Raphael Abt
Manager Digital Crew Planning at Lufthansa Airlines
Cologne, North Rhine-Westphalia, Germany
Summary
👤
Senior🎓
Top SchoolJagadeeswaran Rathinavel is a seasoned data scientist and AI specialist focused on applying deep learning and computer vision to safety-critical infrastructure. As Data Scientist, Staff at Torc Robotics, he contributes to production-grade AI for video perception and analytics in robotics contexts. Previously, as Principal AI/Data Scientist at Wi-Tronix, he built and deployed railroad video analytics solutions, including automated crossing inspections and time-series health diagnostics, using TensorFlow, PyTorch, Docker, and AWS EKS. He holds a PhD in Computational and Applied Mathematics from IIT and a master's in Electrical Engineering with a focus on signal processing, with strong foundations in Bayesian methods and quasi-Monte Carlo techniques. He is an active open-source contributor to QMCPy, a framework for plug-and-play QMC software, and pursues part-time doctoral work in mathematics, alongside hands-on work in 6D pose estimation and synthetic data generation for model training. Based in Chicago, he brings a rare blend of theoretical rigor and production-ready engineering to deliver AI that improves safety and efficiency in rail and industrial systems.
12 years of coding experience
4 years of employment as a software developer
1.1 with distinction, 1.1 with distinction at Karlsruhe Institute of TechnologyMulti-Crew Pilot Licence (MPL), Commercial aircraft pilot training, Multi-Crew Pilot Licence (MPL), Commercial aircraft pilot training at Lufthansa Flight TrainingB. Sc., Industrial Engineering and Management, 1.6, B. Sc., Industrial Engineering and Management, 1.6 at Karlsruhe Institut of Technology
German, English, French
Github Skills (30)
lan10
python10
mathematics10
dimensions10
monte-carlo10
machine-learning9
tensorflow9
neural-network9
deep-learning9
data-structures9
clip8
deep-neural-networks8
segmentation8
ml8
data-science8
Programming languages (3)
Github contributions (5)
GailGithub/GAIL_Dev
Oct 2013 - Jan 2021
GAIL is a suite of algorithms for integration problems in one, many, and infinite dimensions, and whose answers are guaranteed to be correct. GAIL is created, developed, and maintained by Fred Hickernell (Illinois Institute of Technology), Sou-Cheng Choi (University of Chicago and Argonne National Laboratory), and their collaborators including Yuhan Ding (IIT), Lan Jiang (IIT), and Yizhi Zhang (IIT).
Contributions:410 commits, 283 pushes, 2 branches in 7 years 5 months
nationalillinoisfredlaboratoryproblems
jagadeesr/SobolBayesCubaturePaper2019
Dec 2019 - Oct 2022
Contributions:107 pushes, 87 branches in 2 years 10 months
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