Academic Background
Dr. Amir Sani completed his PhD in Machine Learning for Decision Making Under Uncertainty under the supervision of Rémi Munos and Alessandro Lazaric as part of the SequeL team at INRIA-Lille Nord Europe.
Research Fellowships
- With Rama Cont at:
- With Andrea Roventini at the Institute of Economics at Scuola Superiore Sant'Anna Pisa, as a member of the EU Horizons 2020 Future and Emerging Technologies ISIGrowth project
- With Antoine Mandel at the Centre d'Économie de la Sorbonne in Université Paris 1, Panthéon-Sorbonne, as a member of the EU Horizons 2020 Future and Emerging Technologies DOLFINS project
Publications
Agent-Based Model Calibration using Machine Learning Surrogates
With Francesco Lamperti and Andrea Roventini, Journal of Economic Dynamics and Control
The Replacement Bootstrap for Dependent Data
With Alessandro Lazaric and Daniil Ryabko, ISIT 2015
Exploiting easy data in online optimization
With Gergely Neu and Alessandro Lazaric, NIPS 2014
Risk-aversion in multi-armed bandits
With Alessandro Lazaric and Rémi Munos, NIPS 2012
Selected Talks
June 30th, 2018
Agent-Based Model Calibration, Workshop on Economics with Heterogeneous Interacting Agents, Tokyo, Japan
June 19th, 2018
Agent-Based Model Calibration, Invited Session on "Validation of Agent-Based Models", Computing in Economics and Finance, Milan, Italy
May 31st, 2018
Agent-Based Model Calibration using Machine Learning Surrogates, CFM-Imperial ENS Workshop on Machine Learning and Quantitative Finance 2018, London, England
Workshop Papers/Posters
- Inferring Complex Networks of Influence: Understanding Green Investment Tipping Points, with Antoine Mandel, NIPS Workshop on Inference and Learning of Hypothetical and Counterfactual Interventions in Complex Systems, 2016
- Macroeconomic Agent Based Model Calibration using Iterated Surrogates, with Francesco Lamperti, Antoine Mandel and Andrea Roventini, NIPS Workshop on Inference and Learning of Hypothetical and Counterfactual Interventions in Complex Systems, 2016
- Information Theoretic Bootstrapping for Dependent Time Series, with Alessandro Lazaric and Daniil Ryabko, NIPS Workshop on Modern Nonparametric Methods in Machine Learning, 2013
Notable Events
June 24-26, 2019: Sponsor, Workshop on Economic Science with Heterogeneous Interacting Agents (WEHIA 2019)
June 24-26, 2019: Co-Organiser, WEHIA 2019 Roundtables
June 27, 2019: Organiser, Simudyne Calibration Hackathon @ WEHIA 2019
Academic Visits
February 2017: Einaudi Institute for Economics and Finance, Rome, Italy
January 23-27, 2017: Monash Business School Department of Econometrics and Business Statistics
January 10-11, 2017: University of Zurich, Department of Banking and Finance, Zurich, Switzerland
February-September 2017: CFM-Imperial Institute of Quantitative Finance, London, United Kingdom
September 25-30, 2016: Institute of Economics - Scuola Superiore Sant'Anna, Pisa, Italy
September 16, 2016: Alan Turing Institute, London, England
April 17-24, 2016: Institute of Economics - Scuola Superiore Sant'Anna, Pisa, Italy
February 5, 2016: Center for Data Science Paris-Saclay, Saclay, France
Teaching Experience
February-March, 2017: Statistics and Business Analytics, MBA Program, HEC Paris
January 5th, 2017 through February 16th, 2017: Machine Learning for Economics and Finance, University of Paris II Assas, Ingénierie Statistique Financière
February 4th, 2016 through March 3rd, 2016: Machine Learning for Economics and Finance II, University of Paris II Assas, Ingénierie Statistique Financière
December 3rd, 2015 through January 14th, 2016: Machine Learning for Economics and Finance I, University of Paris II Assas, Ingénierie Statistique Financière
Professional Experience
AdapData
Consultant - AI | Process Automation
February 2024 - Present
- Specialized consulting focused on alternative data generation, signalling, and commercial value creation.
- Provide deep expertise in machine learning, complex systems modeling, and quantitative finance.
- Architect, deliver and maintain bespoke signaling systems for value creation as APIs.
Scuola Superiore Sant'Anna
Professional Affiliate
September 2022 - Present
External Research Fellow
October 2017 - September 2022
Research Fellow
June 2017 - October 2017
- Conducted research on agent-based model calibration using Machine Learning Surrogates.
- Focused on quantitative decision-making in macroeconomic modeling, complex systems, network modeling, and ESG impact assessment.
Techstars
Senior Vice President of Fund & Investment Analytics
September 2022 - February 2024
- Leveraged quantitative decision-making techniques and AI-driven analytics for fund follow-on and exit management strategy.
- Implemented data-driven processes to enhance investment thesis development, portfolio management, and value creation initiatives.
- Advised on data-driven initiatives and "alpha" generation across business lines.
EY
Partner
July 2022 - August 2022
Associate Partner
March 2022 - June 2022
- Architected a UK-wide private equity intelligence platform built on alternative and proprietary data sources.
- Leveraged language modeling, NLP, and advanced data processing techniques for operational efficiency and strategic insights.
13books Capital
Chief Technology Officer
January 2020 - November 2021
- Developed and deployed machine learning models for sourcing, screening, benchmarking, and tracking fintech startups.
- Implemented data aggregation/cleaning/engineering ETL based on licensed and alternative sources.
- Designed recommender systems and conducted investor fund flow analysis and network modeling.
Education
- INRIA & University of Lille 1
Doctor of Philosophy (Ph.D.), Machine Learning (2011 - 2015) - University College London, U. of London
MSc, Machine Learning (2010 - 2011) - The Australian National University
MSc, Information Technology (2009 - 2010) - University of San Diego School of Law
Certificate, Law (2005) - University of California, San Diego
BA, Philosophy (1997 - 2001)
Contact Information
London, England
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