Data Science and Intelligent Systems

Concepts and techniques from data science and intelligent computing  are being rapidly integrated into many areas of Electrical and Computer Engineering (ECE), in particular by exploiting new developments in machine learning. Areas such as computer and robot vision, computational imaging, and biometric recognition greatly benefit from recent advances in deep learning. Computational biology and computational neuroscience rely on advanced data science methods to process the vast amounts of information produced by novel sensing modalities, with the ultimate goal of delivering personalized medicine. Transportation and energy networks, as well as the emerging Internet of Things (IoT) infrastructure, heavily rely on intelligent, distributed computing to manage various forms of congestion and other anomalies. To support such intensive data processing, specialized hardware, software, and computer architecture are essential. Research activities in Data Science and Intelligent Systems span a wide range of topics, and also complement and enhance the ECE Department’s synergies with the Division of Systems Engineering, the Hariri Institute, and the Data Science Initiative. A vibrant organizational unit in this research area is the Information and Data Sciences (IDS) group, which brings together faculty and students with interests in the sensing, communicating, and processing of various forms of information. We invite you to explore our research activities, meet our teams, and read about our success stories by visiting the faculty, lab and research center pages below.

Affiliated Faculty

John Baillieul, Kayhan Batmanghelich, Calin Belta, Margrit Betke, Christos Cassandras, David Castañón, Ashok Cutkosky, Robert M. Gray, Prakash Ishwar, W. Clem Karl, Janusz Konrad, Brian Kulis, Wenchao Li, Thomas Little, Hamid Nawab, Bobak Nazer, Eshed Ohn-Bar, Alex Olshevsky, Francesco Orabona, Ioannis Paschalidis, Venkatesh Saligrama, Stan Sclaroff, Archana Venkataraman

Affiliated Labs
Affiliated Research Centers
In the news:
  • February 16, 2023

    One Drop at a Time: BU iGem Team Brings Home Gold Medal

    The annual International Genetically Engineered Machine (iGEM) competition is a momentous opportunity for engineering students with a passion for synthetic biology to gain valuable hands-on experience and make their big ideas into solid reality. Boston University has sponsored a team for the competition for many years now, with the dedicated support of Professor Douglas Densmore and STEM Pathways. In 2022, the BU Hardware team’s hard work paid off with multiple honors: a gold medal and a nomination for the Best Environment Project. Even more importantly, they fulfilled the mission they began with: to create a novel technology with the potential to make a meaningful impact on society. [ More ]

  • January 23, 2023

    The Brain Trust’s Newest Additions

    The Department of Electrical and Computer Engineering welcomes new faculty members Associate Professor Archana Venkataraman and Assistant Professor Kayhan Batmanhelich. [ More ]

  • November 7, 2022

    MADE with Machine Learning: Utilizing AI to Design the Next Generation of Semiconductor Devices

    With the help of advanced, physics-informed machine learning (PIML) techniques, Professors Enrico Bellotti & Luca Dal Negro are setting out to transform the status quo of electronic device design, with the support of a $2.5M grant from the Army Research Office. [ More ]

  • June 8, 2022

    Hariri Highlights: ECE Professor To Lead Computing Institute, and More

    With such clear interests and goals in common, it’s no wonder that there is a strong relationship between BU’s Department of Electrical and Computer Engineering and the Rafik B. Hariri Institute for Computing and Computational Science & Engineering. [ More ]

  • April 20, 2022

    Unveiling the Hidden Signatures of Drug Resistance in Cancer Cells

    Supported by a $1.75M grant from the National Institute of Biomedical Imaging and Bioengineering, a multidisciplinary team of experts led by Professor Ji-Xin Cheng are developing a novel approach to establish high-speed, high-content and high-sensitivity mapping of cancer cell metabolism. [ More ]