ECE Welcomes New Graduate Director Waheed Bajwa

Professor Waheed Bajwa will serve as the ECE Graduate Director for a period of 3 years (2022-2025). We feel grateful that Waheed stepped up to take on this important role for our department. Waheed has a very strong background in research, teaching and student advising. We look forward to working with Waheed closely to bring our graduate program to a new level in the coming years. 

 

 

ECE Welcomes Associate Undergraduate Director Chung-Tse Michael Wu

Associate Professor Chung-Tse Michael Wu will serve as the ECE Associate Undergraduate Director for AY 2022-2023. We are grateful that he has stepped up to take on this role. Going forward, on top of his excellent research work and equipped by his rich mentoring/advising experiences in both undergraduate and graduate students, Michael will serve as the interface between the university/SoE and ECE to coordinate student tours,open houses, and various related events.

Dario Pompili and Tuyen Tran win IEEE Vehicular Technology Society 2022 Neubauer Award

Dario Pompili and Tuyen X. Tran (Rutgers PhD. 2018) have won the  IEEE Vehicular Technology Society 2022 Jack Neubauer Memorial Award recognizing the best systems paper published in the IEEE Transactions on Vehicular Technology for their paper entitled "Joint Task Offloading and Resource Allocation for Multi-Server Mobile-Edge Computing Networks".  The award consists of a certificate and $1,000 divided equally among all authors.   The award will presented tat the upcoming VTC2022-Fall conference in London, September 26-29, 2022. 

Tuyen Tran recieved his PhD. from Rutgers in 2018 and is currently a Senior Inventive Scientist with AT&T Labs Research in Bedminster, NJ.

Congratulations to Dario (pictured left) and Tuyen !

 

Yingying Chen receives NSF Grant for Accelerating AI on Resource-Constrained Edge Devices

ECE Professor Yingying Chen is the recipient of a new award from the National Science Foundation under the Computing and Communication Foundations (CCF) program for the project "A General Framework for Accelerating AI on Resource-Constrained Edge Devices.” This is a three-year $600,000 research project.

This project aims to develop a novel framework that can efficiently design neural-network architectures suitable for execution on edge devices. The upward trend of the pervasive usage of edge devices provides excellent opportunities for on-device intelligence in future mobile and IoT applications, including mobile augmented reality (AR)/Virtual reality (VR), smart manufacturing, mobile healthcare, and autonomous vehicles. While these edge devices have complete software/hardware stacks to execute machine-learning models, they usually have constrained computing resources. They cannot afford to execute the machine-learning models directly. The proposed framework develops network architectures that simultaneously balance memory cost, computing efficiency, and prediction accuracy, which can advance on-device AI applications with low-latency and high-efficiency requirements. The new deployment optimization methods can generally benefit neural-network implementation and deployment on heterogeneous commodity computing platforms without customized hardware.

More details on the project can be found at the NSF page here: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2211163&HistoricalAwards=false

Congratulations to Yingying!

SoE Professors Receive Faculty Excellence Awards

School of Engineering faculty Waheed Bajwa and Chung-Tse Michael Wu were among the recipients of Rutgers’ 2021-2021 Faculty Year-End Excellence Awards, at the first in-person ceremony in two years.  

“This is a moment we get to say thank you,” Rutgers University President Jonathan Holloway said at the awards ceremony. “Thank you for your dedication to excellence and thank you for your commitment to your students. Thank you for your exemplary research and thank you for helping Rutgers change the world for the better.” 

Bajwa, an associate professor in the Department of Electrical and Computer Engineering received the Presidential Outstanding Faculty Scholar Award. The award honors newly promoted or tenured faculty whose outstanding portfolios reflect outstanding research, scholarship, or creative work, as well as outstanding contributions to teaching and service to the Rutgers community and beyond.   

“Rutgers is home to an amazing group of faculty so to have been selected among this group as one of the five awardees this year for the Presidential Outstanding Faculty Scholar Award is quite a surreal and humbling feeling for both me and my family. While the award is a confirmation of the fact that my research and teaching activities during my eleven-year stay at Rutgers have been in the right direction, I owe this award to my students, research mentees, and academic mentors who have helped me be the faculty that I am,” says Bajwa.  

