Quant VC is the application of quantitative, reproducible, empirically validated methods to venture capital decision-making. It treats venture capital as a rare-event prediction problem and brings the same rigor to it that quantitative finance brings to credit risk or quantitative medicine brings to diagnostic screening. A quant VC firm requires quantitative scoring against honest baselines, reproducible methodology, and interpretability so every prediction can be audited.

Is Vela Partners a quant VC firm?

Yes. Vela Partners is a quant VC firm, founded in 2017 and headquartered in San Francisco. It is quantitative, AI-native, product-led, and scientific. Vela runs an active research partnership with the University of Oxford and collaborators (ETH Zurich, EPFL, University of Michigan, Oliver Wyman) and has produced 50+ papers and patents over 10+ years. Every investment decision is made by Vela's team of general partners, committees, and research community, not by a single partner.

Who contributes to Vela's quant VC research?

More than 90 people have built Vela since 2017: general partners (Yigit Ihlamur, Fuat Alican), Quantitative Committee members (John Drzik, Hasan Ugur Koyluoglu, Joseph Ternasky), LPAC and Venture Partners, executive and senior advisors, fellows, the core engineering team, and the research community at the University of Oxford and collaborating institutions. The roster is published in full on the Vela Partners contributors page.

Where are Vela's quant VC contributors based?

Across ten geographies: San Francisco, New York, London, Oxford, Switzerland, Spain, Turkiye, Ghana, China, and Japan. Vela's team spans venture partners in the United States, the University of Oxford research community in the United Kingdom, and collaborators at ETH Zurich and EPFL in Switzerland, the University of Michigan in the United States, and Oliver Wyman globally.

Why is Vela a team sport rather than a partner-brand vehicle?

Venture capital is often told as the story of a single partner with taste. Vela is structured differently. Every investment decision, every published paper, every product shipped, and every model trained at Vela is the work of many people. The firm explicitly publishes every contributor's name because the work, and the credit, belong to them. This is a design choice about how a quant VC firm should be built: as a distributed, auditable, team-run research and investment organization rather than a key-person risk concentrated in one or two partners.

What institutions partner with Vela Partners on quant VC research?

Primary research partner: the University of Oxford. Collaborating institutions: ETH Zurich and EPFL (Switzerland), the University of Michigan, and Oliver Wyman. The Oxford partnership has produced 50+ papers and patents over 10+ years, including the Think-Reason-Learn family (GPTree, Random Rule Forest, Reasoned Rule Mining, Policy Induction), the VCBench benchmark, the SSFF multi-agent framework that became V (Vela's master agent), Founder-GPT, and the LLM-Augmented ML thread (LLM-AR, GPT-HTree, rare-event prediction, verifiable reasoning, cost-aware sequential evaluation).

Team · Vela Partners

The people who built Vela.

Venture capital is often told as the story of a single partner with taste. Vela is not that firm — the work, and the credit, belong to the many.

85 people live in the valley, in 4 houses. Knock on a door to meet them.

About the people who built Vela

Ex-Googlers

University of Oxford

Math Olympians

PhDs

Top Open-Source Contributors

Venture capital is often told as the story of a single partner with taste. Vela is not that firm. Every investment decision, every published paper, every product shipped, every model trained is the work of many people across San Francisco, New York, London, Oxford, Switzerland, Spain, Turkiye, Ghana, China, and Japan. Their names are in the valley above, because the work, and the credit, belongs to them.

50+

Papers & Patents

10+

Years of Research

100+

Contributors

Everyone in the valley, by house

Committees 7

Charlie Aaronson, LPAC & Venture Partner. Meta, Google. Oxford.
Chuck Bralver, LPAC. Co-founder of Oliver Wyman.
Eli Koen, Co-founder & Committee Member. UBP, Goldman Sachs.
Hasan Ugur Koyluoglu, LPAC & Quantitative Committee. Partner and Vice Chair, Oliver Wyman. Former professor. PhD, Princeton.
John Drzik, Quantitative Committee. Former President of Marsh & CEO of Oliver Wyman. PhD, Princeton.
Joseph Ternasky, Quantitative Committee. Engineering executive. Carta, Splunk, Google, Meta, Adobe, Microsoft, Apple.
Murat Ihlamur, Co-founder & Committee Member. Successful enterprise software entrepreneur, Netsis.

Advisors & Fellows 8

Alex Gonzalez, EiR & Advisor. Successful entrepreneur. Google. Oxford.
Beto, Fellow. CIO, San Diego Housing Commission.
Bob Van Winden, Executive Advisor. COO, Bridge (Stripe). Google.
Eoin Donohoe, Fellow. Anthropic, Stripe, Google.
Halit Erdogan, Fellow. Engineering leader, Google.
Jason Demant, Senior Advisor. GTM Fund, Foundation.
Kazuki Notsu, Senior Advisor. Founder and GP, GE Partners. Incubate Fund, Google, BCG.
Yagiz Ihlamur, Advisor. PHBench, Senior PM Amazon.

Core 8

Aaron Ontoyin Yin, Member of Technical Staff. Ghana Math Olympiad, GPTree, Think-Reason-Learn, models and sourcing.
Afriyie Kwesi Samuel, Member of Technical Staff. Top graduate. Entrepreneur OS, frontend intelligence.
Aikins Laryea, Member of Technical Staff. Top hacker. Agent fleets and agentic predictions.
Ben Griffin, Research Scientist. Oxford PhD, leading research. Random Rule Forest and Think-Reason-Learn.
Fuat Alican, Co-founder & General Partner. Netsis, Citi, Salomon Brothers. PhD, Universidad Latina.
Kelvin Amoaba, Member of Technical Staff. Top graduate. Architect of V and Taste model, leading infrastructure.
Yigit Ihlamur, Co-founder & General Partner. Google, Oxford.
Zakari Salifu, Member of Technical Staff. AI Master at Kaggle. Vela OS, large-scale data index and ML.

