Dr. Rohit Kumar Singla is currently serving as an Associate Professor in the Department of Mechanical Engineering at Thapar Institute of Engineering & Technology, Patiala, India. He is associated with the Thermal Group and holds over 10 years of teaching and research experience, both pre- and post-Ph.D. He received his doctoral degree in 2017 from the Indian Institute of Technology (IIT) Ropar, specializing in inverse heat and mass transfer analysis of thermal systems, and completed his M.Tech. in Thermal Engineering from PEC University of Technology, Chandigarh.

Dr. Singla’s core research interests include inverse problems in heat transfer, optimization algorithms, energy systems (cooling towers, heat sinks, solar collectors), bioheat transfer, and phase change materials (PCM). His academic contributions reflect a deep integration of applied mathematics and computational modeling to solve forward and inverse heat transfer problems. He has worked extensively on ill-posed inverse problems, particularly parameter estimation and flux retrieval, applying swarm intelligence, differential evolution, genetic algorithms, and artificial bee colony algorithms. His work has been published in top-tier journals such as Reviews in Mathematical Physics, Applied Thermal Engineering, International Communications in Heat and Mass Transfer, and Inverse Problems in Science and Engineering.

In recent years, Dr. Singla has actively explored the interface of AI/ML and mathematical modeling. He co-developed an ANN-based pricing model for financial derivatives and employed spectrophotometry and machine learning techniques in fruit classification and grading, published in the IEEE Sensors Journal. These AI-driven tools reflect his interdisciplinary capability to merge physical modeling with data-driven techniques.

His expertise in numerical methods includes regularization strategies for inverse problems, PDE-based modeling of composite thermal systems, and advanced basis function methods such as curvelets and decomposition techniques (Adomian, Fourier, wavelets). His work on wavelet- and curvelet-based solvers for nonlinear Schrödinger equations and radiative heat conduction problems demonstrates his deep familiarity with harmonic analysis, which underpins the emerging W-PINNs (Wavelet-based Physics-Informed Neural Networks) methodology.

He has authored more than 30 international journal publications and delivered presentations at reputed international conferences in Japan, USA, Singapore, and Vietnam, reflecting his technical leadership and global engagement. He is currently supervising Ph.D. and master’s students in thermal-fluids, inverse modeling, and AI-driven system design.

Sponsored Research Projects

Dr. Singla has been actively involved in several sponsored research projects, demonstrating his ability to lead and deliver high-impact research outcomes. Notable projects include:

• Principal Investigator (PI) of the DRDO-AIDB Board-funded project titled "Development of a Novel Process for Fabrication of Cost-Effective CFRP/Ti/Al Stacked composites for Structural Aerospace Applications", with a total funding of INR 26 lakhs, aimed at enhancing the thermal management of defense-grade electronics.

• PI of an industry-sponsored project titled "Enhancing Energy Efficiency in Industrial Facilities through Advanced Waste Heat Recovery Strategies", funded by Trident Group, India, with a total sanctioned budget of INR 7.19 lakhs. The project focuses on identifying and recovering waste heat from various process streams in the pulp and paper industry to reduce energy consumption and operational costs.

• Co-PI in two institute-funded projects at Thapar Institute of Engineering & Technology, addressing smart thermal management using Phase Change Materials and Time Table Management System in sustainable engineering applications.

These projects not only underline his expertise in thermal systems, software, and industrial energy efficiency but also reflect strong collaborations with industry and government R&D agencies.