Events

"Fast Identification via Subspace Clustering and Applications to Dynamic and Geometric Scene Understanding" Abstract: More and more data is needed in order to build new machine learning and computer vision […]

"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 […]

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 […]

"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 […]

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 […]

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 […]

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 […]

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 […]

"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 […]

"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 […]