Dr Valentin Danchev

Profile

Dr Valentin Danchev is a Senior Lecturer (Associate Professor) in Business Analytics in the School of Business and Management at Queen Mary University of London, and a Fellow of the Software Sustainability Institute. He holds a DPhil in Development Studies from the University of Oxford (Oxford Department of International Development), where he was also affiliated with the network science group at the Mathematical Institute. Prior to joining Queen Mary, he was a Lecturer in Computational Social Science at the University of Essex and held postdoctoral positions at the Stanford University School of Medicine and the University of Chicago.

Valentin’s research combines computational methods from social data science and network analysis, with approaches from reproducible research and metascience to study issues of data governance, responsible data science workflows, transparency, reproducibility, bias, and social impact of data-intensive research. His current focus is on evaluating the robustness and reliability of AI/ML technologies in the social and health sciences.

Teaching

Undergraduate

• BUS265: Machine Learning and Digital Technology
• BUS346: Social Network Analysis

Valentin teaches machine learning and business analytics with an emphasis on open reproducible research and responsible analysis of real-world data. His open learning materials on Reproducible Data Science with Python provide an accessible introduction to modern open-source computational tools, reproducible workflows, hands-on Python coding, and data science techniques (from exploratory data analysis (EDA), machine learning, causal inference, and network analysis) necessary to perform open, reproducible, and ethical data analysis.

Valentin is a Fellow of the UK Higher Education Academy.

Research

Research Interests:

Research interests

Responsible Business Data Science, Machine Learning, Data Governance, Evaluation of AI & Large Language Models, Research Reproducibility & Transparency, Network Science, Digital Health Interventions, Human Mobility & Migration

Centre and Group Membership

Valentin is a member of the Centre for Globalisation Research (CGR) and the Computational and Quantitative Methods (CQM) research group.

