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Joshua Agterberg, whose work focuses on theoretical problems in data science and statistics, won for his presentation on “Nonparametric Two-Sample Hypothesis Testing for Random Graphs with Negative and Repeated Eigenvalues."

If you’re a Data Science Master’s student and you were unable to attend the Capstone Experience Information Meeting on February 12th, you can view the recording here. Click here for the Powerpoint Presentation (in pdf format).

New program aims to create regional networks of mathematical sciences departments that provide training and internship experiences to doctoral students that lead to “mathematically meaningful” careers outside of academia

He is being recognized for his contributions to graphical model identification and shape analysis with applications to machine learning, medical imaging and computational anatomy.

William Hua's paper outlines a new model that promises to improve patient outcomes by optimizing both medication dosage amounts and the timing of those dosages.

He is known for his efforts to bridge the gap between mathematical research in academia and industry, and to develop programs to prepare students in the mathematical sciences for careers outside of academia.

Collaborative project with Microsoft will use network machine learning on enterprise communication and collaboration data to evaluate and detect network resilience in a post-pandemic world.

Priebe has been recognized for his outstanding research and leadership in the field of statistics.

Established in 1964, the NAE is made up of more than 2,000 peer-elected members and international members who advise the U.S. government on matters regarding engineering and technology.

Charon’s research focuses on shape analysis and its applications to medical imaging and computational anatomy.

Pavlo A. Krokhmal Oleg A. Prokopyev   Dear Colleagues: It is our pleasure to announce that the following paper was named the winner of the 2018 OPTL Best Paper Award: Frank E. Curtis, Zachary Lubberts, Daniel P. Robinson (2018), Concise complexity analyses for trust region methods, Optimization Letters 12(8), 1713-1724. Abstract: Concise complexity analyses are…

Study aimed at understanding fluid turbulence from a physics perspective.