The Rutgers ECE Department is proud to announce that graduating ECE senior Justine Catli will receive the Champion of Teaching and Learning Award at the 7th Annual Chancellor-Provost’s Student Leadership Awards Gala on May 4th, 2022. This award is for "a student who has taken full advantage of their collegiate experience by engaging inside and outside of the classroom while creating learning opportunities for their peers.” Awardees are selected among all undergraduate students at Rutgers-New Brunswick.

Throughout her time at Rutgers, Justine has been deeply involved in peer learning and mentoring. She is a leader and tireless advocate for all students in the ECE Department and in the School of Engineering more broadly. In addition to working extensively with the Rutgers Learning Centers as a Learning Assistant, she has organized new extracurricular workshops with industry sponsors and developed the IEEE Social Good Hackathon, now in its second year. Justine is currently the President of Rutgers IEEE, leading their many activities. She previously created and held the new position of External Vice President to build bridges with other student groups, the ECE Department, and industry. She has also been active in recruiting students to ECE through our Open House, Admitted Students’ Day, and Intro to Engineering. The impact of her work will last long after she graduates: due to her advocacy, the School of Engineering is working with the Learning Centers to create an anti-bias training workshop for all Learning and Teaching Assistants that will be implemented beginning in Fall 2022.

As stated in the criteria for the award, Justine has made a strong impact in the area of teaching and learning while fostering learning opportunities through peer mentoring or leadership,
dedicated time, resources, or efforts beyond what is expected of her position, upheld the values of peer instruction such as student-centered active learning, an inclusive and safe learning environment, and a well-developed pedagogical approach to peer instruction. The ECE Department is lucky to have such a committed advocate and educator among our students.

Congratulations to Justine on this well-deserved honor!

A team of Rutgers WINLAB/ECE faculty, led by Distinguished Professor Roy Yates as the PI, has received a three-year, $1,000,000 grant entitled "RINGS: REALTIME: Resilient Edge-cloud Autonomous Learning with Timely Inferences" from the NSF as part of NSF's recent multi-million dollar program aimed at the development of intelligent, resilient, and reliable next generation -- or NextG -- networks. More details about this NSF investment, termed RINGS—short for Resilient and Intelligent Next-Generation Systems, can be found in an NSF press release.
 
In this project, the team comprising of ECE faculty members Roy Yates, Dipankar Raychaudhuri, Anand Sarwate and Waheed Bajwa, will design and experimentally validate a mobile edge cloud (MEC)-based distributed machine learning (ML) system that will act as an enabler of emerging real-time applications, ranging from augmented reality and smart cities to autonomous vehicles, with strict latency requirements in the next generation of mobile networks.
 
Overall, the ECE department has received two of the 37 awarded RINGS grants (the other one being led by Professor Salim El Rouayheb), which speaks to the quality of the research being conducted in the department.

Congratulation to this year’s senior students who participated in the ECE capstone program and their advisers for a job well done!

The Capstone Expo was back in person this year and was held in the BSC. Capstone Expo Day demonstrated our students’ exceptional capabilities.

A panel of judges joint us to identify the top ten projects, recognized 3 special awards (best in research, best in impact, best in commercialization) and award three Galbiati Entrepreneurial awards (total of $5,000). Our judges were very impressed with the quality of the projects and commended our students’ capabilities and enthusiasm. The capstone teams did a fantastic job and made us all proud!

Before we announce the winning projects, I would like to thank everyone involved with this year’s capstone program:

Many advisers undertook students’ guidance this year. We would like to thank the ECE faculty who supported the program and advisers inside and outside of Rutgers who contributed their time and effort to help our students. Their efforts and support are key to the success of our capstone program and the students’ learning experience.

We would like to acknowledge the support of the following industry sponsors: 

• Don Bachman, Head of Strategy, Russelectric, a Siemens Business, and board member at 7x24 Exchange Metro New York Chapter;
• Joe Rambala, President, Electronic Warfare, Space & Airborne Systems, L3Harris;
• BlackRock;
• Galbiati family.

