Virtual IDSS events, including online course start dates and webinars.

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Webinar: Your Pathway to a Master’s with MITx MicroMasters Program in SDS

online

Learn how you can leverage your online learning for academic credit at MIT, and our pathway schools. MIT is teaming up with several institutions to ensure you get the most out of your MITx MicroMasters® program credential in Statistics and Data Science (SDS). Find out which pathway works best for you in this webinar presented by: Teresa Taylor, Director of Business Operations, College of the Extended University, California State Polytechnic University, Pomona (USA) Prof. Erik Rolland, Dean of the College…

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SES & IDPS Dissertation Defense – Paolo Bertolotti

Paolo Bertolotti (IDSS)
E18-304

Inference and Diffusion in Networks ABSTRACT Networks provide a powerful and unified framework to study complex systems. By abstracting systems down to entities and their connections, network models provide insight into the structure and dynamics of critical systems across multiple domains. In this thesis, we study diffusion in social networks. Diffusion through networked systems corresponds to numerous consequential processes, and we focus on epidemic spread and information diffusion. We study these processes by applying and extending ideas from statistical inference.…

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2022 LIDS Student Conference

Zoom

The annual LIDS Student Conference is a student-organized, student-run conference that provides an opportunity for graduate students and postdocs to present their research to peers as well as to the community at large. This year, we are delighted to welcome four distinguished plenary speakers and accompanying student sessions in Machine Learning and Statistics; Information and Networks; Control Theory and Applications; Algorithms, Optimization, and Game Theory. This year's plenary speakers are: Yuejie Chi Professor in the Department of Electrical and Computer…

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2022 LIDS Student Conference

Zoom

The annual LIDS Student Conference is a student-organized, student-run conference that provides an opportunity for graduate students and postdocs to present their research to peers as well as to the community at large. This year, we are delighted to welcome four distinguished plenary speakers and accompanying student sessions in Machine Learning and Statistics; Information and Networks; Control Theory and Applications; Algorithms, Optimization, and Game Theory. This year's plenary speakers are: Yuejie Chi Professor in the Department of Electrical and Computer…

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WiDS Cambridge 2022

Online

WiDS Cambridge is a virtual one-day technical conference will feature an all-female line up of speakers from academia and industry to talk about the latest data science-related research in a number of domains.

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SES Dissertation Defense

Max Vilgalys (IDSS)
E18-304

Essays on Measuring Climate Change Damages and Adaptation ABSTRACT Through changes in average temperature, precipitation patterns, and extreme weather events, climate change is already causing severe ecological and economic damages. Further warming is expected to have a profound effect on the functioning of ecological and human systems worldwide. While it is a top priority to limit carbon emissions and mitigate future climate change, it is also essential to prepare for damages from climate change in the remainder of this century.…

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SES Dissertation Defense

Mengying "Mandy" Wu (IDSS)
online

Local official and polluter accountability in China’s environmental inspections ABSTRACT Poor environmental practices can lead to high levels of ambient pollution that damage human health and cause premature death. Even if environmental regulations are well designed, incomplete implementation at the local level carries high social costs. Although widely documented, solutions to inadequate enforcement have not been comprehensively studied. Here I use the setting of China’s environmental inspections to study what interventions effectively overcome the enforcement gap and reduce air pollution…

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SES Dissertation Defense

Yi "Alicia" Sun (IDSS)
32-D677

Algorithmic Fairness in Sequential Decision Making ABSTRACT Machine learning algorithms have been used on a wide range of applications, and there are growing concerns about potential biases of those algorithms. While many solutions have been proposed for addressing biases in predictions from an algorithm, there is still a gap in translating predictions to a justified decision. Moreover, even a justified and fair decision could lead to undesirable consequences with decisions create a feedback effect. While numerous solutions have been proposed…

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