Samyakh Tukra
Chief AI Officer & Co-Founder at Applied Computing
London, England, United Kingdom
Summary
👤
Senior🎓
Top SchoolSamyakh Tukra is a Chief AI Officer and co-founder with 8 years of cross-industry experience building production-grade AI systems that bridge cutting-edge research and real-world operations. He holds a PhD in AI & 3D computer vision from Imperial College London and has led teams to deploy multi-agent, physics-grounded AI (Orbital) that runs live refinery operations with 15-second natural-language inference. His background spans applied research at Shell and Tractable—publishing novel masked image modeling work accepted at CVPR—and founding a healthcare AI startup that predicted organ failure up to 48 hours ahead and partnered with multiple NHS trusts. Samyakh combines MLOps and edge deployment expertise (real-time mixed-precision inference on constrained GPUs) with product and investor-facing leadership. He’s comfortable moving models from simulation and lab to safety-critical industrial and clinical environments, and is known for scaling ML infra to handle ultra-large datasets and data drift.
8 years of coding experience
6 years of employment as a software developer
Master of Engineering - MEng Medical Engineering, Master of Engineering - MEng Medical Engineering at Cardiff University / Prifysgol CaerdyddDoctor of Philosophy Artificial Intelligence & 3D Computer Vision, Doctor of Philosophy Artificial Intelligence & 3D Computer Vision at Imperial College London
Github Skills (17)
histogram-of-oriented-gradients10
classifier9
histogram9
svm8
vector7
object-detection6
machine-learning6
python6
depth5
prediction5
deep-learning5
pytorch5
3d-reconstruction3
pytorch-lightning2
lightning2
Programming languages (2)
Github contributions (5)
SamPlvs/Deep-Reinforcement-Learning
May 2019 - May 2019
Contributions:48 commits, 47 pushes, 1 branch in 6 days
SamPlvs/Object-detection-via-HOG-SVM
Mar 2018 - May 2018
This is an application of Object detection using Histogram of Oriented Gradients (HOG) as features and Support Vector Machines (SVM) as the classifier. Implemented in python, the following libraries are requires
Contributions:20 commits, 1 PR, 17 pushes in 2 months
pytorchsupport-vector-machinespythonclassifiergradients
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