Dr. Prince Solanki is an academician, presently working as Assistant Professor of Mathematics at the School of Computer Science & Engineering, IILM University, Gurugram. He completed his Ph.D. in Operations Research from the Indian Institute of Technology (IIT) Roorkee and has over two years of post-doctoral teaching experience at the university level. His primary research interests lie in mathematical optimization, operations research, and nature-inspired metaheuristic algorithms, with applications to renewable-energy system design, most notably wind farm layout optimization (WFLOP). As a researcher, he has published in reputed SCI/SCIE- and Scopus-indexed international journals of Elsevier and Springer, and in peer-reviewed conference proceedings, and remains an active contributor to the soft computing and optimization research community. He has twice qualified the CSIR-UGC NET (Mathematical Sciences), in addition to GATE and IIT-JAM qualifications.

Educational Qualification

• Ph.D., Mathematics (Operations Research), Indian Institute of Technology (IIT) Roorkee (2017–2024)
  – Thesis: Design and Development of New Variants of Salp Swarm Algorithm for Energy-Related Optimization Problems (Supervisor: Prof. Kusum Deep)
• M.Sc., Mathematics, Indian Institute of Technology (IIT) Roorkee (2015–2017)
• B.Sc. (Hons.), Mathematics, Ramjas College, University of Delhi (2012–2015)

National Qualifications

• CSIR–UGC NET (Mathematical Sciences) — qualified twice (2017, 2018)
• GATE (Mathematics) — 2017
• IIT-JAM (Mathematics) — 2015

Academic Experience

• Assistant Professor (Mathematics), IILM University — Aug 2024–Present
• Assistant Professor (Mathematics), NIMS University, Jaipur — July 2023–Aug 2024
• Teaching Assistant, Department of Mathematics, IIT Roorkee — 2017–2023

Research Interests

• Mathematical optimization and operations research
• Metaheuristics, evolutionary and nature-inspired algorithm design (Salp Swarm, Genetic, PSO, GWO, BBO variants)
• Statistical validation of stochastic optimization algorithms
• Machine learning integrated with optimization (ML + OR)
• Linear and nonlinear programming; large-scale system modeling
• Renewable-energy optimization, including wind farm layout optimization (WFLOP)

Research and Scholarly Publication

JOURNAL ARTICLES (SCI/SCIE & SCOPUS INDEXED)

• “FreqGAN-GWO: Frequency-domain Generative Adversarial Network with Grey Wolf Optimizer for Robust Single-Image Dehazing” (with P. Dwivedi), Applied Soft Computing, Elsevier, 2026.
• “Laplacian Salp Swarm Algorithm for Continuous Optimization” (with K. Deep), International Journal of System Assurance Engineering and Management, Springer, 2023.
• “Quadratic Approximation Salp Swarm Algorithm for Function Optimization” (with K. Deep), OPSEARCH, Springer, 2023.

CONFERENCE PROCEEDINGS

• “Minimization of Molecular Potential Energy Function Using Laplacian Salp Swarm Algorithm (LX-SSA)” (with K. Deep and A.K. Nagar), Soft Computing for Problem Solving, Lecture Notes in Networks and Systems, Vol. 547, Springer, Singapore, 2023.
• “Examining Structural Bias in Salp Swarm Algorithm and Its Two Variants Using Signature Test: A Theoretical Study” (with K. Rajwar and K. Deep), Soft Computing for Problem Solving (SocProS 2023), Frontiers of Artificial Intelligence, Ethics and Multidisciplinary Applications, Springer, Singapore, 2025.

WORK IN PROGRESS

• Graph Neural Network guided (GNN)-LXSSA & QASSA for the Wind Farm Layout Optimization Problem (WFLOP).

Conference Presentations

• “Minimization of Molecular Potential Energy Function using Laplacian Salp Swarm Algorithm (LX-SSA)” — 11th International Conference on Soft Computing for Problem Solving (SocProS 2022), IIT Mandi, April 2022.
• “Examining Structural Bias in Salp Swarm Algorithm and Its Two Variants using Signature Test: A Theoretical Study” — 12th International Conference on Soft Computing for Problem Solving (SocProS 2023), IIT Roorkee, August 2023.

Teaching

• Engineering Mathematics–I — B.Tech (1st year): calculus, matrices, sequences and series, and ordinary differential equations.
• Engineering Mathematics–II — B.Tech (1st year): multivariable calculus, Laplace transforms, Fourier series, and partial differential equations.
• Linear Algebra (MAN-001) — tutorials and evaluation, IIT Roorkee.
• Numerical Methods (MAN-002) — tutorials and evaluation, IIT Roorkee.

Professional Development

FACULTY DEVELOPMENT PROGRAMMES (FDP)

• E & ICT Academy, IIT Kanpur (a joint initiative of MeitY & IIT Kanpur), June 2025.
• FDP on Deep Learning on TensorFlow — SCRS, New Delhi, with Islamic University of Science and Technology, Awantipora, July 2020.
• International FDP on Nature Inspired Algorithms–II — SCRS, New Delhi, August 2020.

WORKSHOPS & TRAINING PROGRAMMES

• Optimization in Engineering — CSIR-Central Building Research Institute, Roorkee, December 2017.
• GIAN Course: Multi-objective Optimization using Metaheuristics — IIT Kanpur, March 2018.
• Swarm and Evolutionary Algorithms: Theory and Applications — Soft Computing Research Society & Mathematical Colloquium, IIT Roorkee, March 2018.
• SCRS Lecture Series: Nature Inspired Algorithms–I — SCRS, New Delhi, June 2020.
• International Winter Training Course on Nature Inspired Optimization Techniques using MATLAB — E & ICT Academy, IIT Roorkee & SCRS, New Delhi, December 2020.

CONFERENCES ATTENDED

• International Conference on Recent Trends in Operations Research and Statistics (RTORS) — IIT Roorkee, 2017.
• 11th & 12th International Conferences on Soft Computing for Problem Solving (SocProS) — IIT Mandi (2022), IIT Roorkee (2023).

Academic Service & Achievements

• Session Chair — 13th International Conference on Soft Computing for Problem Solving (SocProS 2025), IIT Roorkee.
• Volunteer — International Conference on Recent Trends in Operations Research and Statistics (RTORS 2017), IIT Roorkee.

Technical Skills

• Programming & Computation: MATLAB, Python
• Tools & Documentation: LaTeX, MS Excel, MS Word