🧑‍🔬 Manish Kumar

🏛️ Affiliations

🎓Indian Institute of Information Technology AllahabadPrayagraj · India2005–2011Education 2007–2011 · Ph.D, ITEmployment since 2005 · Associate Professor, Information Technologycurrent🎓University of OxfordOxford · United Kingdom2008–2023 · 36 papers🎓École Centrale ParisChâtenay-Malabry · France2012–2016 · 12 papers🎓Stanford UniversityStanford · United States2008–2012 · 8 papers🔬The Alan Turing InstituteLondon · United Kingdom2016–2019 · 7 papers🔬CentraleSupélecGif-sur-Yvette · France2014–2016 · 7 papers🎓Oxford Brookes UniversityOxford · United Kingdom2005–2007 · 7 papers🔬Centre de Vision NumériqueGif-sur-Yvette · France2014–2016 · 6 papers🔬Institut national de recherche en sciences et technologies du numériqueLe Chesnay-Rocquencourt · France2013–2015 · 6 papers🔬Centre Inria de SaclayPalaiseau · France2013–2015 · 4 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 7 more institutions on single bylines are not listed.

🧭 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. AlphaEvolve: A coding agent for scientific and algorithmic discovery (2025 · 202 citations)
   AlphaEvolve is a coding agent from Google DeepMind. It tests whether large language models can produce new discoveries, not just strong benchmark scores, on problems where a machine can check candidate answers. The user supplies three things: a working starting program with sections flagged for evolution, an…
2. Mathematical Discoveries from Program Search with Large Language Models (2023 · 200 citations)
   Large language models can write code, but they often produce answers that sound right and are wrong. That makes them hard to trust for new scientific results. The authors present FunSearch, an evolutionary loop that combines a frozen code LLM (Codey, built on PaLM2) with an automatic evaluator that scores each…
3. NIT-Agartala-NLP-Team at SemEval-2026 Task 9: A Weighted Soft-Voting Ensemble Framework of Fine-Tuned LLMs for Binary and Multi-Label Polarization Detection (2026)
   The paper describes a system for SemEval-2026 Task 9, which targets polarization in online text. The task has two parts: deciding whether a post is polarized, and labeling polarized posts with one or more types (Political, Racial/Ethnic, Religious, Gender/Sexual, Others). The task corpus covers 22 languages, but the…

All works

15 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them.

1. OBJ CUT ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetManish Kumar, Philip H. S. Torr, Andrew Zisserman2005 · 329 citations
2. AlphaEvolve: A coding agent for scientific and algorithmic discoveryarXiv:2506.13131Alexander Novikov, Ngân Vũ, Marvin Eisenberger, et al.2025 · 202 citations
3. Mathematical Discoveries from Program Search with Large Language ModelsNature 625Bernardino Romera-Paredes, Mohammadamin Barekatain, Alexander Novikov, et al.2023 · 200 citations
4. Efficient discriminative learning of parts-based models ↗IEEE International Conference on Computer Vision (ICCV) · no summary yetManish Kumar, Andrew Zisserman, Philip H. S. Torr2009 · 84 citations
5. OBJCUT: Efficient Segmentation Using Top-Down and Bottom-Up Cues ↗IEEE Transactions on Pattern Analysis and Machine Intelligence · no summary yetManish Kumar, P. Torr, Andrew Zisserman82 citations
6. Smooth Loss Functions for Deep Top-k Classification ↗arXiv:1802.07595 · no summary yetLeonard Berrada, Andrew Zisserman, M. Pawan Kumar2018 · 73 citations
7. An Invariant Large Margin Nearest Neighbour Classifier ↗IEEE International Conference on Computer Vision (ICCV) · no summary yetManish Kumar, Philip H. S. Torr, Andrew Zisserman2007 · 45 citations
8. Solving Markov Random Fields using Second Order Cone Programming Relaxations ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetManish Kumar, Philip H. S. Torr, Andrew Zisserman2006 · 37 citations
9. Deep Frank-Wolfe For Neural Network Optimization ↗arXiv (Cornell University) · no summary yetLeonard Berrada, Andrew Zisserman, Manish Kumar2018 · 22 citations
10. Training Neural Networks for and by Interpolation ↗International Conference on Machine Learning · no summary yetLeonard Berrada, Manish Kumar, Andrew Zisserman2020 · 11 citations
11. Trusting SVM for Piecewise Linear CNNs ↗arXiv (Cornell University) · no summary yetLeonard Berrada, Andrew Zisserman, Manish Kumar2016 · 10 citations
12. Learning from M/EEG Data with Variable Brain Activation Delays ↗Lecture notes in computer science · no summary yetWojciech Zaremba et al.2013 · 6 citations
13. An Object Category Specific mrf for Segmentation ↗Lecture notes in computer science · no summary yetManish Kumar, Philip H. S. Torr, Andrew Zisserman2006 · 2 citations
14. NIT-Agartala-NLP-Team at SemEval-2026 Task 9: A Weighted Soft-Voting Ensemble Framework of Fine-Tuned LLMs for Binary and Multi-Label Polarization DetectionInternational Workshop on Semantic Evaluation (SemEval)Shivam, Manish Kumar, Anupam Jamatia2026
15. Comment on Stochastic Polyak Step-Size: Performance of ALI-G ↗arXiv (Cornell University) · no summary yetLeonard Berrada, Andrew Zisserman, Manish Kumar2021

🤝 Co-authors here

6 co-authors with a page, the most papers together first.

• Alexander Novikov ×2
• Emilien Dupont ×2
• Francisco J. R. Ruiz ×2
• Abigail See
• Po-Sen Huang
• Pushmeet Kohli

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings ×2
• IEEE International Conference on Computer Vision (ICCV) ×2
• Lecture notes in computer science ×2
• International Workshop on Semantic Evaluation (SemEval): SemEval 2026
• IEEE Transactions on Pattern Analysis and Machine Intelligence
• International Conference on Machine Learning
• Nature 625

🔗 Cited by

Papers of our library cite their works 408 times (of the 149,439 papers whose bibliographies we read); 36 citing papers with a page here →.

Updated 1 November 2026

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