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Alexandre Drouin

Head of Frontier AI Research

ServiceNow

Biography

Welcome to my page!

I’m a Principal Research Scientist at ServiceNow Research in Montreal and an Adjunct Professor of Computer Science at Laval University and Mila. I lead ServiceNow’s Frontier AI Research team , where we explore the key capabilities needed for enterprise AI, such as data analytics, computer-use agents, and decision-making systems, as well as the key barriers that limit their adoption, including trustworthiness, security, long-horizon execution, and the challenge of reliably measuring progress through rigorous benchmarking.

More recently, my research has focused on decision making under uncertainty, spanning causal discovery, time series forecasting, and the development of foundation models for these domains. This work has increasingly converged on a central theme: automating decision making through reliable enterprise agents capable of reasoning, acting, and adapting in complex environments.

In the past, I developed machine learning algorithms for biomarker discovery in large genomic datasets, with a particular focus on the global problem of antibiotic resistance. I obtained my Ph.D. in Computer Science in 2019 under the supervision of François Laviolette.

Interests

  • Machine learning
  • Decision-making (causal inference, forecasting)
  • AI Agents
  • Benchmarking

Education

  • PhD in Artificial Intelligence, 2019

    Laval University

  • MSc in Artificial Intelligence, 2014

    Laval University

  • BSc in Computer Science, 2012

    Laval University

Talks

Full Stack Benchmarking for Knowledge Work

In less than a year, AI agents have evolved from a research curiosity into the foundation of some of the largest software platform …

LLM Agents From Fundamentals to Real-World Applications

This lecture introduces the core principles behind LLM-based AI agents, demonstrates how they can create real-world impact across a …

Multivariate probabilistic time series forecasting: transformer-based copulas and the limitations of proper scoring rules

Accurate estimation of time-varying quantities is crucial for effective decision-making across various domains, including healthcare …

Apprentissage automatique et raisonnement causal - Au delà des corrélations

La recherche en apprentissage automatique a rendu possibles d’époustouflantes avancées en intelligence artificielle. Un avenir où un …

Mind the structure: an introduction to causal inference for machine learning

Machine learning algorithms excel at discovering statistical dependency patterns in data. Those can be exploited to produce extremely …

Current students

Graduate Students

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Arjun Ashok

PhD Student

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Léo Boisvert

PhD Student

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Thibaud Godon

PhD Student