Prof. Dina Katabi

Thuan (1990) and Nicole Pham Professor of Electrical Engineering and Computer Science
Director, Center for Wireless Networks and Mobile Computing (Wireless@MIT)

Primary DLC

Department of Electrical Engineering and Computer Science

MIT Room: 32-G936

Areas of Interest and Expertise

Computer Networks
Data Communication
Security: Trade-offs in Denial of Service, System Adaptability, Intrusion Detection
Tools for Measuring Network Congestion
Intranet Measurement and Protocols
Enterprise Network Optimization
Traffic Engineering
Congestion Control, Network Measurements, Scalability and Robustness of Communications Systems<br>Differentiated Services, Internet Pricing, Routing, Content Distribution, Self Configurable and Wireless Networks<br>Network Security

Research Summary

Professor Katabi's research spans digital health, wireless sensors, mobile computing, machine learning and computer vision.

They encompass congestion control, network measurements, scalability and robustness of communication systems, differentiated services, Internet pricing, routing, content distribution, peer-to-peer systems, self-configurable and wireless networks, and network security.

She has a particular interest in adapting tools from various fields of applied mathematics such as control theory, coding theory, and AI to solve problems in computer networks.

Recent Work

  • Video


    October 13, 2021Conference Video Duration: 42:10
    Dina Katabi
    Andrew and Erna Viterbi Professor
    MacArthur Fellow
    Leader of NETMIT Research Group
    Director of the MIT Center for Wireless Networks and Mobile Computing

    AI in LIfe Science 2018 - Dina Katabi

    December 4, 2018Conference Video Duration: 37:3

    AI for Passive In-Home Patient Monitoring: From Wearables to Invisibles

    This talk introduces Emerald, a novel MIT technology for in-home non-intrusive patient monitoring. The Emerald device is a WiFi-like box that runs customized machine learning algorithms to learn digital biomarkers from the wireless signals in the patient's home. It can remotely monitor the patient’s gait speed, falls, respiratory signal, heart rate, and sleep quality and stages. The sensing is completely passive – i.e., the patient can go about her normal life without having to wear any sensors on her body, write a diary, or actively measure herself. This talk will discuss the technology and the results from pilot studies in various therapeutic areas.

    2018 MIT AI in Life Sciences and Healthcare Conference