Ikjyot Singh Kohli, Ph.D.

Contact Info:

E-mail: ikjyotsingh@icloud.com 

YouTube: https://www.youtube.com/@IkjyotSinghKohli/

Instagram: https://www.instagram.com/ikjyotsingh16/

Publications: https://arxiv.org/a/kohli_i_1.html

Education

• York University, Toronto, Canada — Ph.D. – Mathematical Physics, 2014
• York University, Toronto, Canada — M.Sc. – Mathematical Physics, 2012
• University of Toronto, Toronto, Canada — Honours B.Sc. – Physics and Mathematics, 2010

Recent Experience

Director – Data Science, Loblaw Companies Limited; Toronto, Canada — 2020-Present

• Leading a large team of data scientists and engineers in all areas of data science and analytics focusing on the Media, Marketing, and Loyalty businesses for Loblaw Companies, generating approximately $200M in annual revenue directly attributable to the analytics work done by my team. Led the design and implementation of original machine learning-based solutions with respect to campaign measurement, custom audience targeting, NLP, optimization theory and statistical testing involving very large datasets at scale. Transitioned all solutions to the GCP environment for maximum scalability and efficiency. 

Senior Manager – Data Science, Deloitte-Schulich Cognitive Labs; Toronto, Ontario — 2019-2020

• Senior manager and consultant lead a team of junior data scientists working with several local and international companies spanning a variety of industries from banking and finance to legal and advertising/marketing in implementing end-to-end data science and machine learning solutions. Scaled these solutions in both AWS and Azure environments depending on specific client needs.

Senior Manager – Data Science, Cineplex; Toronto, Canada – 2017-2019

• Led a team of data scientists, engineers and visualization experts responsible for the commercialization of machine learning and AI models supporting several business lines at Cineplex: Marketing, Media, Finance, and others. Developed an attendance and audience projections model for Cineplex Media leading to $30M of quarterly revenue for the company. Invented the showtimes  optimization model for optimal allocation of showtimes scheduling all across all nationwide theatre locations to maximize revenue. (Preprint of results can be found at: http://arxiv.org/abs/1911.10153) All solutions were implemented and scaled in Azure. 

Mathematical Sciences Research, York University — 2015-2017

• Worked on led research for problems in mathematical physics and the mathematical structure of machine learning algorithms. (Major research results can be found here: https://arxiv.org/a/kohli_i_1.html) Many of these results have been published in high-level mathematics and physics journals. Areas of research included: General Relativity, Dynamical Systems, Numerical Methods in AI/ML, Quantization and classical mechanical structures of neural networks.

Recent Publications

• “The Wavefunction of Continuous-Time Recurrent Neural Networks” – I.S. Kohli and M.C. Haslam – arXiv:2102.09399 [cs.LG][math-ph][math.DS][quant-ph] (2021)
• “Einstein’s Field Equations as Continuous-Time Recurrent Neural Networks” – I.S. Kohli – arXiv:2001.02512 [gr-qc] (2020)
• “On an Optimal Solution to the Film Scheduling and Showtime Staggering Problem” – I.S. Kohli and K.G. Inglis – arXiv:1911.10153 [math.OC][stat.ML] (2019)
• “An Analysis of the Replicator Dynamics for an Asymmetric Hawk-Dove Game” – I.S. Kohli and M.C. Haslam – arXiv:1607.05192[math.DS] (2016)
• “Einstein’s Field Equations as a Fold Bifurcation” – I.S. Kohli and M.C. Haslam – arXiv.1607.05300[physics.gen-ph](2016)

Invited Presentations/Talks Given

• “Revolutionzing the Grocery Experience with Data and Actionable Insights” – The Ortus Club – October, 2021
• “CDO – Data and Analytics Executive Virtual Roundtable – Canada” – September, 2021
• “AI in the Insurance Industry” – Talk Given to the China Pacific Insurance Company – December, 2020
• “A Talk on AI” – SEEC – 2019 York University Partner Retreat – June, 2019
• “AI and Automation” – Big Data Toronto, June 2019
• “Data Science Automation at Cineplex” – Data Marketing Toronto – November, 2018
• “Enabling Predictive Analytics at Cineplex” – Big Data Toronto, June 2018