Tonmoy Saikia
Senior Machine Learning Engineer at Nomitri
Berlin, Germany
Summary
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Senior🎓
Top SchoolTonmoy Saikia is a Senior Machine Learning Engineer based in Berlin with 12 years of experience specializing in robust computer vision systems, particularly stereo depth estimation, object detection and few-shot learning. He holds a PhD in Computer Vision from the University of Freiburg and has transitioned research innovations into production at companies like Algolux, Torc Robotics and now Nomitri. His work spans academic contributions—documented in publications and a Google Scholar profile—and practical open-source impact, such as implementing a GaussianCompactKernel in the well-known Shogun toolbox to make its core more extensible. Tonmoy combines expertise in synthetic-data-driven perception, neural architecture search for efficiency, and methods to improve robustness under corruption or scarce data, often exploring unconventional data-generation PoCs like video diffusion and ControlNet. Colleagues benefit from his mix of rigorous research training and hands-on ML engineering that bridges prototype to deployment.
11 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy - PhD Computer vision, Doctor of Philosophy - PhD Computer vision at The University of FreiburgB.Tech Computer Science, B.Tech Computer Science at National Institute of Technology Silchar
Github Skills (6)
machine-learning10
c-language10
cprogramming-language10
artificial-intelligence9
cmake9
swig7
Programming languages (5)
Github contributions (5)
shogun-toolbox/shogun
Mar 2016 - Mar 2016
Shōgun
Role in this project:
ML Engineer
ML EngineerContributions:7 commits, 1 PR, 11 comments in 3 days
Contributions summary:Tonmoy primarily contributed to the implementation of a `GaussianCompactKernel` within the Shogun machine learning toolbox. Their work involved adding source files, defining the class structure, implementing compute functionality, and integrating the kernel into the existing framework. The user also updated documentation and interface files to accommodate this new kernel, making the core framework more extensible. Further commits optimized computations and improved code formatting.
cmakedata-sciencegunc-plus-plusmachine-learning
lmb-freiburg/netdef_models
Aug 2018 - Nov 2018
Contributions:29 commits, 27 pushes, 1 branch in 3 months
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