Franklin Templeton
Director, Principal Research Scientist
AI, machine learning, optimization, and data-driven decision-making
Harshad Khadilkar
Visiting Associate Professor in Computer Science and Engineering at IIT Bombay, and Director / Principal Research Scientist at Franklin Templeton. His work spans AI-driven investment methods, reinforcement learning, operations research, simulation, transportation, supply chains, and energy systems.
Current roles
Franklin Templeton and IIT Bombay
Page updated
May 2026
Summary
A concise view of the main profile themes.
- Research and teaching expertise in machine learning, AI, and data-driven business decision-making.
- Academic foundation from IIT Bombay and MIT, with PhD and SM degrees from MIT.
- Corporate research leadership across Franklin Templeton, Tata, TCS Research, and IBM Research.
- Applied research and consulting experience across finance, supply chain, energy, retail, and transportation.
- 12 years of combined industry and research experience, including team and student leadership.
- Global academic and industry network, including an ongoing formal association with IIT Bombay.
Work Experience
Current and recent roles.
Computer Science and Engineering, IIT Bombay
Visiting Associate Professor
Tata Sons
Data Science Lead
TCS Research
Senior Scientist / Scientist
IBM Research
Research Scientist
Education
Formal training and academic distinctions.
Massachusetts Institute of Technology
PhD, Aeronautics and Astronautics
Massachusetts Institute of Technology
SM, Aeronautics and Astronautics
Indian Institute of Technology, Bombay
BTech, Aerospace Engineering
Career Highlights
Selected awards, talks, and recognitions.
- Distinguished PC member award at CODS-COMAD 2024.
- Best paper in industry track at CODS-COMAD 2021.
- TEDx IMI Kolkata Live talk in 2019.
- TCS Innovista 2019 team prize, selected from more than 4000 entries.
- Second prize in the 2017 INFORMS railway analytics competition.
- Third prize in the 2015 INFORMS railway analytics competition.
- Nominated by IBM for the 2015 Global Young Scientists Summit.
- Best paper awards at ACM BuildSys and ACM e-Energy in 2014.
- IBM Outstanding Technical Achievement award in 2015.
- Institute silver medal from IIT Bombay in 2009.
Publications and Patents
Selected items. See Google Scholar for the full publication list.
Book Chapters
Circular Economy Enabled by Community Microgrids, Seetharam, Khadilkar, Ganu, in An Introduction to Circular Economy, Springer, 2020.
Towards Adaptive Enterprise: Adaptation and Learning, Khadilkar, Paranjape, in Advanced Digital Architectures for Model-Driven Adaptive Enterprises, IRMA, 2020.
Recent Papers
Using Common Random Numbers for Simulation-based Planning with Rollouts, Yadav, Maliakkal, Khadilkar, Kalyanakrishnan, RLC 2026.
A Meta Reinforcement Learning Approach to Goals-Based Wealth Management Reference, Das, Khadilkar, Mittal, Ostrov, Srivastav, Wang, JFDS 2026.
Interpreting Omega Ratio for Goals-Based Wealth Management, Khadilkar, Mittal, Gorjala, Wang, Radhakrishnan, Srivastav, JoWM 2026.
AURA-QG: Automated Unsupervised Replicable Assessment for Question Generation, Rajshekar, Khadilkar, Bhattacharyya, AACL-IJCNLP 2025.
Efficiency Boost in Decentralized Optimization, Kalwar, Khadilkar, Baranwal, CIKM 2025.
Linear-Time Optimal Deadlock Detection for Efficient Scheduling in Multi-Track Railway Networks, Doshi, Tripathi, Agarwal, Khadilkar, Kalyanakrishnan, IJCAI 2024.
Patents
System and Method for Concurrent Dynamic Optimization of Replenishment Decisions in Networked Node Environment, granted March 2022.
System and Method for Pre-emptive Product Selection from an Inventory, filed December 2018.
Managing a Picogrid with a Computing Device, granted December 2017.
Contact
For academic collaboration, talks, student projects, or industry research conversations, reach out by email.