Dina Katabi

Academic biography

Katabi received a bachelor's degree in electrical engineering from the University of Damascus in 1995, then an M.S in Computer Science and a Ph.D. in Computer Systems Networking and Telecommunications from MIT in 1998 and 2003, respectively. In 2003, Katabi joined MIT, where she holds the title of Professor in the Department of Electrical Engineering and Computer Science. She is the co-director of the MIT Center for Wireless Networks and Mobile Computing and a principal investigator at MIT's Computer Science and Artificial Intelligence Laboratory.

Research and career

Katabi's research focused on signals, machine learning and health. Her work started in networks (especially the congestion control challenge), where she found solutions for a better reliability of networks. Then, with her team, she used machine learning and signals to analyze the human body. Based on how RF signals bounce off our bodies, the researchers could measure human breathing, heart rates, emotion and sleep stages, without having the "patient" wear any sensor. Her most recent research combined medicine with AI, where she developed with her team a system capable of diagnosing Parkinson's Disease.

Awards

In 2013, Katabi won the Grace Murray Hopper Award, recognizing her as the outstanding young computer science professional.

In 2012, her work on Sparse Fourier Transforms was chosen as one of the top 10 breakthroughs of the year by Technology Review.

In September 2013, Katabi was awarded a MacArthur Fellowship for her work. In 2013 she also became a fellow of the Association for Computing Machinery.

In 2014, on the celebration of Project Mac's 50th anniversary, her work on X-ray vision was chosen as one of the "50 ways that MIT has transformed computer science."

In 2015, Katabi presented her startup idea to President Obama at White House demo day.

In 2017, she was elected a member of the National Academy of Engineering for contributions to network congestion control and to wireless communications. In the same year, Katabi received the ACM Prize in Computing for her groundbreaking contributions to wireless networking. The Association for Computing Machinery recognized her as “one of the most innovative researchers in the field of networking,” noting her integration of communication theory, signal processing, and machine learning to address challenges in wireless systems.

In 2022, she was elected a member of the American Academy of Arts and Sciences.

In 2023, Katabi was elected to the National Academy of Sciences, and received an Honorary Doctorate in Humane Letters from the American University of Beirut in recognition of her significant contributions to research and innovation in wireless networks.

In 2024, Katabi presented her work on AI-powered, contactless health monitoring at the 2025 MIT Women's Conference, showcasing how wireless signals can be used to assess sleep quality, respiration, and gait in home settings, especially for individuals with chronic illnesses. That same year, she was profiled by the U.S. Department of State in its ShareAmerica series, which highlighted her development of artificial intelligence tools to monitor breathing, heart rate, sleep, and movement to aid in the diagnosis and management of conditions such as Parkinson's disease, Alzheimer's disease, Crohn's disease, ALS, and Rett syndrome.

She was also a featured speaker at the 2024 International Congress of Parkinson's Disease and Movement Disorders, where she presented research on the use of artificial intelligence to detect neurodegenerative disease symptoms through passive monitoring of breathing patterns. Her lab continues to develop radio wave–based, contactless sensing devices—resembling Wi-Fi routers—that are capable of tracking a wide range of health conditions, including Alzheimer's disease, atopic dermatitis, autoimmune disorders such as lupus, and other neurodegenerative illnesses like ALS.

As of 2024, Katabi holds the Thuan and Nicole Pham Professorship at the Massachusetts Institute of Technology (MIT), and serves as director of the MIT Center for Wireless Networks and Mobile Computing. Her research focuses on the intersection of AI, wireless sensing, and medical diagnostics.

In 2025, her research group published a study demonstrating that a neural network could detect Parkinson's disease using breathing data collected during sleep. The study, which analyzed data from more than 7,600 individuals, showed that the model could accurately distinguish individuals with Parkinson's disease from healthy participants, and could further estimate disease severity and monitor progression over time—offering a non-invasive tool for both clinical use and remote care.

In 2025, she was elected a member of the National Academy of Medicine.