Aldo Pacchiano Camacho

Aldo Pacchiano is an Assistant Professor at Boston University's Faculty of Computing & Data Sciences and a Visiting Scientist at the Schmidt Center of the Broad Institute of MIT and Harvard. Originally from Mexico City, he earned his PhD in Computer Science at UC Berkeley under Peter Bartlett and Michael Jordan, and was a postdoctoral researcher at Microsoft Research NYC. His research leverages sequential decision-making to design adaptive AI systems, focused on reinforcement learning, bandits, online learning, and algorithmic fairness, with an emphasis on autonomous scientific discovery. Before BU he spent a year at the Broad Institute, and he represented Mexico at the International Mathematical Olympiad in 2006, 2007, and 2008.

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• Represented Mexico at IMO 2006 (Honorable Mention), 2007 (Bronze) and 2008 (Silver): the elite olympiad pipeline that fed his MIT/Cambridge/Berkeley research path.2008
• Postdoc at Microsoft Research NYC (2021-2023), then a one-year appointment at the Broad Institute of MIT and Harvard, then Assistant Professor at BU CDS in 2024 - rapid progression from industry postdoc to faculty.2024
• PhD in Computer Science at UC Berkeley (2021), thesis 'Model Selection for Contextual Bandits and Reinforcement Learning', advised by Peter Bartlett and Michael Jordan.2021
• Leads the Pacchiano Lab for Adaptive and Intelligent Algorithms (PLAIA), a BU CDS group focused on sequential decision making, RL, bandits and experiment design.2026
• Public CV email [contact omitted] (his MSR tenure contact).2023
• Toured industrial research before academia: visiting researcher at FAIR, DeepMind London, Google Research, Google Brain, plus MSR internships (2018-2021).2021
• From Mexico City, and the only named BU CDS faculty explicitly tied to a Mexico City origin - a Mexico-to-MIT-to-Berkeley-to-BU trajectory.2024
• Writes short fiction and notes in English and Spanish on a separate literary site, distinct from the research persona.2026