IIT Patna
Research Areas:
Mathematical Finance, Numerical Methods for PDEs, Machine learning in derivative Pricing
ResearchGate:
www.researchgate.net/profile/Kuldip-Patel-5
Google Scholar:
scholar.google.co.in/citations?user=5RG97_8AAAAJ&hl=en
ORCID iD: orcid.org/0000-0001-8108-8195
Research Area: Computational Finance and Deep Learning Approaches for Pricing Options
ResearchGate: www.researchgate.net/profile/Pradeep-Sahu-16?ev=hdr_xprf
Google Scholar: scholar.google.com/citations?user=8Oi7KRkAAAAJ&hl=en
Email: pradeep_2321ma03@iitp.ac.in
Research Area: Computational Finance
Email: vinay_2421ma05@iitp.ac.in
Research Area: Computational Methods for Pricing Interest Rate Derivatives
ResearchGate:
Google Scholar:
Email: bidyadhar_2421ma03@iitp.ac.in
Contact: +919078724172
Research Area: Numerical Methods for Option Pricing
ResearchGate: www.researchgate.net/profile/Monu-Kumar-29?ev=hdr_xprf
Google Scholar: scholar.google.com/citations?user=6QRL9MQAAAAJ&hl=en
ORCID iD: orcid.org/0009-0001-7246-0722
Email: monu_2422ma04@iitp.ac.in
◼️ Siddhant Pratap Singh (Ongoing)
◼️ Vaibhav Ingle (Ongoing)
◼️ Yash Kumar, Forecasting Stock Indices and Environmental Systems-A comparative analysis of Stochastic and Machine Learning Models, 2025
◼️ Sandeep Kumar Ram, Numerical methods for differential equations, 2025
◼️ Dipanjon Sen, Data driven option pricing using single and multi-asset Supervised Learning, 2024
◼️ Subhadeep Das, Inferring solutions of differential equations using noisy multi-fidelity data, 2024
◼️ Ravi Raj, Study of discrete Markov Chain and its Application, 2024
◼️ Aryan Kothioyal, Solving Nonlinear PDEs using Stochastic ML and Residual Networks for Option Pricing, 2025
◼️ Aryan Mrigwani, Solving Partial Differential Equations with convolutional neural network, 2025
◼️ Prakhar Gupta, Learning time-dependent PDEs with a linear and nonlinear separate convolutional neural network, 2025
◼️ Prakash Kumar Jha, A Machine Learning Based Approach to Assess Impact of MGNREGA and PDS on Agricultural Labour Availability, 2025
◼️ Suryansh Jaiswal, Solving Nonlinear PDEs using Stochastic ML and Residual Networks for Option Pricing, 2025
◼️ Devesh Kumar Pandey, An Assessment of Impact of MGNREGA and PDS on Agricultural Labour Availability, 2025
◼️ Ayush Bhaskar Singh, Adaptive Weighting Strategies in Physics-Informed Neural Networks: A Focus on Self-Adaptive PINNs for solving PDEs, 2025
◼️ Rishabh Raunak, Advanced Physics-Informed Neural Networks for solving Partial Differential Equations, 2025
◼️ Keshav Saxena, Solving Partial Differential Equations with Deep Operator Neural Networks- DeepONets, 2025
◼️ Shantanu Vishal Punde, Energy Dissipative Deep Operator Neural Networks for solving Partial Differential Equations, 2025
◼️ Abhishek Nayak, Topic: Option Pricing with Machine Learning, 2021
◼️ Priyansh Bharadwaj, Topic: Solving High Order Partial Differentiation Equation Using Deep Learning, 2021
◼️ Rishabh Prasad Topic: Pricing Options and computing implied volatilities using Artificial Neural Networks, 2021
◼️ Suraj Kumar, Institute of Mathematics and Applications, Bhubneshwar (May 2022-July 2022)
◼️ Parul Agarwal, Institute of Mathematics and Applications, Bhubneshwar (May 2022-July 2022)
◼️ Tushar Raj, BIT Mesra (May 2021- July 2021)
◼️ S. Priyadarshini, Bishop Heber College, Tuticorin, Tamilnadu (May 2021- July 2021)
◼️ Divyansh Rai, IIIT Allahabad (May 2020- June 2020)
◼️ Sandhya Rathore, IIT BHU (May 2020- June 2020)
◼️ Avanish Pratap Singh, Galgotias University (May 2020- June 2020)