Selected Publications

Journal articles

• Xianyuan Liu, Jiayang Zhang, Shuo Zhou, Thijs L van der Plas, Avish Vijayaraghavan, Anastasiia Grishina, Mengdie Zhuang, Daniel Schofield, Christopher Tomlinson, Yuhan Wang, et al. 2025. Towards deployment-centric multimodal ai beyond vision and language. arXiv preprint arXiv:2504.03603. https://doi.org/10.48550/arXiv.2504.03603
• Stoudt S, Jernite Y, Marshall B, Marwick B, Sharan M, Whitaker K, Danchev V. (2024) Ten simple rules for building and maintaining a responsible data science workflow. PLOS Computational Biology 20(7): e1012232. https://doi.org/10.1371/journal.pcbi.1012232
• BigScience Workshop, Teven Le Scao, Angela Fan, Christopher Akiki, Ellie Pavlick, Suzana Ilić, Daniel Hesslow, Roman Castagné, Alexandra Sasha Luccioni, François Yvon, Matthias Gallé, Jonathan Tow, Alexander M Rush, Stella Biderman, Albert Webson, Pawan Sasanka Ammanamanchi, Thomas Wang, Benoît Sagot, Niklas Muennighoff, Albert Villanova del Moral, Olatunji Ruwase, Rachel Bawden, Stas Bekman, Angelina McMillan-Major, Iz Beltagy, Huu Nguyen, Lucile Saulnier, Samson Tan, Pedro Ortiz Suarez, Victor Sanh, Hugo Laurençon, Yacine Jernite, Julien Launay, Margaret Mitchell, Colin Raffel, Aaron Gokaslan, Adi Simhi, Aitor Soroa, Alham Fikri Aji, Amit Alfassy, Anna Rogers, Ariel Kreisberg Nitzav, Canwen Xu, Chenghao Mou, Chris Emezue, Christopher Klamm, Colin Leong, Daniel van Strien, David Ifeoluwa Adelani, Dragomir Radev, Eduardo González Ponferrada, Efrat Levkovizh, Ethan Kim, Eyal Bar Natan, Francesco De Toni, Gérard Dupont, Germán Kruszewski, Giada Pistilli, Hady Elsahar, Hamza Benyamina, Hieu Tran, Ian Yu, Idris Abdulmumin, Isaac Johnson, Itziar Gonzalez-Dios, Javier de la Rosa, Jenny Chim, Jesse Dodge, Jian Zhu, Jonathan Chang, Jörg Frohberg, Joseph Tobing, Joydeep Bhattacharjee, Khalid Almubarak, Kimbo Chen, Kyle Lo, Leandro Von Werra, Leon Weber, Long Phan, Ludovic Tanguy, Manan Dey, Manuel Romero Muñoz, Maraim Masoud, María Grandury, Mario Šaško, Max Huang, Maximin Coavoux, Mayank Singh, Mike Tian-Jian Jiang, Minh Chien Vu, Mohammad A Jauhar, Mustafa Ghaleb, Nishant Subramani, Nora Kassner, Nurulaqilla Khamis, Olivier Nguyen, Omar Espejel, Ona de Gibert, Paulo Villegas, Peter Henderson, Pierre Colombo, Priscilla Amuok, Quentin Lhoest, Rheza Harliman, Rishi Bommasani, Roberto Luis López, Rui Ribeiro, Salomey Osei, Sampo Pyysalo, Sebastian Nagel, Shamik Bose, Shamsuddeen Hassan Muhammad, Shanya Sharma, Shayne Longpre, Somaieh Nikpoor, Stanislav Silberberg, Suhas Pai, Sydney Zink, Tiago Timponi Torrent, Timo Schick, Tristan Thrush, Valentin Danchev, Vassilina Nikoulina, Veronika Laippala, Violette Lepercq, Vrinda Prabhu, Zaid Alyafeai, Zeerak Talat, Arun Raja, Benjamin Heinzerling, Chenglei Si, Davut Emre Taşar, Elizabeth Salesky, Sabrina J Mielke, Wilson Y Lee, Abheesht Sharma, Andrea Santilli, Antoine Chaffin, Arnaud Stiegler, Debajyoti Datta, Eliza Szczechla, Gunjan Chhablani, Han Wang, Harshit Pandey, Hendrik Strobelt, Jason Alan Fries, Jos Rozen, Leo Gao, Lintang Sutawika, M Saiful Bari. 2023. BLOOM: A 176B-Parameter Open-Access Multilingual Language Model. arXiv preprint arXiv:2211.05100v4. https://doi.org/10.48550/arXiv.2211.05100
• Danchev, V., (2022). Reproducible Data Science with Python: An Open Learning Resource. Journal of Open Source Education, 5(56), 156. https://doi.org/10.21105/jose.00156.
• Yacine Jernite, Huu Nguyen, Stella Biderman, Anna Rogers, Maraim Masoud, Valentin Danchev, Samson Tan, Alexandra Sasha Luccioni, Nishant Subramani, Isaac Johnson, Gerard Dupont, Jesse Dodge, Kyle Lo, Zeerak Talat, Dragomir Radev, Aaron Gokaslan, Somaieh Nikpoor, Peter Henderson, Rishi Bommasani, and Margaret Mitchell. 2022. Data Governance in the Age of Large-Scale Data-Driven Language Technology. In 2022 ACM Conference on Fairness, Accountability, and Transparency (FAccT '22). Association for Computing Machinery, New York, NY, USA, 2206–2222. https://doi.org/10.1145/3531146.3534637
• Danchev, V., Min, Y., Borghi, J., Baiocchi, M. and Ioannidis, JPA., (2021). Evaluation of Data Sharing After Implementation of the International Committee of Medical Journal Editors Data Sharing Statement Requirement.Jama Network Open. 4 (1), e2033972-e2033972
• Naudet, F., Siebert, M., Pellen, C., Gaba, J., Axfors, C., Cristea, I., Danchev, V., Mansmann, U., Ohmann, C., Wallach, JD., Moher, D. and Ioannidis, JPA., (2021). Medical journal requirements for clinical trial data sharing: Ripe for improvement.PLOS Medicine. 18 (10), e1003844-e1003844
• Hardwicke, TE., Serghiou, S., Janiaud, P., Danchev, V., Crüwell, S., Goodman, SN. and Ioannidis, JPA., (2020). Calibrating the Scientific Ecosystem Through Meta-Research. Annual Review of Statistics and Its Application. 7 (1), 11-37
• Janiaud, P., Axfors, C., van't Hooft, J., Saccilotto, R., Agarwal, A., Appenzeller-Herzog, C., Contopoulos-Ioannidis, DG., Danchev, V., Dirnagl, U., Ewald, H., Gartlehner, G., Goodman, SN., Haber, NA., Ioannidis, AD., Ioannidis, JPA., Lythgoe, MP., Ma, W., Macleod, M., Malički, M., Meerpohl, JJ., Min, Y., Moher, D., Nagavci, B., Naudet, F., Pauli-Magnus, C., O'Sullivan, JW., Riedel, N., Roth, JA., Sauermann, M., Schandelmaier, S., Schmitt, AM., Speich, B., Williamson, PR. and Hemkens, LG., (2020). The worldwide clinical trial research response to the COVID-19 pandemic - the first 100 days. F1000Research. 9, 1193-1193
• Danchev, V., Rzhetsky, A. and Evans, JA., (2019). Centralized scientific communities are less likely to generate replicable results. eLife. 8, e43094
• Danchev, V. and Porter, MA., (2018). Neither global nor local: Heterogeneous connectivity in spatial network structures of world migration. Social Networks. 53, 4-19

Book Chapters

Danchev, V. and Porter, M., (2021). Migration networks: applications of network analysis to macroscale migration patterns. In: Research Handbook on International Migration and Digital Technology. Edited by Marie McAuliffe. Edward Elgar Publishing. 70–90. https://doi.org/10.4337/9781839100611

Supervision

Valentin welcomes prospective PhD students interested in the following topics: responsible data science and business analytics, evaluation of transparency, reproducibility and robustness of applications of machine learning and artificial intelligence, computational social science, social networks, causal inference, science policy and innovation, data governance, and digital health interventions. 

Public Engagement

Valentin is a Fellow of the Software Sustainability Institute, Academic Fellow of QMUL Digital Environment Research Institute (DERI), and Member of the Steering Committee of the PRISM Health Symposium (Promoting Research in Social Media and Health), University of California, San Francisco (UCSF).

Press Coverage

• “Many researchers say they’ll share data — but don’t” Nature 606, 853 (2022)

"Taking the pain out of data" Nature 610, 220-221 (2022).