Mehdi Javanmard receives DARPA Young Faculty Award

Mehdi Javanmard, an associate professor in the School of Engineering Department of Electrical and Computer Engineering (ECE) has received a two-year, $500,000 Defense Advanced Research Projects Agency (DARPA) Young Faculty Award (YFA). The award also includes a $500,000 option phase for a third year.
 
“This DARPA YFA is the second such award in successive years in the ECE department and, along with eight active NSF CAREER awards reflects the phenomenal successes of our young faculty members,” says ECE distinguished professor and chair, and Rutgers WINLAB assistant director Narayan Mandayam.
 
Javanmard’s project, “Lab-on-a-Microparticle: Injectable Wirelessly Powered Label-free Nanowell Sensors for In Vivo Quantification of Protein and Small Molecules” will make a new type of wirelessly powered tiny sensors able to map and monitor markers and various molecules in tissues and wounds.
 
“Winning the DARPA Young Faculty Award is a great honor for me at a very exciting time in my career,” says Javanmard, who was a 2019 recipient of a National Science Foundation CAREER Award. “I will get to think out of the box and work on a very high-risk but high-reward project for healthcare.”
 
Established to incubate the next generation of scientists, mathematicians, and engineers who will spend significant time and energy on Department of Defense (DoD) and national security issues, the prestigious DARPA YFA Award is presented to talented young faculty in the early stage of their academic careers. Javanmard’s DARPA Award – which provides funding, mentoring, and access to industry and DoD contacts – will expose him to both DoD needs as well as to the DARPA program development process.
 
According to Javanmard, over the last few decades, the DoD has invested heavily in new biosensing and medical diagnostic technologies that benefit the health and wellbeing of all members of society. “This can include rapid detection of infectious agents like COVID-19, treating and monitoring wounds with smart bandages, and even monitoring and treating chronic diseases such as cancer, gastrointestinal diseases, and rheumatoid arthritis,” he explains.
 
Javanmard, who views healthcare access as one of the leading challenges of the 21st century, seeks to apply his engineering knowledge and skill to create innovative, interdisciplinary solutions to pressing healthcare problems. “With the coronavirus pandemic, as a society we have learned about the need for more innovative diagnostic tools – and that the current centralized lab model of testing is simply inadequate to serve society’s needs. As a result, the economic loss for this country alone will be trillions of dollars.”
 
“The idea that our inventions in the lab can be used to save lives and improve the quality of life of patients, really makes me excited,” he says. “We hope we can make better tools for more rapid and inexpensive diagnosis of diseases in order to make healthcare more accessible to the broader population.”
 
For Javanmard, students will play a critical role in this research. “Students are our most valuable and precious resource. They go into the lab and design, fabricate, and test devices and analyze the results,” he insists. ”We can only achieve great things with the heavy involvement of our students.”

 

WINLAB Researchers receive NSF Grant for Hardware-accelerated Trustworthy Deep Learning

ECE Professor Yingying Chen (PI) and WINLAB CTO, Ivan Seskar are the recipients of a new NSF planning award titled "Hardware-accelerated Trustworthy Deep Neural Network” from the NSF Principles and Practice of Scalable Systems (PPoSS) program. This is a one-year $250,000 collaborative effort among Rutgers, Indiana University, Temple University and NYIT, covering the disciplines of electrical and computer engineering, computer science, security and data science. The aim of the PPoSS program is to support a community of researchers who will work symbiotically across the multiple disciplines above to perform basic research on the scalability of modern applications, systems, and toolchains. The planning grant will be used to develop a LARGE grant proposal to foster the development of principles that lead to rigorous and reproducible artifacts for the design and implementation of large-scale systems and applications across the full hardware/software stack.

During the planning phase, Yingying’s team will develop a scalable and robust heterogeneous system that includes a new low-cost, secure, deep-learning hardware accelerator architecture and a suite of large data compatible deep learning algorithms. The new technologies resulting from this planning grant will also enable extremely large-scale data and facilitate efficient, low-latency applications in connected vehicles, real-time mobile applications, and timely precision health.
 
You can find more details on the project at the NSF page here. 

WINLAB Researchers receive NSF Grant for Hardware-accelerated Trustworthy Deep Learning

ECE Professor Yingying Chen (PI) and WINLAB CTO, Ivan Seskar are the recipients of a new NSF planning award titled "Hardware-accelerated Trustworthy Deep Neural Network” from the NSF Principles and Practice of Scalable Systems (PPoSS) program. This is a one-year $250,000 collaborative effort among Rutgers, Indiana University, Temple University and NYIT, covering the disciplines of electrical and computer engineering, computer science, security and data science. The aim of the PPoSS program is to support a community of researchers who will work symbiotically across the multiple disciplines above to perform basic research on the scalability of modern applications, systems, and toolchains. The planning grant will be used to develop a LARGE grant proposal to foster the development of principles that lead to rigorous and reproducible artifacts for the design and implementation of large-scale systems and applications across the full hardware/software stack.

