• Zulqarnain Qayyum Khan’s PhD Dissertation Defense

    "Interpretable Machine Learning for Affective Psychophysiology and Neuroscience" Abstract: In this thesis, we leverage existing Machine Learning (ML) models where appropriate and develop novel models to advance the understanding of affective psychophysiology and neuroscience. Additionally, considering the increased use of ML as a toolbox, we highlight underlying assumptions and limitations of basic ML methods to […]

  • Gordon Institute Virtual Information Session

    Learn how you can earn a Graduate Certificate in Engineering Leadership as a stand-alone certificate or in combination with one of twenty Master of Science degrees offered through Northeastern’s College of Engineering, College of Science, or Khoury College of Computer Sciences.  The National Academy of Engineering recognized The Gordon Institute of Engineering Leadership (GIEL)for its […]

  • Leonardo Bonati’s PhD Dissertation

    432 ISEC 360 Huntington Ave, Boston, MA, United States

    "Softwarized Approaches for the Open RAN of NextG Cellular Networks" Abstract: The 5th and 6th generations of cellular networks (5G and 6G), also known as NextG, will bring unprecedented flexibility to the wireless cellular ecosystem. Because of a typically closed and rigid market, the telco industry has incurred high costs and non-trivial obstacles for delivering […]

  • Science on Tap: Design and Perception of Heptic Devices for Social Communication

    206 Egan 360 Huntington Ave, Boston, MA, United States

    COE PhD Council presents SCIENCE ON TAP Design and Perception of Heptic Devices for Social Communication Dr. Cara Nunez Postdoctoral Research Fellow, Harvard John A. Paulson School of Engineering and Applied Sciences Faculty Fellow Assistant Professor (Incoming July 2023), Sibley School of Mechanical and Aerospace Engineering, Cornell University Join us for free ice cream and […]

  • Shuangjun Liu’s PhD Dissertation Defense

    Location: 532 ISEC "United Human Pose: Integrating Domain Knowledge and Machine Learning" Abstract: Deep learning (DL) approaches have been rapidly adopted across a wide range of fields because of their accuracy and flexibility, but require large labeled training data. This presents a fundamental problem for applications with limited, expensive, or private data (i.e. Small Data Domains). […]

  • Gordon Undergraduate Leadership Development Workshop

    431 Stearns 431 Stearns Center, 360 Huntington Ave, Boston, MA, United States

    Enhance your co-op experience with the Gordon Undergraduate Leadership Development Workshop. This engineering leadership workshop is designed for Northeastern University undergraduate engineering juniors and seniors during their second or third co-op experience. Workshop sessions are designed to be completed in parallel with co-op. The program includes a series of engineering leadership development activities focused on expanding […]

  • Abhimanyu Sheshashayee’s PhD Dissertation Defense

    Location: 532 ISEC "Wake-up Radio-enabled Wireless Networking: Measurements and Evaluation of Data Collection Techniques in Static and Mobile Scenarios" Abstract: Multi-hop wireless networks such as Wireless Sensor Networks and in general, networks without the support of a fixed infrastructure, which enable most applications of the Internet of Things, are comprised of wirelessly communicating nodes that are […]

  • Siyue Wang’s PhD Dissertation Defense

    "Towards Robust and Secure Deep Learning Models and Beyond" Abstract: Modern science and technology witness the breakthroughs of deep learning during the past decades. Fueled by the rapid improvements of computational resources, learning algorithms, and massive amounts of data, deep neural networks (DNNs) have played a dominant role in many real world applications. Nonetheless, there […]

  • Kimia Shayestehfard’s PhD Proposal Review

    "Permutation Invariant Graph Learning" Abstract: Graphs are widely used in many areas such as biology, engineering, and social sciences to model sets of objects and their interactions and relationships. Tasks addressed by applying machine learning to graphs, known as graph learning, include node and graph classification, edge prediction, transfer learning, and generative modeling/distribution sampling, to […]

  • AME Academy 2022 Summer Session

    ADDITIVELY MANUFACTURED ELECTRONICS (AME) - THE NEXT GENERATION OF ELECTRONIC DEVICES AND CIRCUITS FROM 2D TO 3D AME Academy will be delivering a 1 day event at Northeastern University, Boston MA on July 29, 2022. Join the team of experts led by electronics industry veteran Mr. Gene Weiner, member of the IPC’s Raymond E. Pritchard Hall […]