Harvard University Department of Statistics

10/29/2024

We’re excited to announce that Preceptor Julie Vu will speak with the Harvard College Women’s Center on Wednesday, October 30th at 7 PM in Canaday Hall B (Lower Level)! Join us for an inspiring discussion on navigating identities in academic and professional spaces, female representation in STEM, and gender equity. Scan the QR code and save the date!

10/04/2024

Congrats t to Statistics PhD alum Louis Cammarata on receiving the 2025 Lawrence D. Brown PhD Student Award! 🏆 Cammarata was selected based on his work on dynamic network analysis with Prof. Tracy Ke: https://statistics.fas.harvard.edu/news/louis-cammarata-receives-2025-lawrence-d-brown-phd-student-award-0

09/23/2024

🎉 Congratulations to Prof. Susan Murphy on receiving the 2024 Mosteller Statistician of the Year Award! 🏆✨ We celebrated her achievements with students, postdocs, and colleagues at a special BCASA reception. Read more in the BCASA's newsletter: https://sway.cloud.microsoft/kHlKB41elOp5CxoK?ref=Link

09/10/2024

Hosted by Harvard Stats, CS & Applied Math, our Women in Tech & AI Career Panel featured Stella Biderman, Executive Director of Eleuther AI, & Ashley Mae Conard, Sr. Researcher at Microsoft Research Health Futures. What an empowering event! https://statistics.fas.harvard.edu/news/statistics-department-hosts-women-tech-and-ai-career-panel

09/05/2024

Read “HEDE: Heritability estimation in high dimensions by Ensembling Debiased Estimators" by Yanke Song, Xihong Lin, and Pragya Sur. They develop a new method for estimating heritability or signal-to-noise ratio in challenging high-dimensional scenarios, with applications to statistical genetics:

Estimating heritability remains a significant challenge in statistical genetics. Diverse approaches have emerged over the years that are broadly categorized as either random effects or fixed effects heritability methods. In this work, we focus on the latter. We propose HEDE, an ensemble approach to....

08/29/2024

Congrats to Kevin Luo, Yufan Li, and Pragya Sur on their paper “ROTI-GCV: Generalized Cross-Validation for right-ROTationally Invariant Data." They introduce ROTI-GCV, a new framework for cross-validation under sample dependence and heavy-tailed covariates:

Two key tasks in high-dimensional regularized regression are tuning the regularization strength for good predictions and estimating the out-of-sample risk. It is known that the standard approach -- $k$-fold cross-validation -- is inconsistent in modern high-dimensional settings. While leave-one-out....

08/28/2024

Tune into the Stats and Stories podcast to explore how Bayesian methods are impacting the environmental landscape. The podcast features Noel Cressie, Distinguished Professor at the University of Wollongong, Australia, and Director of its Centre for Environmental Informatics:

Would you be surprised if a wombat won a statistical achievement award? well our guest Noel Cressie is here to talk about the WOllongong Methodology for Bayesian Assimilation of Trace-gases and how it can impact the environmental landscape.

08/27/2024

To all literature & stats fans, how similar is stats analysis to close readings? Take a look at responses in Statistical Modeling, Causal Inference, and Social Science blog by Stats PhD Alum Prof. Andrew Gelman: https://statmodeling.stat.columbia.edu/2024/08/14/close-reading-in-literary-criticism-and-statistical-analysis/.

Close reading in literary criticism and statistical analysis Posted on August 14, 2024 9:14 AM by Andrew I happened to come across this comment from Jrc a few years back: A lot of your posts about journalism and writing are almost like literary criticism – close reading for context, picking out pa...

08/26/2024

For the last meeting, our Data & Society Book Club enjoyed the outdoors while discussing The Harvard Data Science Review's Special Issue 5 "Future Shock: Grappling With the Generative AI Revolution." Sponsored by the Stats Department, the book club was co-led by Julie Vu and Emily Palmer and included participants from across the Harvard campus. During this last meeting, we shared our insights and reactions to problems associated with GenAI - thanks for a lively discussion!

08/23/2024

Thank you, Harvard Data Science Review, for your insightful article on "Is Chat GPT More Biased Than You?" The article examines the bias in LLMs and explores how to reduce this bias. Read more here:

AI is changing the world in ways that are difficult to forecast, but the impact will surely be enormous. Large language models (LLMs) are the most recent AI system that has captured the public eye. The rise of AI and LLMs offers efficiency and assistance, but raises questions of job loss, fairness,....

08/22/2024

Read "Predictive Inference in Multi-environment Scenarios" by John C. Duchi, Suyash Gupta, Kuanhao Jiang and Pragya Sur, which addresses the challenge of constructing valid confidence intervals in problems of prediction across multiple environments:

We address the challenge of constructing valid confidence intervals and sets in problems of prediction across multiple environments. We investigate two types of coverage suitable for these problems, extending the jackknife and split-conformal methods to show how to obtain distribution-free coverage....

08/21/2024

Congrats to Cory McCartan, Chris Kenny, Tyler Simko, Emma Ebowe, Michael Y. Zhao, and Kosuke Imai on their new working paper "Redistricting Reforms Reduce Gerrymandering by Constraining Partisan Actors"! https://alarm-redist.org/posts/2024-07-25-redistricting-reforms/

08/20/2024

Check out "Statistics Behind the Headlines" audiobook from the Stats and Stories podcast in which John Bailer and Rosemary Pennington provide a "roadmap to statistical literacy and a data self-defense course"!

Listen to full audiobook of The Statistics Behind the Headlines with John Bailer and Rosemary Pennington.

08/19/2024

Take a look at the Institute of Mathematical Statistics (IMS) August Bulletin, which features the 2024 Gottfried E. Noether Early Career Scholar Award presentations by Edgar Dobriban, Associate Professor of Statistics and Data Science at Wharton, and Lucas Janson, Associate Professor in the Harvard Statistics Department:

08/16/2024

Congratulations to Yanke Song, Sohom Bhattacharya, and Pragya Sur on their new paper, “Generalization error of min-norm interpolators in transfer learning”. They develop a new framework for quantifying the generalization error of min-norm interpolators under transfer learning: https://arxiv.org/abs/2406.13944.

08/05/2024

Congrats to Huang, Austern & Orbanz on "Gaussian Universality for Approximately Polynomial Functions of High-dimensional Data." They establish an invariance principle for polynomial functions of n independent high-dimensional random vectors: https://arxiv.org/abs/2403.10711

07/30/2024

Suqi Liu and Morgane Austern characterize the performance of graph neural networks for graph alignment problems in the presence of vertex feature information in a recent paper: https://arxiv.org/abs/2402.07340

07/30/2024

“Future Shock: Grappling With the Generative AI Revolution,” a special issue of the Harvard Data Science Review, explores societal consequences of rapid AI advances. Related articles will appear through 11/30 (the 2nd anniversary of ChatGPT). Read Xiao-Li Meng & David Leslie's intro:

In the jarring opening scene of the 1972 documentary Future Shock, a film directed by Alexander Grasshoff and based on the classic study by sociologist and futurist Alvin Toffler (1970), the blurred silhouettes of a man and woman walk side by side down a serene country road. As the two figures amble...