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 […]

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). […]

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 […]

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 […]

Want to learn Python, but don’t know where to start?  We’ll walk you through everything you need to start using Python, beginning with writing code for the very first time. In this interactive workshop, you will learn about and practice core Python skills such as writing functions, troubleshooting errors, and installing packages. We will also cover tips […]

"Robust Sparsified Deep Learning" Abstract: This dissertation studies robustness issues around DNN deployments on resource constrained systems, under both environmental and adversarial input adaptation. We propose a means of compressing a Radio Frequency deep neural network architecture through weight pruning, and provide a systems-level analysis of the implementation of such a pruned architecture at resource-constrained […]

"Model-based decision making in life sciences" Abstract: Mathematical models are key tools in rational decision-making processes. A ``good" model is expected to reproduce experimental observations, which enables predictions outside the previous experimental settings. The accuracy of predictions depends on the assumptions used to model the system. The objective of this study is to explore possible […]