- Assistant Research Professor
- Director of Studies, Queens' College
- The Adeline Yen Mah Bye Fellow, Queens' College
Biography
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 Centre for Mathematical Sciences in Madrid. As an educator, he has taught Physics, Mathematics, and Computer Science to undergraduate and graduate students for over a decade.
Research
Conjecture Generation, AI for Mathematics, Quantum Gravity.
Media: AI Starts to Sift Through String Theory’s Near-Endless Possibilities
Currently I am the primary supervisor to doctoral students working on Quantum Gravity and AI for Mathematics
Teaching
Theory of Deep Learning, MPhil ACS, (2021 - Present)
Supervisions in Discrete Mathematics, AI. Director of Studies for Part IA (Queens' college).
Professional Activities
Upcoming conferences:
- AI x Mathematics, an AI residency for mathematics, ICMS, Edinburgh, Feb 2026 (co-organisers Yang-Hui He, Minhyong Kim)
- Neural Reasoning for Scientific and Mathematical Discovery, March 2026, Cambridge (co-organisers Tiansi Dong, Pietro Lio, Mateja Jamnik)
- Recent Progress in Computational String Geometry, Chennai Mathematical Institute, Jan 2026 (co-organisers Damian Kaloni Mayorga Pena, Vishnu Jejjala, Tristan Hübsch, Per Berglund, Ivonne Zavala Carrasco).
Past workshops conducted:
- String Data 2025, December, London, Infosys and LIMS (co-organisers Sven Krippendorf, Yang Hui He)
- AAAI workshop, Neural Reasoning and Mathematical Discovery – An Interdisciplinary Two-Way Street, Philadelphia, 2025 (co-organisers Tiansi Dong, Pietro Lio, Mateja Jamnik).
- String Data 2022, University of Cambridge (co-organisers David Berman, Yang-Hui He)
- AI-assisted mathematical discovery, London Institute for Mathematical Sciences, Royal Institution, July 2023 (co-organisers Thomas Fink, Yang-Hui He)
- The annual Hardy Lecture in Mathematics organised by the London Mathematical Society, June 2023 (co-organisers London Mathematical Society, Thomas Fink, Saksham Sharma).
- Accelerate Science Winter School, Department of Computer Science and Technology, University of Cambridge, February 2021 (co-organisers Accelerate Science Team, Cambridge).
Seminar series
- A Hitchhiker’s guide to Complex Geometry, Department of Computer Science and Technology, University of Cambridge alongside, DTU (Denmark), and ARYA (Japan), April – June 2022 (co-organisers Alison Pouplin, Pablo Morales)
- Number Theory and Machine Intelligence, Department of Computer Science and Technology, University of Cambridge, January 2024 (speaker Tom Oliver)
- Reflections on Diophantine equations: an intricate web of theory and computation, Department of Computer Science and Technology, May 2025 (speaker Minhyong Kim)
- Lunch time seminars for the Accelerate Science program, Department of Computer Science and Technology (co-organiser Sam Nallaperuma, Soumya Banerjee)
Publications
Journal articles
- 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.
- Getting CICY High — Bull, Hui-He, Jejjala, Mishra, Physics Letters B, Vol. 795, August 2019, pp.700-706.
- Machine Learning CICY Threefolds — Bull, He, Jejjala, Mishra, Physics Letters B, Vol. 785, October 2018, pp.65-72.
- Highly Symmetric Quintic Quotients — Candelas, Mishra, Fortschritte der Physik, 1800017, 66, 2018.
- Discrete Symmetries of Complete Intersection Calabi-Yau Manifolds — Lukas, Mishra, Communications in Mathematical Physics 379, 847–865 (2020).
- Calabi-Yau Threefolds with Small Hodge Numbers - Candelas, Constantin, Mishra, Fortschritte der Physik, Vol 66, Issue 6, June 2018.
- Hodge Numbers for CICYs with Symmetries of Order Divisible by 4 — Candelas, Constantin, Mishra, Fortschritte der Physik 64 (2016) 463-509.
- The Family Problem: Hints from Heterotic Line Bundle Models — Constantin, Lukas, Mishra, Journal of High Energy Physics (2016): 173.
- Predicting Ruthenium Catalyzed Hydrogenation of Esters Using Machine Learning — Mishra, von Wolff, Tripathi, Bremond, Preiss, Kumar, Lawrence, Ravuri, Digital Discovery, Royal Society of Chemistry, 2023, 2, 819-827.
- Machine Learning for Optical Motion Capture-driven Musculoskeletal Modeling from Inertial Motion Capture Data — Dasgupta, Sharma, Mishra, Nagaraja, Bioengineering, 2023, 10(5), 510, 2022.
- Machine Learning for Musculoskeletal Modeling of Upper Extremity — Sharma, Dasgupta, Cheng, Mishra, Nagaraja, IEEE Sensors Journal, 22.19 (2022): 18684-18697.
- Phase-controlled Stable Solitons in Nonlinear Fibers — Rajitha, Mishra, Dey, Panigrahi, 2019, Journal of the Optical Society of America B, 36(1), pp.1-6.
- Chemical Oscillation in Ultracold Chemistry — Modak, Das, Mishra, Panigrahi, Europhysics Letters 145 (3), 32003.
- Resolving overlapping transitions in the 1S0→ 3P1 line of Yb using the Zeeman effect, Mishra, Pandey, Nartarajan, Prayas 3 (4).
Workshop articles
- Learning Modular Exponentiation with Transformers, Demitri Africa, Kapoor, Sorg, Mishra, NeurIPs workshop, 2025.
- A Matter of Interest: Understanding Interestingness of Math Problems in Humans and Language Models, (Shubhra) Mishra, Machino, Poesia, Jiang, Hsu, Weller, (Challenger) Mishra, Broman, Tenenbaum, Jamnik, Zhang, Collins, NeurIPs workshop, 2025.
- A Physics-informed Search for Metric Solutions to Ricci Flow, Their Embeddings, and Visualization — Jain, Mishra, Lio, NeurIPs workshop, ML and Physical Sciences, 2022.
Preprints
- Hermitian Yang–Mills connections on general vector bundles: geometry and physical Yukawa couplings – Mishra, Tan, 2512.10907.
- A remark on weighted average multiplicities in prime factorisation — Mirjanić, Aggarwal, Mishra, 2510.06993.
- Machine Learning Workflows for Motion Capturedriven Biomechanical Modelling — Nagaraja, Sharma, Dasgupta, Mishra, 10.21203/rs.3.rs-6588431.
- Mathematical Conjecture Generation Using Machine Intelligence — Mishra, Roy Moulik, Sarkar, 2306.07277.
- New Cross-phase Modulated Localized Solitons in Coupled Atomic-Molecular BEC — Mishra, Das, Dastidar, Panigrahi, 1109.5571.
- Grey Solitons in Doped Optical Fibers — Mishra, Dey, Panigrahi, 1109.4556.
Thesis: Calabi--Yau Manifolds, Discrete Symmetry, and String theory
