Challenger Mishra

About

Challenger is a Theoretical Physicist working on AI driven mathematical discovery. As an Assistant Research Professor Challenger’s work is at the intersection of Physics, Geometry, and Machine Learning. Currently, he is developing new machine driven approaches to AI assisted mathematics through conjecture generation. At Queens’ he has been the Director of Studies in Computer Science since 2022, and the Adeline Yen Mah Bye-Fellow. He is also a co-founder of the Queens’ Entrepreneurship Society. He did a doctorate in theoretical physics studying Calabi–Yau manifolds with applications to quantum gravity at the University of Oxford, as a Rhodes scholar. Previously he worked at The Alan Turing Institute, London, the Oxford University’s Department of Computer Science, and the International Centr

Selected publications

• Hermitian Yang–Mills connections on general vector bundles: geometry and physical Yukawa couplings – Mishra, Tan, Journal of High Energy Physics, Volume 2026, article number 93 (2026).
• Symbolic Approximations to Ricci-flat Metrics Via Extrinsic Symmetries of Calabi-Yau Hypersurfaces – Mirjanić, Mishra, Machine Learning: Science and Technology 6.3 (2025): 035029.
• Precision String Phenomenology – Berglund, Butbaia, Hübsch, Jejjala, Peña, Mishra, Tan, Physical Review D, 111.8 (2025): 086007
• Calabi-Yau metrics through Grassmannian learning and Donaldson’s algorithm – Henrik Ek, Kim, Mishra, Contemporatary Mathematics, American Mathematical Society, 2025.
• cymyc – Calabi-Yau Metrics, Yukawas, and Curvature – Berglund, Butbaia, Hübsch, Jejjala, Peña, Mishra, Tan, Journal of High Energy Physics 2025 (3), 1-31.
• Learning to be Simple – He, Jejjala, Mishra, Sharnoff, AI for Science 1.2 (2025): 025006.
• Physical Yukawa Couplings in Heterotic String Compactifications – Berglund, Butbaia, Hübsch, Jejjala, Peña, Mishra, Tan, Advances in Theoretical and Mathematical Physics, 28 (2024) 8.
• Machine Learned Calabi–Yau Metrics and Curvature – Berglund, Butbaia, Hübsch, Jejjala, Mayorga Peña, Mishra, Tan — Advances in Theoretical and Mathematical Physics, Vol 27, Number 4, 2023.
• Neural Network Approximations for Calabi–Yau Metrics— Jejjala, Mayorga Peña, Mishra, Journal of High EnergyPhysics, Volume 2022, Article number: 105, 2022.
• Baryons from Mesons: A Machine Learning Perspective — Gal, Jejjala, Mayorga Peña, Mishra, International Journal of Modern Physics A, Vol 37, No 6, 2022.