Param Hanji

Lead Research Scientist - Generative Vision

Cambridge, England, United Kingdom
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Summary

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Senior
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Top School
Param Hanji is a Lead Research Scientist specializing in generative vision with 11 years of experience bridging computer vision, optimisation, and probabilistic machine learning. He has moved fluidly between academia and industry—earning a PhD from Cambridge and holding research roles at the University of Cambridge, Apple (camera algorithms), and now Cartwheel—bringing both theoretical depth and product-focused rigor. His work spans implementing state-of-the-art learning-based models and diving into the theory of probabilistic generative models, aiming to improve both sample quality and principled uncertainty. Comfortable shipping research into production environments, he has a track record of short, impactful stints across top labs and tech companies that accelerate applied research. Based in Cambridge, UK, he keeps an active personal webpage for more frequent updates, signaling a preference for rapid iteration and open scientific communication. Colleagues describe him as an early-stage researcher who pairs mathematical curiosity with practical engineering to push generative vision forward.
code11 years of coding experience
job6 years of employment as a software developer
bookDoctor of Philosophy - PhD, Doctor of Philosophy - PhD at University of Cambridge
bookBachelor’s Degree, Bachelor’s Degree at National Institute of Technology Karnataka
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Stackoverflow

Stats
1reputation
277reached
0answers
2questions
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Github Skills (39)

visible10
predictor10
rewriting9
simulator9
field-of-view9
python8
relational-algebra8
gpu8
query-language8
logic-programming7
machine-learning7
knowledge-representation7
deep-learning7
depth6
optical-flow6

Programming languages (5)

C++CLuaPythonCuda

Github contributions (5)

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gfxdisp/HDRutils

Feb 2021 - Sep 2022

Contributions:14 releases, 79 commits, 1 PR in 1 year 6 months
catchchaos/Parallel-PNG

Apr 2016 - Nov 2016

Contributions:4 PRs, 10 pushes, 2 branches in 6 months
cudaeratosthenes-algorithmgpusieveparallelize
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