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  • About me - Bryan Wilder
    Bryan Wilder bwilder@cmu edu Follow Twitter; Github; Google Scholar; About me I am an Assistant Professor in the Machine Learning Department at Carnegie Mellon University My research focuses on AI for equitable, data-driven decision making in high-stakes social settings, integrating methods from machine learning, optimization, and causal
  • BRYAN WILDER
    Bryan Wilder, Laura Onasch-Vera, Graham Diguiseppi, Robin Petering Chyna Hill, Amulya Yadav, Eric Rice, Milind Tambe Clinical trial of an AI-augmented intervention for HIV prevention
  • Publications - Bryan Wilder
    Bryan Wilder, Laura Onasch-Vera, Graham Diguiseppi, Robin Petering Chyna Hill, Amulya Yadav, Eric Rice, Milind Tambe Clinical trial of an AI-augmented intervention for HIV prevention in youth experiencing homelessness
  • CMU Lab for AI and Social Impact - Bryan Wilder
    Bryan Wilder bwilder@cmu edu Follow Twitter; Github; Google Scholar; CMU Lab for AI and Social Impact PhD Students Ye Won (Emily) Byun (co-advised with Zachary Lipton) Santiago Cortes Gomez; Ruiqi Lyu (co-advised with Roni Rosenfeld) Ananya Joshi (co-advised with Roni Rosenfeld)
  • Equilibrium effects of LLM reviewing - Bryan Wilder
    Bryan Wilder bwilder@cmu edu Follow Twitter; Github; Google Scholar; Equilibrium effects of LLM reviewing LLMs have been proposed as an aid to the process of scientific peer review I argue that (a) different ways of using LLMs in review can have very different consequences and that (b) to reason about these consequences, it crucial to
  • BRYAN WILDER
    Bryan Wilder, Laura Onasch-Vera, Graham Diguiseppi, Robin Petering Chyna Hill, Amulya Yadav, Eric Rice, Milind Tambe Clinical trial of an AI-augmented intervention for HIV prevention
  • Uncharted but not Uninfluenced: Influence Maximization with an Uncertain . . .
    Bryan Wilder1, Amulya Yadav1, Nicole Immorlica2, Eric Rice1, Milind Tambe1 1 Center for AI in Society, University of Southern California 2 Microsoft Research, New England {bwilder, amulyaya, ericr, tambe}@usc edu nicimm@gmail com ABSTRACT This paper focuses on new challenges in influence maximization
  • End-to-End Influence Maximization in the Field - Bryan Wilder
    selecting influential peer leaders Subsequently, Wilder et al [25] introduced the DOSIM algorithm which accounts for uncertainty about the true probability of influence propagation using a robust optimization approach We note that our approach to parameter ro-bustness is similar to techniques used in robust MDP planning [14],
  • Teaching - Bryan Wilder
    Bryan Wilder bwilder@cmu edu Follow Twitter; Github; Google Scholar; Teaching Spring 2023: Machine Learning in Practice (10-718) Fall 2023: Mathematics for Machine Learning (10-606) and Computation for Machine Learning (10-607) Fall 2024: Mathematics for Machine Learning (10-606) Computation for Machine Learning (10-607) and Machine Learning in Practice (10-718)
  • Optimizing network structure for preventative health - Bryan Wilder
    Bryan Wilder, Han Ching Ou, Kayla de la Haye, Milind Tambe Center for Artificial Intelligence in Society University of Southern California {bwilder,hanchino,delahaye,tambe}@usc edu ABSTRACT Diseases such as heart disease, stroke, or diabetes affect hundreds of millions of people Such conditions are strongly impacted by obesity,





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