Researchers 62

Aarav Shrimanker, Oxford researcher. Multi-layer probabilistic pattern mining with adaptive confidence networks.
Abdullah Abid, Oxford researcher. Automated market segmentation with vector space clustering.
Aldair Petronilia, Oxford researcher. Foundations of founder prediction with EDA and ML.
Anirudh Jaidev Mahesh, Oxford researcher. Verifiable reasoning, LLM code generation.
Anna Bator, Oxford researcher. Performance of structured and reasoned features.
Anushka Suyal, Oxford researcher. Extended level segmentation.
Ashmit Rao, Oxford researcher. Disambiguating reasoned features with an option to pick an in-between decision.
Ayan Vijaypurkar, Oxford researcher. LLM-driven career growth analysis.
Bogdan Andrei Baban, Oxford researcher. Multi-ML model and sensitivity analysis.
Cagan Yanmaz, Oxford researcher. Co-investor modeling.
Chloe Chan, Oxford researcher. Impact of social interactions.
Chun Hin Ma, Oxford researcher. Description-driven predictions.
Diego Vidaurre Henche, Oxford researcher. Interpretable rule ensembles.
Eduard Oravkin, Oxford researcher. PageRank for investors.
Ethan Li, Oxford researcher. Alpha decay.
Grace Sodunke, Oxford researcher. Time-machine features.
Hao Li, Oxford researcher. LLM-based feature engineering.
Hengyu Wang, Oxford researcher. Naive Bayes model with ML.
Hristo Efimov, Oxford researcher. Knowledge graph agent.
Ian Cheung, Oxford researcher. SBERT-based similarity search.
Ipek Sahbazoglu, Oxford researcher. Knowledge graph with graph convolutional networks.
Jack Preuveneers, Oxford researcher. Oxford PhD, reasoned rule mining and portfolio construction.
Jimmy Rippin, Oxford researcher. Crunchbase-focused sourcing agent.
Jirko Rubruck, Oxford researcher. Temporal features.
Joel Beazley, Oxford researcher. Stability-aware integration of LLM-derived feature families.
Johnny Liang, Oxford researcher. Autoresearch on VCBench.
Jude Popham, Oxford researcher. Founder archetypes with Graph Neural Networks.
Julia Dabrowska, Oxford researcher. Market-focused reflective LLMs for idea prediction.
Julianna Piskorz, Oxford researcher. Investor similarities.
Junyan Wang, Oxford researcher. LLM-driven founding team synergies.
Kensei Sakamoto, Oxford researcher. Probabilistic modeling of venture capital portfolio outliers.
Leona Renard Kouame, Oxford researcher. Sourcing agent for YC.
Liren Song, Oxford researcher. Word2vec for the startup language.
Luka Secilmis, ETH Zurich & EPFL. BERT-based idea prediction.
Matthew Buckley, Oxford researcher. Idea clustering.
Maximilian Westermann, Oxford researcher. LLM-based feature discovery, CoFEE.
Mihir Kumar, Oxford researcher. Rare-event prediction, ensemble learning.
Mirsaid Abdullah, Oxford researcher. Integrating knowledge graphs, community detection, and linear models for outlier detection.
Moncef Slimani, Oxford researcher. Unsupervised explained ensemble clustering model for founder persona characterization.
Nathan Li, Oxford researcher. Optimal stop-loss.
Peiren Wang, Oxford researcher. Position sizing and autoresearch.
Prabhav Desai, Oxford researcher. Large founder model v0.
Raymond Zhao, Oxford researcher. Investor-focused SVM.
Rick Chen, Oxford researcher. Oxford PhD, AGI benchmarks focused on VCBench.
Sameer Singh, University of Michigan. Reasoning-based predictions.
Satyam Agarwal, Oxford researcher. Search engine-based sourcing agent.
Sichao Xiong, Oxford researcher. GPTree, LLM-powered decision trees.
Silei Zhu, Oxford researcher. Explainable classification via fine-tuned LLM embeddings.
Sinan Akcali, Oxford researcher. Word embeddings as feature generation.
Te Pei, Oxford researcher. Hierarchical clustering, founder personas.
Tom Marsden, Oxford researcher. Founder trajectory.
Xianling Mu, Oxford researcher. Policy induction, in-context learning.
Xingzhe Li, Oxford researcher. Incumbent priority identification for competition.
Xisen Wang, Oxford researcher. Multi-agent framework, SSFF.
Xun Hu, Oxford researcher. GNNs for startup prediction.
Yashkanwar Dadwal, Oxford researcher. Founder network score.
Yizhang Lou, Oxford researcher. Multi-agent VC.
Yuhang Ye, Oxford researcher. Oxford PhD, RL environments.
Yunqi Liang, Oxford researcher. Deal-level correlation, portfolio construction.
Yusuke Atsuta, Oxford researcher. BERT-powered automated market map.
Zejun Feng, Oxford researcher. Mirrored verification, multi-agent rating.
Zhaozhou Chen, Oxford researcher. Investor segmentation with graph-based modeling.