• PhD Dissertation Defense Shivang Aggarwal

    Location: ISEC 332 "Towards Reliable, High Capacity mmWave Wireless LANs for Mobile Devices" Abstract: The IEEE 802.11ad standard, with its 14 GHz of unlicensed spectrum around 60 GHz, is touted as one of the key technologies for building the next generation of WLANs that will enable high throughput demanding mobile applications. However, there have been serious […]

  • Interdisciplinary Women’s Collaborative Hackathon

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

    The IWC will be hosting our first annual Hackathon! This event will take place on November 19th from 8am-10pm in the Curry Student Center. It is open to women and non-binary undergraduate and graduate students and we welcome all experience levels. There will be corporate sponsors, free swag, and food is provided. All members from a […]

  • Research Initiation: Analyzing inequities in undergraduate workforce opportunities between biomedical and other engineering disciplines

    Monday, November 21st at 12pm (VIRTUAL) Please Register: https://bit.ly/3MxqA0u All attendees receive a FREE BOOK! Abstract: Biomedical Engineering majors have been shown to exhibit higher rates of transfer to different engineering majors, lower rates of internship and career employment offers, and lower average starting salary compared to other engineering majors. These inequities in undergraduate workforce […]

  • Info Session: Dialogue in Turkey

    If you are interested in joining the Dialogue of Civilization program in Turkey (summer 1 2023), you can attend the Info Session which takes place on Mon 21st, from 2:00 pm - 2:30 pm. This event is hybrid and you can RSVP using this link. Also, please visit the program brochure page for more information. […]

  • Mahshid Asri’s Proposal Review

    "Development of Anomaly Detection and Characterization Algorithms Using Wideband Radar Image Processing for Security Applications" Abstract: Detection and characterization of suspicious body-worn objects is necessary for safe and effective personnel screening. In airports, developing a precise system that can distinguish threats and explosives from objects like money belt can reduce the pat-down significantly while maintaining […]

  • Can Qin’s PhD Proposal Review

    "Transfer Learning across Domains, Tasks and Models" Abstract: The big data stands as a cornerstone of deep learning, which has significantly improved a wide range of machine learning and computer vision tasks. Despite such a great success, data collection is time-consuming and costly, considering manual efforts and privacy restrictions. Transfer learning is a promising direction […]

  • Xuanyi Zhao’s PhD Proposal Review

    "AlN/AlScN based Micro Acoustic Metamaterials for Radio Frequency Applications of the Next Generations" Abstract: In the last two decades‚ micro-acoustic resonators (μARs) have played a key role in integrated 1G-to-4G radios‚ providing the technological means to achieve compact radio frequency (RF) filters with low loss and moderate fractional bandwidths (BW<4%). More specifically‚ Aluminum Nitride (AlN) […]

  • Research Presentations On Bendable Electronics and Sustainable Technologies (BEST)

    442 Dana 360 Huntington Ave, 442 DA, Boston, MA, United States

    Professor Ravinder Dahiya will be joining Northeastern’s ECE Department on January 2023. Please join us for an interactive mini-symposium featuring projects from the BEST Lab directed by Professor Dahiya.   The presenters are: Dr. Dhayalan Shakthivel, Research Associate, Inorganic Nanowires for Flexible and Large Area Electronics Dr. Gaurav Khandelwal, Post-doc, Functional Materials based Triboelectric Nanogenerators for Selfpowered Sensors and […]

  • Prof. Hui Guan – “Towards accurate and efficient edge computing via multi-task learning “

    442 Dana 360 Huntington Ave, 442 DA, Boston, MA, United States

    "Towards accurate and efficient edge computing via multi-task learning " Abstract: AI-powered applications increasingly adopt Deep Neural Networks (DNNs) for solving many prediction tasks, leading to more than one DNNs running on resource-constrained devices. Supporting many models simultaneously on a device is challenging due to the linearly increased computation, energy, and storage costs. An effective […]