Many thanks to our panel of judges for their effort and time taken to support and celebrate our students’ achievements. The panel included: Minning Zhu (Rutgers ECE), Soyab Khatumbra (L3Harris), Alexander Loh (BAE Systems), Adam Novak (General Dynamics Mission Systems), Yaniv Myszkin (Audible), Don Bachman (Siemens), Milap Shah (Microsoft), Niral Shah (Apple), Will Cheng, Sabian Corrette (Rutgers), Pragati Sharma (Rutgers), Darshan Singh (Intel), Aditi Satish (Rutgers), Umama Ahmed (L3Harris), Roshni Shah (American Express), Scott Yappen (Foley Power Systems), Swetha Angara (TD Securities), Xuemeng Li (Hunter College), Marina Eskander (Concord Engineering Group), James Bibby (Schindler Elevator Corp), Steven Wu (Nuro Inc), Bhargav Tarpara (Capable Health), Parth Kanani (Empire Circuits), Anish Seth (Rutgers), Pavan Desai (Johnson & Johnson), Tim Petersen (L3Harris), Frank Hoffman (Lockheed Martin), Akash Nayak (Fidelity Investments)

Their expertise, care, and insights where priceless in making the hard decisions as for the top projects.

A very warm thank you to our wonderful ECE staff: Arletta Hoscilowicz, Pamela Heinold, John Scafidi, Kevin Wine, and Christopher Reid. As always, their commitment and hard work made this event and others happen. Many thanks to Demetrios Lambropoulos who worked tirelessly to support the capstone program around the year and to all the undergraduate students who helps with capstone expo: Aayushi Kasera, Shreya Pandey, Ritika Rao, Anisha Barde, Anurag Vattipalli, Roshan Patel, Sreetulasi Mannepalli, Aaron Soner, Adam D'Souza, Rohan Rahalkar, Emma Heinold, Harvey Zhang and Arthur Patlewicz.

After hours of diligent work, here are the awards granted by our panel of judges:

Top ten projects: 

Dean Thomas Farris announced early today the appointment of Yingying Chen as the new Chair of the ECE Department.

Zahra Aref and Ayman Younis have been selected as recipients of IEEE Communications Society Phoenix ISS Awards for academic year 2021-2022. The IEEE Communications Society Phoenix ISS Award was established to encourage engineering student to participate in professional activities. Awards are to be given to full-time or part-time students to cover expenses for students to attend the International Switching Symposium, or other IEEE Communications Society Conferences.

Congratulations Zahra and Younis!

Bios and abstracts of their recent papers are below.

Zahra Aref is a Ph.D. candidate at WINLAB, Department of Electrical and Computer Engineering, Rutgers University, NJ, USA. She is advised by Prof. Narayan B. Mandayam. Zahra’s research is focused on cyber-security, deep reinforcement learning, and human decision-making models. She was awarded as the best TA in the Department of Electrical Engineering, Rutgers University, in Spring 2021. Zahra received her master’s degree in Electrical Engineering/Telecommunication from Isfahan University of Technology, Isfahan, Iran in 2014, and developed high-speed network switches on NetFPGA.

Abstract:  Cloud storage is a target of advanced persistent threats (APTs), where a sophisticated adversary attempts to steal sensitive data in a continuous manner. Human monitoring and intervention are the integral part of the reinforcement learning (RL) approaches to defend against APTs. In this paper, prospect theory (PT) is used to model the subjective behavior of the cloud storage defender in assigning computing resources (processing units) to scan and monitor the cloud storage system against an APT attacker bot, which attempts to steal information from the cloud. Under a constraint on the total number of processing units and a lack of knowledge of the opponent’s resource allocation strategy, we study the defense performance of a federated maximum-likelihood deep Q-network (FMLDQ) RL algorithm against a sophisticated branching dueling deep Q-network (BDQ) RL attack algorithm. Specifically, the RL strategy for the defender is affected by subjective decisions in estimating the processing units of the attacker. Simulation results show that when the defender has more resources than the attacker, an EUT-based defense strategy (without human intervention) yields better data protection. On the other hand, when the defender has fewer resources, a PT based defense strategy (with human intervention) is better.

