Summary
Melan Vijayaratnam is an AI research engineer and PhD in Machine Learning and Computer Vision specializing in low-latency video transmission, with nine years of cross-disciplinary experience spanning academia and industry. He has conducted research at Telecom Paris and CNRS-affiliated GREYC, worked on Bayesian deep learning for 2D object detection at Valeo, and explored deep learning for robotic grasping at Georgia Tech. Currently at Ektacom, he applies few-shot and meta-learning techniques to practical perception problems, bridging rigorous research with product-facing constraints. His background combines strong theoretical training (PhD, MSc engineering) with hands-on internships and research engineering roles across France, the UK, and the US. Notably, his work emphasizes low-latency, resource-aware models for real-time video systems rather than purely benchmark-driven performance. Based in Greater Paris, he brings a pragmatic research-to-deployment mindset to applied computer vision challenges.
9 years of coding experience
2 years of employment as a software developer
Master of Science (MSc) Electrical and Computer Engineering, Master of Science (MSc) Electrical and Computer Engineering at Georgia Institute of Technology
Master of Science Graduate in Engineering of ENSEA, Master of Science Graduate in Engineering of ENSEA at Ecole nationale supérieure de l'Electronique et de ses Applications
Doctor of Philosophy - PhD Signal Images Automatique et Robotique, Doctor of Philosophy - PhD Signal Images Automatique et Robotique at Institut Polytechnique de Paris
Doctor of Philosophy - PhD, Doctor of Philosophy - PhD at Télécom Paris
French, English, Spanish, Japanese