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# Name of the speaker | ||
name: Ondrej Biza | ||
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# Link to the speaker's webpage | ||
webpage: https://ondrejbiza.com/# | ||
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# Primary affiliation of the speaker | ||
affil: Northeastern Univeristy | ||
# Link to the speaker's primary affiliation | ||
affil_link: https://www.northeastern.edu/ | ||
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# An image of the speaker (square aspect ratio works the best) (place in the `assets/img/speakers` directory) | ||
img: ondrejbiza.png | ||
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# # (Optional) Secondary affiliation of the speaker | ||
# affil2: BuzzFizz Corp | ||
# # Link to the speaker's secondary affiliation | ||
# affil2_link: https://buzzfizz.corp | ||
--- | ||
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<!-- Whatever you write below will show up as the speaker's bio --> | ||
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__TBD__ |
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# Name of the speaker | ||
name: Aldo Pacchiano | ||
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# Link to the speaker's webpage | ||
webpage: https://www.aldopacchiano.ai/ | ||
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# Primary affiliation of the speaker | ||
affil: Broad Institute | ||
# Link to the speaker's primary affiliation | ||
affil_link: https://www.broadinstitute.org/ | ||
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# An image of the speaker (square aspect ratio works the best) (place in the `assets/img/speakers` directory) | ||
img: aldopacchiano.jpeg | ||
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# # (Optional) Secondary affiliation of the speaker | ||
# affil2: BuzzFizz Corp | ||
# # Link to the speaker's secondary affiliation | ||
# affil2_link: https://buzzfizz.corp | ||
--- | ||
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<!-- Whatever you write below will show up as the speaker's bio --> | ||
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Aldo Pacchiano is an Assistant Professor at the Boston University Center for Computing and Data Sciences and a Fellow at the Eric and Wendy Schmidt Center of the broad institute of MIT and Harvard. He obtained his PhD under the supervision of Profs. Michael Jordan and Peter Bartlett at UC Berkeley and was a Postdoctoral Researcher at Microsoft Research, NYC. His research lies in the areas of Reinforcement Learning, Online Learning, Bandits and Algorithmic Fairness. He is particularly interested in furthering our statistical understanding of learning phenomena in adaptive environments and use these theoretical insights and techniques to design efficient and safe algorithms for scientific, engineering, and large-scale societal applications. |
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