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August 25, 2022Graduate Student OrientationLocation: TEP 1403 (Tepper)
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Morning ScheduleSpeaker
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9:00 AMBreakfast
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9:30 AMWelcome to the School of Computer ScienceMartial Hebert
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9:45 AMWelcome to the Machine Learning DepartmentRoni Rosenfeld
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10:00 AMProgram Requirements: Separate talk for MS & PhD students(MS) Katerina Fragkiadaki (TEP 1403)(PhD) Tom Mitchell (TEP 1409)
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10:45 AMBreak
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Faculty Research Talk TitleSpeakerResearch AreaFaculty WebpageLooking for # PhD StudentsLooking for # MS Students
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11:00 AMA Human-centered Agenda for MLHoda HeidariFairness, Explainability, & Accountability for MLhttps://www.cs.cmu.edu/~hheidari/1-22-3
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11:20 AMEpidemiological ForecastingRoni Rosenfeld and Bryan Wilder
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11:40 AMReinforcement Learning for Nuclear Fusion and Self-Driving CarsJeff SchneiderRL, active optimization, multi-agent learning and coordinationwww.cs.cmu.edu/~schneide1-21-2
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Afternoon Schedule
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12:00 PMLunch
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1:00 PMEvaluating and Adapting to Distribution ShiftZico KolterDeep Learninghttp://zicokolter.com1-20-1
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1:20 PMStructured Prediction for Natural Language ProcessingMatt GormleyML for NLP
http://www.cs.cmu.edu/~mgormley/
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1:40 PMFoundations of Machine Learning and its influence on other areasNina BalcanFoundations of ML, Computational Economics, Algorithmshttp://www.cs.cmu.edu/~ninamf/21
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2:00 PMEmbodied Common Sense LearningKaterina FragkiadakiDeep Learning, Computer Vision, Language Grounding, Roboticshttps://www.cs.cmu.edu/~katef/0-20-1
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2:20 PMBreak
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2:40 PMML for the Real-World ImpactArtur Dubrawski
healthcare, security, trustworthy ML, efficient learning from limited information, ML respectful of common sense and first principles
www.autonlab.org3-40
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3:00 PMMachine learning and systemsTianqi ChenMachine learning and systemstqchen.com0-10-1
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3:20 PMML for understanding our body: from cell to tissueJian MaML for biomedicinehttps://www.cs.cmu.edu/~jianma/11
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August 26, 2022Graduate Student OrientationLocation: TEP 1403 (Tepper)
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Morning Schedule
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9:00 AMBreakfast
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Faculty Research Talk TitleSpeakerResearch AreaFaculty WebpageLooking for # PhD StudentsLooking for # MS Students
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9:30 AMPrivacy, Fairness, and Incentives in MLSteven Wu(differential) privacy, game theory, algorithmic fairnesshttps://zstevenwu.com/
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9:50 AMSequential Decision Making: Theory and ApplicationsAarti Singhhttps://www.cs.cmu.edu/~aarti/21
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10:10 AMML for high-stakes social decisionsBryan Wilderhttps://bryanwilder.github.io/1-2
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10:30 AMThird Wave AI: Incorporating Domain KnowledgePradeep Ravikumar
https://www.cs.cmu.edu/~pradeepr/
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10:50 AMBreak
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11:05 AMLearning from people: Fairness, Accuracy and RobustnessNihar Shahhttps://cs.cmu.edu/~nihars10
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11:25 AMFoundations of Cooperative AIVincent Conitzergame theoryhttps://www.cs.cmu.edu/~conitzer/1+0.1
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11:45 AMNeural Reinforcement Learning for Combinatorial OptimizationYiming Yanghttp://www.cs.cmu.edu/~yiming/10
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Afternoon Schedule
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12:00 PMLunch
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1:00 PMGSA Presentation
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1:20 PMML-Informed decision-making for fair and equitable outcomesRayid Ghaniml for social good, public policy, fairness, explainabilityrayidghani.com11-2
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1:40 PMTBAAndrej RisteskiTheory of generative models, out-of-distribution generalization, ML for science
https://www.andrew.cmu.edu/user/aristesk/
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2:00 PMTowards Continually Improving AgentsDeepak PathakDeep Learning, Robot Learning, Computer Vision, RLhttps://www.cs.cmu.edu/~dpathak/12
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2:20 PMBreak
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2:40 PMReliable machine learning in the wildAditi Raghunathandeep learning, robustnesshttps://www.cs.cmu.edu/~aditirag/
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3:00 PMIntro to SCS Computing
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3:20 PMGame-theoretic statistics, and distribution-free UQAaditya Ramdassequential inference, UQ for ML, theoretical stats
https://www.stat.cmu.edu/~aramdas/
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3:40 PMZack Lipton
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