Ayman Younis is a Ph.D. candidate at the Cyber-Physical Systems Laboratory (CPS Lab), Department of Electrical and Computer Engineering, Rutgers University, NJ. He is advised by Prof. Dario Pompili. His research focuses on wireless communications and mobile cloud computing, with emphasis on software-defined testbeds. He received the Best Paper Award at the IEEE/IFIP Wireless On-demand Network Systems and Services Conference (WONS) in 2021.

Paper title:
QLRan: Latency-Quality Tradeoffs and Task Offloading in Multi-node Next Generation RANs

Abstract: Next-Generation Radio Access Network (NG-RAN) is an emerging paradigm that provides flexible distribution of cloud computing and radio capabilities at the edge of the wireless Radio Access Points (RAPs). Computation at the edge bridges the gap for roaming end users, enabling access to rich services and applications. In this paper, we propose a multi-edge node task offloading system, i.e., QLRan, a novel optimization solution for latency and quality tradeoff task allocation in NG-RANs. Considering constraints on service latency, quality loss, and edge capacity, the problem of joint task offloading, latency, and Quality Loss of Result (QLR) is formulated in order to minimize the User Equipment (UEs) task offloading utility, which is measured by a weighted sum of reductions in task completion time and QLR cost. The QLRan optimization problem is proved as a Mixed Integer Nonlinear Program (MINLP) problem, which is a NP-hard problem. To efficiently solve the QLRan optimization problem, we utilize Linear Programming (LP)-based approach that can be later solved by using convex optimization techniques. Additionally, a programmable NG-RAN testbed is presented where the Central Unit (CU), Distributed Unit (DU), and UE are virtualized using the OpenAirInterface (OAI) software platform to characterize the performance in terms of data input, memory usage, and average processing time with respect to QLR levels. Simulation results show that our algorithm performs significantly improves the network latency over different configurations.

President Jonathan Holloway has announced that Professor Waheed Bajwa  has been selected to receive a Presidential Outstanding Faculty Scholarly Award for 2021-22. This award is bestowed in recognition of Waheed's outstanding teaching and scholarly accomplishments in his years at Rutgers, as documented in the evaluation that has led to his recent promotion to Full Professor. The award carries with it a grant of $1000 from the Trustees to assist his academic efforts in the coming year. The award will be presented to Waheed at a reception to be held at the President’s Tent located on College Avenue Campus on Thursday, May 5, 2022.

ECE Associate Professor Salim El Rouayheb is the recipient of a new NSF RINGS award for the project titled "Walk For Resiliency & Privacy: A Random Walk Framework for Learning at the Edge."  Dr. El Rouayheb is the PI on this  three-year $999,999.00 collaborative effort between Rutgers and the University of Illinois at Chicago (UIC). Rutgers’ share of the award is $330,162.00.

In this project, Dr. El Rouayheb and his team aim to advance Random Walk learning algorithms  for the joint design of distributed learning and networking algorithms for Next Generation (NextG) wireless systems.  The rigid centralized infrastructure of current systems can limit the full potential of achieving resiliency and privacy in NextG systems. Random walk algorithms enable a fluid architecture where centralization and full decentralization constitute two corner points. The proposed work will focus on major challenges and opportunities specific to the applicability of random walk learning in NextG, namely: (i) Adaptability to the heterogeneity of the data and the heterogeneity and dynamic nature of the network; (ii) Resiliency and graceful degradation in the face of failures via coding-theoretic redundancy methods; (iii) Model distribution across nodes and random walking snakes; and (iv) Privacy of the locally owned data.

More details on the project can be found on the NSF page here.

Congratulations Salim!