Ms. Divyanee Garg | Economics, Econometrics and Finance | Best Researcher Award
Indian Institute of Technology, Delhi | India
Ms. Divyanee Garg is a mathematician specializing in Portfolio Optimization, Behavioural Finance, Robust Portfolio Optimization, and Data-Driven Financial Techniques. Her research focuses on developing innovative mathematical and computational frameworks for decision-making under uncertainty, combining advanced risk measures such as Expectile Value at Risk (EVaR) and Conditional Value at Risk (CVaR) with behavioral finance models. She has contributed significant work on robust portfolio optimization using deep neural networks, integrating data-driven approaches to enhance traditional financial modeling. Ms. Divyanee Garg has published in high-impact journals, including Computational and Applied Mathematics and Omega, addressing deviation measures, robust allocation strategies, and cumulative prospect theory-based indexing, reflecting her strong influence in the field. She has presented her research at international conferences, including the 34th European Conference on Operational Research (EURO 2025, UK) and the ORSI Annual Convention 2024 (IIT Bombay), as well as symposia at IIT Roorkee and ISI Delhi, demonstrating active engagement with the global research community. Her notable projects include the development of optimality and duality conditions for semi-infinite programming problems and numerical improvements to Gauss-Chebyshev quadrature rules, both highlighting her analytical rigor and methodological innovation. Recognized for her academic excellence, she is a recipient of the Prime Minister’s Research Fellowship (PMRF) and the INSPIRE Scholarship from the DST, India. Ms. Divyanee Garg actively contributes to workshops and summer schools on large-scale optimization and machine learning applications in finance, combining theoretical depth with practical relevance. Her research exemplifies the integration of mathematical rigor, computational innovation, and applied financial insight, positioning her as a leading young researcher in quantitative finance and optimization.
Profiles: Google Scholar | ORCID | ResearchGate | LinkedIn | Staff Profile
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