To See Like a Human: The Quest After Aristotle's Holy Grail
Nov. 1, 2021
Written by Taylor Beck
What interests a group of cognitive scientists at Princeton is how we learn the categories that structure our minds. Their goal is to map these conceptual terrains using machines.
Students take a plunge into a special theoretical deep learning workshop with instructors from academia and big tech companies
Oct. 29, 2021
Written by Sharon Adarlo

As machine learning gains traction in research and industry, one subfield, deep learning, has emerged as a hot area of interest due to rapid development and research, according to Boris Hanin, an assistant professor in Princeton University’s Department of Operations Research and Financial Engineering.

Scientists pinpoint the genes for tuskless African elephants, which have evolved under intense poaching pressure
Oct. 21, 2021
Written by Sharon Adarlo

In certain regions of Africa wracked by heavy poaching, people have observed an increased incidence of African elephants without their iconic white tusks, which are prized in the multibillion-dollar wildlife black market. But there has been no direct genetic evidence indicating how this was happening or why this trait…

CSML Internship Program Provides Students Valuable Research Opportunities
Oct. 13, 2021
Written by Sharon Adarlo

Within a specially-made box in a lab on the campus of Princeton University, several fuzzy bumblebees (Bombus impatiens) flew through the air while a camera sat over the enclosure, watching and recording every moment. What made these bees distinct, besides their artificially constructed habitat, was that these insects…

Michael Hu: studying the connections between machine learning and communications
Sept. 29, 2021
In both his independent work and his development as a software engineer, the CSML certificate has been particularly helpful, said Michael Hu. It not only enabled him to connect to a community of like-minded scholars, but it also gave him opportunities to explore machine learning more deeply.
CSML, PICSciE and DataX help researchers launch new cancer analysis software
Sept. 22, 2021

To probe the origin and spread of cancers in the human body more effectively, Ben Raphael, professor of computer science at Princeton University, and his research lab created HATCHet or Holistic Allele-specific Tumor Copy-number Heterogeneity, an algorithm that is capable of…

NSF awards team that includes Princeton, CSML researchers $5M to model water resources using machine learning
Sept. 20, 2021
As extreme weather events such as flooding and drought become more common in a climate impacted by humans, the ability to understand and predict water resources and systems is becoming more important than ever. To that end, a team of Princeton University and University of Arizona researchers has received a $5 million grant from the National Science Foundation (NSF) for the HydroGEN (Hydrologic Scenario Generation) project, which will use machine learning and artificial intelligence to develop simulated models of the nation’s watershed systems.
Nick McGreivy: working at the intersection of machine learning and plasma physics
Sept. 15, 2021
Nick McGreivy is interested using machine learning as a tool to accelerate the computational simulation of partial differential equations in plasma physics. “Plasma physicists have spent a lot of time and effort developing equations that describe the behavior of plasma within a nuclear fusion reactor,” said McGreivy. “One problem that I am working on is that often those equations take a really long time to solve. The goal is to speed that process up dramatically, maybe even by a couple of orders of magnitude, through a clever application of machine learning. And then that will allow us to test much more quickly and a much wider range of different possible scenarios, which would be useful for the optimization of future fusion reactors.”
Christopher Barkachi: using data science to build an e-learning marketplace
Aug. 26, 2021
Written by Sharon Adarlo
Barkachi is interested in using data science techniques for practical applications and having it potentially spun off into a start-up business. His independent project for the CSML certificate was developed along those lines: an e-learning market place called LiveShare.
Christina Kreisch: using machine learning tools to probe the universe’s evolution
Aug. 17, 2021
Written by Sharon Adarlo
Kreisch research interests lie in cosmology, a branch of astronomy that concerns itself with the universe’s origin and its evolution. She marries this interest with machine learning, which scientists have increasingly come to rely in recent years in order to interpret cosmological data. “I work at the intersection of theory and computation and cosmology,” said Kreisch. Her thesis is made up of three parts. The first part is theory and computationally-driven and concerns itself with neutrinos and their interactions in the early universe. This research, “The Neutrino Puzzle: Anomalies, Interactions, and Cosmological Tensions,” appeared in the journal Physical Review D in April 2019 and garnered 170 citations. Kreisch is first author.