I School Lectures

Who should make decisions about ethical and responsible technology deployments? And how do impacted communities make political claims over data technologies?

When identifying organ transplant recipients — and in other matching problems — is it better to find a match more quickly, or more slowly and carefully? Afshin Nikzad’s research weighs the tradeoffs in different circumstances.

Can we combine data from satellites, mobile phones, and financial services providers with machine learning to identify the neediest people and better target humanitarian aid?

Timothy Tangherlini uses a computational folkloristic approach to analyze conversations on the social media platform Parler leading up to the January 6th attack on the Capitol.

Jevin West breaks down the threats of scientific disinformation, predatory publishing and pseudoscience, the reproducability crisis, and generative AI.

Narges Mahyar discusses community-centered tools that empower the general public to engage in real-world sociotechnical problems.

Diag Davenport outlines an unexpected pattern of bias underlying officers’ choices to use or not use an algorithmic risk score.

Analyses of police misconduct rely heavily on self-reported law-enforcement data. Dean Knox proposes a research algorithm to deal with unreliable and distorted data.

Alex Chohlas-Wood demonstrates two ways that data science and information technology can improve outcomes in the criminal legal system.

Jennifer Allen estimates how much curbing misinformation could benefit public health.

Cornelia Ilin gives a high-level introduction to the transformer model architecture, using bidirectional representations from transformers (BERT) on electronic medical health records to predict pediatric patients’ diagnosis codes.

Ali Montazeralghaem researches recommender systems, deep learning and reinforcement learning methods, and natural language processing.

The creator of open-source projects FinRL, ElegantRL, and FinGPT outlines the deep learning revolution and his experiences applying it to the challenging domain of the financial market.

Arvind Satyanarayan explores the future of human/machine partnerships.

Nina Beguš will introduce “artificial humanities,” an approach that integrates the study of humanities into the creation of technologies

How the definition, production, and leveraging of information are shaped by caste, class, and gender, and the implications for development.

Behind the census’s neat grid of numbers is a collage of messy, human stories — you just have to know how to read them.

Bryan Pardo discusses his lab’s work bridging the gap between digital audio software interfaces and the musicians, podcasters, and sound artists who use the tools.

Dr. Doris Lee presents her dissertation research enabling data analysts to identify trends and patterns, generate and verify hypotheses, and detect outliers and anomalies.

Richmond Wong presents his dissertation researchon the relationships between design practices and social values.