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Mengdi
Wang

Professor of Electrical and Computer Engineering and the Center for Statistics and Machine Learning

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Research interests: Decision making and reinforcement learning problems involving uncertainty or hidden information; modeling uncertainty and designing algorithmic approaches that "learn" the best decisions as information is revealed. optimization (stochastic, online, and even more), stochastic programming, variational inequalities, dynamic programing, statistical learning, and game dynamics.

Related News

An assortment of advanced microchips on a lab table.
A grant of nearly $10 million to design advanced microchips for wireless communications and sensing was announced May 28 by the National Center for the Advancement of Semiconductor Technology, or Natcast. Princeton’s Kaushik Sengupta will lead the joint government-industry effort. Photos by Sameer A. Khan/Fotobuddy

Princeton will lead U.S. effort to design better chips for wireless communication

Man speaks near podium while pointing at a scientific graphics on a screen.
Egemen Kolemen describes how he has used artificial intelligence to increase stability in the reactions that power nuclear fusion as a source of clean electricity. Photos by David Dooley/Fotobuddy

Initiative aims to make Princeton a leader in AI accelerated engineering

Mengdi Wang in her office with math on the whiteboard in background.
Mengdi Wang in her Princeton office. Photo by Sameer A. Khan/Fotobuddy

Mengdi Wang makes a play at decoding disease

Speaker at podium in front of screen that says AI for Control, Design and Creation.
Mengdi Wang, associate professor of electrical and computer engineering and co-director of one of several new AI initiatives, spoke at Princeton’s recent AI Summit. Photo by Sameer A. Khan/Fotobuddy

New initiatives bring Princeton to the fore of AI innovation

Single strand ribonucleic acid.
Princeton researchers led by Mengdi Wang have developed a language model to home in on partial genome sequences and optimize those sequences to improve function for the development of mRNA vaccines and other therapies. Illustration from Adobe Stock.

Can language models read the genome? This one decoded mRNA to make better vaccines.

Vincent Poor and Mengdi Wang
H. Vincent Poor and Mengdi Wang

Princeton Engineering faculty members receive grants for COVID-19 research from C3.ai Digital Transformation Institute

Affiliations

Professor writes on white board while talking with grad student.

Electrical and Computer Engineering

Improving human health, energy systems, computing and communications, and security

26 Prospect building

Center for Statistics and Machine Learning