Trisha Mittal
Sr. Researcher at Dolby Laboratories
Sunnyvale, California, United States
Summary
👤
Senior🎓
Top SchoolTrisha Mittal is a senior researcher and computer vision specialist with a decade of experience bridging academic rigor and industry impact, currently driving research at Dolby Laboratories after roles as a senior CV research engineer and multiple research internships at Apple and Adobe. She completed a PhD in Computer Science at the University of Maryland following integrated M.Tech training at IIIT-B, and has worked on interdisciplinary problems spanning machine teaching, inverse reinforcement learning, multimedia systems, and human-centered sketch recognition. Her career blends deep research—evidenced by visiting fellowships at Max Planck—and practical ML deployment in product-focused labs, enabling rapid translation of novel algorithms into real-world applications. Based in Sunnyvale, she pairs strong formal training with hands-on experimentation, often tackling how humans and machines perceive and generate visual content. An approachable researcher, she maintains a public portfolio (trishamittal.github.io) that highlights both technical depth and creative problem framing.
10 years of coding experience
2 years of employment as a software developer
iMTech (Integrated M.Tech in Information Technology), iMTech (Integrated M.Tech in Information Technology) at International Institute of Information Technology BangaloreDoctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at University of MarylandApeejay School NOIDASardar Patel Vidyalaya, New Delhi
English, Hindi
Github Skills (11)
deep-reinforcement-learning10
q-learning10
paper9
computer-vision9
reinforcement-learning8
python6
image-processing6
deep-learning3
neon3
neural-network3
hardware3
Programming languages (3)
Github contributions (5)
BardOfCodes/DRL_in_CV
Aug 2017 - Nov 2017
A course on Deep Reinforcement Learning in Computer Vision. Visit Website:
Contributions:53 commits, 7 PRs, 49 pushes in 3 months
computer-visiondeep-reinforcement-learningreinforcementpolicy-gradientq-learning
TrishaMittal/KaggleMLChallenge
Aug 2017 - Apr 2024
To classify StumbleUpon content (webpages and media) as evergreen or ephemeral
Contributions:1 PR, 4 pushes, 1 branch in 6 years 8 months
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