Center for Statistics and Machine Learning, Princeton University

"In what other setting can students and professors relive their childhoods, share future plans, and explore the world that revolves around Taylor Swift!" said Day Yi, lecturer at the Center for Statistics and Machine Learning.

On April 19th, the center hosted undergraduate students and some of their favorite faculty members for the annual Dinner with a Professor event. Students enrolled in the SML minor program were welcomed to invite faculty from any department on campus as their guest for the meal. The relaxed environment of the event instigated conversations that moved beyond the typical academic exchanges of lectures and office hours.

Dinner with a Professor is just one way CSML works to foster and celebrate the cross-campus reach of machine learning at Princeton.

Read the full story now:

Students and faculty from across campus enjoy annual Dinner with a Professor event On April 19th, the Center for Statistics and Machine Learning hosted undergraduate students and their favorite faculty members for the center’s annual Dinner with a Professor event. This year, the invited students and faculty got together over a 4-course meal at the Princeton restaurant Mistral to...

Research code is sometimes years old or written in outdated programming languages. So, how can academics take code that is messy or obscure or both and make it reproducible and sustainable? At the Center for Statistics and Machine Learning, Princeton University, research software engineers Anushka Acharya and Vineet Bansal are here to help. Acharya and Bansal take code used by Princeton University faculty for research projects and optimize it — pushing forward machine learning on campus.

“I’ve never really been at an institution before that had anything quite like the research software engineer program,” said Assistant Professor, Lewis-Sigler Institute for Integrative Genomics Michael Skinnider, who’s been collaborating with the CSML RSEs since fall. “It’s been a fantastic experience.”

“Vineet definitely made my code more legible and also made it into a package so that it can be installed,” said Assistant Professor at Princeton Engineering Christine Allen-Blanchette who's been working with the CSML RSEs since fall.

Read the full story now:

Software engineers optimize code to accelerate machine learning research at Princeton Across the Princeton campus, a diffuse group of research software engineers are tackling the challenge of making research code reproducible and sustainable head-on. Stationed across departments, the RSEs — as they’re referred to in shorthand — work to support computational research projects ru...

With artificial intelligence becoming ingrained in our everyday lives and AI mishaps often making the news, “We need to do our homework and ensure we provide the public the guarantees and assurances that are necessary to deploy the technology,” said Princeton University Assistant Professor of Electrical and Computer Engineering Jaime Fernández Fisac.

Last week, Fernández Fisac stopped by the Center for Statistics and Machine Learning, to discuss the ways in which he and his colleagues at the Safe Robotics Laboratory are working toward ensuring safety in human-AI interactions. Read the full story:

As the space between robots and humans blurs, how do we keep the interactions safe? The AI boom brings with it opportunities for great benefits — but risks for individual and societal harm are inevitable as well. In a seminar hosted by the Center for Statistics and Machine Learning, Assistant Professor Jaime Fernández Fisac shared some of the ways he and his colleagues at the Sa...

"Machine learning is transforming the way we do research all over the Princeton University campus," says Tom Griffiths, Professor of Psychology and Computer Science and Director of the Center for Statistics and Machine Learning, Princeton University

For last month's Wintersession, CSML hosted a workshop exploring the ways that Princeton researchers are utilizing artificial as a tool to enhance their work. Now on the website, read about the workshop and the ways that is an aid for discovery on campus:

Across campus, Princeton researchers use machine learning to aid discovery How does a researcher make sense of the data they collect over the course of what might be years of conducting experiments? They could have to comb through masses of data looking for patterns or they might want to predict unknown information using what they do have. Increasingly, machine learning is...

Next week, the Center for Statistics and Machine Learning is hosting a Wintersession workshop on and its usefulness in faculty, postdoc, and student research.

Spots went fast, but get on the wait list now, as availability is expected to open up for interested parties: https://winter.princeton.edu/register/

As a part of Princeton's Schmidt DataX initiative, scientist Julian Gold is taking his background in pure mathematics and applying it to create tools that will help biologists better understand cell and tissue growth.

“Going from probability theory to computational biology may seem like a major leap,” said Gold, who started at Princeton in the spring semester of 2023. “Probability theory is a toolkit for studying randomness, and for handling incomplete information."

Read more about Gold and his work:

DataX – Julian Gold: making the leap from pure mathematics to computational biology Julian Gold had spent most of his academic research career in the world of pure mathematics. As a researcher, Gold used probability theory, an area of mathematics concerned with studying chance events or random phenomena. In particular, he focused on understanding the properties of mathematical obje...

Happy Holidays from the Center for Statistics and Machine Learning!

Wishing you all merry days, decked halls, and a festive time with family and friends ❄️

An afternoon of sweet treats and even sweeter furry friends 🐶❤️

Students dropped by the center yesterday to enjoy bubble tea and therapy dogs as a part of our end-of-semester Barks, Bubbles, and Brownies event.

Special thank you to good boys and girls Tashi, Bobka, Aspen, Lacy, Tony, and Clancy for making it a paw-some day!

After wrapping up a successful semester, our graduate research seminar students were treated to a celebratory lunch – and goody bags!

“SML510 is a great venue to hear and share research with peers,” said Jamie Chin Chiu, PhD candidate in psychology and neuroscience. “Not only do we get ample time to dig deep into methodology and get to ask technical questions about analyses, but you also get to practice explaining your research to peers who are outside of your domain since the cohort comes from a good mix of disciplines!”

Gili Karni, PhD candidate in neuroscience, said the course was both “lots of fun” and academically stimulating. “My favorite part about the seminar was the opportunity to engage in rigorous conversations exploring different applications of statistics with a diverse group of students,” said Karni. “It was a valuable experience that expanded my knowledge and broadened my perspective.”

SML 510 is open to students enrolled in the Graduate Certificate Program in Statistics and Machine Learning. For more information on the course: https://bit.ly/3uU4f8g

CSML at Princeton University seeks applications from outstanding professional instructors to join our faculty in creating/teaching exciting undergraduate data science, statistics, and machine learning courses.

Lecturer Position Available at CSML The Center for Statistics and Machine Learning at Princeton University seeks applications from outstanding professional instructors to join our faculty in creating and teaching exciting undergraduate data science, statistics, and machine learning courses. Depending on the applicant's background and....

CSML leadership is pleased to announce the very popular certificate program in statistics and machine learning has been converted to a Princeton University minor.
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