Department of Electrical and Computer Engineering Associate Professor Chung-Tse Michael Wu won the Board of Trustees Research Fellowship for Scholarly Excellence. It honors distinguished newly-promoted and tenured faculty whose contributions to teaching during their early years at Rutgers have been truly outstanding.  

“I am truly humbled and honored to receive this award. First and foremost, I am grateful to Rutgers for providing us with great research environments that enable us to work on cutting-edge research projects in the field of electromagnetics,” said Prof. Wu. 

“Moreover, I feel fortunate that we have brilliant, capable students and researchers on our team who work tirelessly to deliver their best research outcomes. This award is a wonderful recognition of the research carried out by our entire group.”

Rutgers Team receives NSF Grant for Learning-Assisted Additive Manufacturing

ECE Assistant Professor Bo Yuan is a co-PI on a Rutgers team that received a new NSF award for the project titled "Computation-Informed Learning of Melt Pool Dynamics for Real-Time Prognosis.”  The team received a three-year $509K award and is led by Professor Yuebin Guo (PI) from Mechanical and Aerospace Engineering. Prof. Dong Deng from Computer Science is also a Co-PI.
 
The goal of this project is to explore deep understanding and fast prediction of melt pool behaviors are necessary for printing high-quality parts. Data science models (e.g., deep learning, or DL) may use diverse types of melt pool data for efficient prediction of overheating. But the data science models lack transparency, are computationally expensive, and need massive training data. On the other hand, computational models may understand the complex melt pool behaviors, but require continuous updates of model parameters and are not suitable for fast prediction. This project provides an integrated approach by using the strength of both models for fast prediction of melt pool overheating. The outcome of this project will not only contribute to the fundamental knowledge of deep learning but also enable the broad acceptance of the project's testbed as a public tool for the additive manufacturing community. 
 
You can find more details on the project at the NSF page here
 
Congratulations to Bo and the team!

ECE Seniors receive Air Force Research Laboratory (AFRL) recognition for Capstone Project on RF Machine Learning

Graduating ECE Seniors  Michael Zhao and Morriel Kasher have been selected for their Capstone Design project "Radio Frequency Machine Learning (RFML): Streamlining SDR Implementation of Neural Networks Through GNURadio " to compete in the  US Airforce Research Laboratory (AFRL) Beyond 5G SDR University Challenge 2021/22,  a nation-wide  competition that includes both  graduate and undergraduate student teams. AFRL also provided  funding for the project with high end software defined radio (SDR) equipment that helped significantly in  project execution. Michael and Morriel's work advised by ECE Associate Professor Predrag Spasojevic was one of only 11 invitees to the AFRL Beyond Showcase this May 2022. 

The RFML project achieves  advanced signal processing operations on experimental, real-world radio data in  an off-line manner, while post-processing previously collected or simulated data. Application examples include Wideband Anomaly Detection, Radiometric Fingerprinting, and Modulation Recognition, problems of increasing importance due to extreme proliferation of wireless devices.  In their work, Michael and Morriel designed and demonstrated a working  prototype that can take arbitrary RFML Neural Networks algorithms and signaling formats directly from Software Defined Radios and execute advanced signal processing algorithms in an on-line manner, while the data is received. Their solution is revolutionary in the design and difficulty of achieving and will open many new applications in the field of RFML with very significant implications for current and future wireless systems. 
 
The project was also awarded first place in the ECE Capstone Design competition and third place in the Galbiati Entrepreneurial competition, which recognized those capstone projects with immediate potential for commercialization.
 
Congratulations to Michael, Morriel and Predrag!

Yingying Chen to be honored at the Chancellor-Provost’s Celebration of Faculty Excellence

The University has announced that Professor Yingying Chen will be honored at the Chancellor-Provost’s Celebration of Faculty Excellence on May 19.  She will be recognized for the following accomplishments this past year- (i) Fellow, National Academy of Inventors, and (ii) Distinguished Member, Association for Computing Machinery.

Congratulations Yingying!

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