Devinder Kumar

Devinder Kumar

Head, ML Systems & Engineering

TD Bank (AI Platform) · Ex-Stanford Postdoc

I am a ML engineering & research leader specializing in building ML platform & systems for building & operationalization of AI/ML models in complex production environments. Looking to build/scale an AI/Machine Learning team(s), engineering tools, infrastructure & operations to deliver business value.

Previously, I was a Postdoctoral Fellow at Stanford University. I completed my PhD in Explainable AI under Dr. Alexander Wong (VIP Lab, UWaterloo) and Dr. Graham Taylor (Machine Learning Research Group, UGuelph).

Career Milestones

Current

Head, ML Systems & Engineering

TD Bank (AI Platform)

Leading machine learning systems & engineering org at AI Platform, TD Bank, focusing on ML Engineering, MLOps, model deployment, and scalable enterprise intelligence.

Past

Postdoctoral Fellow

Stanford University

Research at the Stanford Cognitive & Systems Neuroscience Laboratory (SCSNL), School of Medicine.

Past

Lead AI Scientist

NextAI (NEXT Canada)

Led a team of AI scientists advising world-class startups on AI R&D and product development.

Past

Deep Learning & Research Engineering

Philips Research (HQ) & UPMC-Sorbonne (LIP-6)

Research and engineering roles specializing in deep learning applications, medical oncology solutions, and data science.

Selected Publications

2024 · PLOS Digital Health

Reporting radiographers’ interaction with Artificial Intelligence—How do different forms of AI feedback impact trust and decision switching?

C. Rainey, R. Bond, J. McConnell, C. Hughes, D. Kumar, S. McFadden

2020 · WACV

Unsupervised Domain Adaptation in Person re-ID via k-Reciprocal Clustering and Large-Scale Heterogeneous Environment Synthesis

D. Kumar, P. Siva, P. Marchwica, A. Wong

2018 · Nature Communications

Insightful classification of crystal structures using deep learning

A. Ziletti, D. Kumar, M. Scheffler, L. M. Ghiringhelli

2017 · CVPR Workshop (Oral)

Explaining the Unexplained: A CLEAR Approach to Understanding Deep Neural Networks

D. Kumar, A. Wong, G. W. Taylor

2015 · ICME CEA Workshop

Recipe recognition with large multimodal food dataset

X. Wang, D. Kumar, N. Thome, M. Cord, F. Precioso

2013 · IEEE Potentials (Best Paper)

Constructive Learning for Human-Robot Interaction

A. Singh, S. Karanam, D. Kumar

Media & Impact