• Jiacheng Shi’s PhD Dissertation Defense

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

    Title: Towards a Programmable, High Speed, and Robust Internet of Underwater Things Location: ISEC 232 Committee Members: Prof. Tommaso Melodia (Advisor) Prof. Stefano Basagni Prof. Kaushik Chowdhury Abstract: Increasing demand of underwater exploration requires a platform with higher data rate, more robust performance, and hardware/software flexibility. The biggest challenge to realize these networked platforms is […]

  • Reconnect Workshop 2023: Risk Assessment

    Where: The Omni Hotel, Providence, Rhode Island   This year's workshop is focused on Risk Assessment. Risk assessment is an overall process of identifying, analyzing, and preparing for potential risks (e.g., natural or man-made disasters), which is extremely important to ensure the continuity of organization operations and the well-being of the people involved. Risk assessment goals […]

  • Recurring

    CommLab Writing Group

    Curry Student Center 360 Huntington Ave., Boston, MA, United States

    Join us weekly in the Curry Student Center, room 433. Setting and sticking to a consistent writing schedule is key to improving skills and accomplishing your writing tasks (don’t just take our word for it). COE graduate students are invited to join the CommLab writing group to share best practices, get feedback from your peers, […]

  • 2023 AEESP Conference Hosted at Northeastern University

    Northeastern University is proud to present the 2023 AEESP Research and Education Conference, organized in collaboration with a large team from universities in New England including Massachusetts Institute of Technology, Tufts University, University of Connecticut, University of Maine, University of Massachusetts-Amherst, University of New Hampshire, and University of Rhode Island.  This conference will be welcoming […]

  • Alfred P. Navato’s PhD Dissertation Defense

    Title: Enabling Anomaly Detection in Complex Chemical Mixtures Through Multimodal Data Fusion Date: 6/26/2023 Time: 10:00:00 AM Location: SH 210, Committee Members: Prof. Mueller (Advisor) Prof. Erdogmus Prof. Ioannidis Prof. Onnis-Hayden Abstract: Recently innovations in machine learning and data processing are increasingly tied to ensuring useability and interpretability when these methods are applied within end-user […]

  • Chang Liu’s PhD Dissertation Defense

    "Unleashing the Potential of Transfer Learning for Visual Applications" Committee Members: Prof. Raymond Fu (Advisor) Prof. Sarah Ostadabbas Prof. Zhiqiang Tao Abstract: The recent flourish of deep learning in various tasks is largely accredited to the rich and accessible labeled data. Nonetheless, massive supervision remains a luxury for many real-world applications. Further, the domain shift […]

  • Cooper Loughlin’s PhD Dissertation Defense

    "Deep Generative Models for High Dimensional Spatial and Temporal Data Analysis" Committee Members: Prof. Vinay Ingle (Advisor) Dr. Dimitris Manolakis Prof. Purnima Ratilal-Makris Abstract: Data analysis and exploitation in practical applications is challenging when observations are the result of many interacting natural and man-made phenomena. We address two important problems for which traditional methods of […]

  • 2023 ASEE Conference- Baltimore, MA

    Northeastern College of Engineering will attend ASEE 2023 Annual Conference this year at the Baltimore Convention Center, MA. Join us to learn about Northeastern's graduate engineering programs from Sunday, June 25th to Wednesday, June 28th! Our booth number is 98.    

  • Deniz Unal’s PhD Proposal Review

    Title: Software-Defined Underwater Acoustic Networks Committee Members: Prof. Tommaso Melodia (Advisor) Prof. Stefano Basagni Prof. Kaushik Chowdhury Dr. Emrecan Demirors Abstract: The exploration, monitoring, and understanding of oceans play a crucial role in addressing climate change, overseeing underwater pipelines, and preventing maritime warfare attacks. To achieve these significant objectives, it is vital to utilize networks […]

  • Zifeng Wang’s PhD Dissertation Defense

    Title: Effective and Efficient Continual Learning Committee Members: Prof. Jennifer Dy (Advisor) Prof. Stratis Ioannidis Prof. Yanzhi Wang Abstract: Continual Learning (CL) aims to develop models that mimic the human ability to learn continually without forgetting knowledge acquired earlier. While traditional machine learning methods focus on learning with a certain dataset (task), CL methods adapt […]