Graduate Research Assistant
July 1, 2022 – July 1, 2023
Saarbrücken, Saarland, Germany
Rediscovery.io
Junior Deep Learning Research Scientist
July 1, 2020 – May 1, 2021
Myelin Foundry
Deep Learning Intern
March 1, 2020 – June 1, 2020
Bengaluru Area, India
RunwayML
Machine Learning Researcher (Consultant)
September 1, 2019 – January 1, 2020
Chennai Area, India
Intel Corporation
Deep Learning Consultant
August 1, 2019 – August 1, 2019
Bangalore
Myelin Foundry
Deep Learning Intern
June 1, 2019 – June 1, 2019
Bengaluru, Karnataka, India
MIT Media Lab
Undegraduate Researcher
September 1, 2018 – December 1, 2018
Greater Boston Area
Obama Sings
March 1, 2019 – March 1, 2019
An application which automatically downloads Karaoke files, subsequently using audio processing to download, slice and compile audio of a speakers speeches into a song, by also altering properties of the audio.
StoryBoxVR
September 1, 2018 – Present
Interactive Media based VR storytelling platform with AI generated prompts for an engaging gameplay environment for coordinated curiosity.
Psych.ai
December 1, 2017 – Present
Won the First Prize at Microsoft Garage Hacks GAINS AI Hackathon held at Microsoft's Hyderabad Campus. We built Psych.ai which leveraged the applications of Deep Learning in Computer Vision to build an application which can be integrated with Microsoft Stream, which allows the user to enhance the experience of viewing a video by allowing him/her to select an emotion to be enhanced and automatically enhancing those frames which reflect the emotion. Two other crucial applications: > Allowing for Visual cues of comedy, art for hearing impaired. > Diversification of content for people from different cultures.
DeepHPD - Deep Human Presence Detector
December 1, 2017 – Present
Won first prize at ImagingHub smart home competition. DeepHPD is an application which makes use of Deep Learning, Convolutional Neural Networks in specific deployed on a GPU server interfaced with a Raspberry Pi which takes input from a Basler Dart Camera. The project takes in an input feed via the camera and classifies over a sum of frames the class label for "Human" and "No Human" the confidence scores are then used to trigger a response via an external circuit which can be used for alerts/burglar alarms and for applications such as turning on appliances.
Deep Greetings
June 1, 2017 – September 1, 2017
In this project we attempt to develop a novel framework for generation of greeting cards using Deep Learning for the next major upcoming festival. Our current model includes festivals such as Diwali, Halloween, Valentines day, Independence day and Christmas. To this end, we use neural style transfer to generate the cover/background image of our greeting card and an LSTM model trained on text, poetry, stories related to the festival in order to generate text on the festival. We also use Augmented Reality to display a personalized greeting video of your choice on the card, all these features are combined to form the final greeting card.
Two Way Convolutional Neural Network
February 1, 2017 – March 1, 2017
Implementation of the research paper "Two-Stream Convolutional Networks for Action Recognition in Videos " https://arxiv.org/pdf/1406.2199.pdf using Keras and Scikit Learn.
Gypsy
January 1, 2017 – February 1, 2017
A program implemented in python which makes use of Identification trees and Microsoft Cognitive Services (MCS) Emotion Detection API which takes various factors such as age, gender, current state of mind and suggests travel locations near you in Chennai.
The Machine : Autonomous Video Surveillance System
January 1, 2017 – March 1, 2017
Submitted at Smart India Hackathon 2017 under the Ministry of Electronics and Information Technology Implemented a model for automating surveillance analysis consisting a deep learning model which would first detect anomalous events and then label them according to its training then would intimate the the relevant authorities.
Sequence Models
Coursera
June 24, 2026 – Present
Mathematics for Machine Learning Specialization
Coursera
June 24, 2026 – Present
Convolutional Neural Networks
Coursera
June 24, 2026 – Present
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
Coursera
June 24, 2026 – Present
Mathematics for Machine Learning: Multivariate Calculus
Coursera
June 24, 2026 – Present
Mathematics for Machine Learning: Linear Algebra
Coursera
June 24, 2026 – Present
Mathematics for Machine Learning: PCA
Coursera
June 24, 2026 – Present
Structuring Machine Learning Projects
Coursera
June 24, 2026 – Present
deeplearning.ai specialization
Coursera
June 24, 2026 – Present
Neural Networks and Deep Learning
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's diverse project portfolio, including award-winning hackathon entries and personal projects, demonstrates a strong passion for machine learning and AI. Their experience spans various sub-fields (CV, NLP, audio processing, generative models) and environments (academic research, industry internships, consulting), indicating adaptability and a broad interest in the field. The alignment with a target role of ML Engineer is very strong, given their specialized background and continuous engagement with advanced ML topics. The candidate's pursuit of a Master's and Doctoral research further underscores a commitment to deep technical understanding and continuous learning, which would be a good cultural fit for a research-intensive or innovation-driven organization.
Soft Skills & Operational Fit
The candidate's project descriptions and work history suggest a proactive, research-oriented individual capable of independent problem-solving and contributing to cutting-edge AI/ML initiatives. Their involvement in hackathons and diverse projects indicates a strong drive for innovation and practical application of theoretical knowledge. The numerous research assistant roles highlight a collaborative spirit within academic settings.