During the planning phase, Yingying’s team will develop a scalable and robust heterogeneous system that includes a new low-cost, secure, deep-learning hardware accelerator architecture and a suite of large data compatible deep learning algorithms. The new technologies resulting from this planning grant will also enable extremely large-scale data and facilitate efficient, low-latency applications in connected vehicles, real-time mobile applications, and timely precision health.
 
You can find more details on the project at the NSF page here. 

Rutgers Researchers receive NSF National Research Traineeship (NRT) Grant for Socially Cognizant Robotics

ECE Professor Kristin Dana is the PI for a $3M National Science Foundation Research Traineeship (NRT) grant to Rutgers entitled SOCRATES: Socially Cognizant Robotics for a Technology Enhanced Society. The co-PIs are Kostas Bekris (CS), Clinton Andrews (Bloustein School), Jacob Feldman (Psychology), and Jingang Yi (MAE). 
 
The NSF NRT grants are designed to develop and implement bold, transformative models for science, technology, engineering and mathematics (STEM) graduate education training. SOCRATES will create a new vehicle for graduate training and research that integrates technology domains of robotics, machine learning and computer vision, with social and behavioral sciences (psychology, cognitive science and urban policy planning). The long-term objective is to nurture and mobilize a community of researchers who can draw on sophisticated understanding of social structures and processes in the effective development and deployment of autonomous systems for the benefit of individuals and society. A key challenge of the program is Robotics for Everyday Augmented Living (REAL), semi-automated systems that focus on tasks and work within daily life. The REAL challenge will be emphasized using a heterogeneous testbed of robots on campus (Rutgers Live Lab) to go beyond standard lab-based robot experiments incorporating field work with the campus as a model for society. Emerging applications of robotics are certain to bring significant changes in individuals' lives and profound social impacts, including the future workforce of the nation. Key questions are: What are societal impacts of robotic technology? How can these impacts be predicted and evaluated in order to influence next-generation technology? How can robotics be developed in a socially cognizant manner? While the potential of robotics is often postulated, the realization of ubiquitous robot assistants augmenting an individual's productivity and quality of life has not been realized. This training program seeks to identify the critical societal needs that technology can realistically address to catalyze and guide meaningful research. The interdisciplinary theme of SOCRATES unites technologists and social scientists in order to steer the development of robotics and intelligent systems toward the benefit of society. The program aims to train a new type of professional, the socially cognizant roboticist, through the convergence of the socially aware technologists and the technology-aware social scientist. The proposed theme of (SOCRATES) Socially Cognizant Robotics for a Technology Enhanced Society will catalyze a new paradigm of integrative graduate training at the burgeoning interface of society and intelligent devices. The program will differ substantially from traditional robotics programs by integrating technology disciplines and social sciences towards beneficial societal impact. Multi-year cohorts of over 35 graduate students will be impacted by the program, comprised of 17 NRT-funded students, as well as 20 non-NRT-funded students. The program will be offered at the MS and PhD level. A larger community of MS/PhD students across four major academic units (Engineering, Computer Science, Behavioral Sciences, and Public Policy) will be impacted, bringing the expected total to approximately 100 students benefiting from some component of the program over five years.
 
You can find more details on the project at the NSF page here. 
 
Congratulations to Kristin and her team!

Rutgers Researchers receive NSF National Research Traineeship (NRT) Grant for Socially Cognizant Robotics

ECE Professor Kristin Dana is the PI for a $3M National Science Foundation Research Traineeship (NRT) grant to Rutgers entitled SOCRATES: Socially Cognizant Robotics for a Technology Enhanced Society. The co-PIs are Kostas Bekris (CS), Clinton Andrews (Bloustein School), Jacob Feldman (Psychology), and Jingang Yi (MAE). 
 
The NSF NRT grants are designed to develop and implement bold, transformative models for science, technology, engineering and mathematics (STEM) graduate education training. SOCRATES will create a new vehicle for graduate training and research that integrates technology domains of robotics, machine learning and computer vision, with social and behavioral sciences (psychology, cognitive science and urban policy planning). The long-term objective is to nurture and mobilize a community of researchers who can draw on sophisticated understanding of social structures and processes in the effective development and deployment of autonomous systems for the benefit of individuals and society. A key challenge of the program is Robotics for Everyday Augmented Living (REAL), semi-automated systems that focus on tasks and work within daily life. The REAL challenge will be emphasized using a heterogeneous testbed of robots on campus (Rutgers Live Lab) to go beyond standard lab-based robot experiments incorporating field work with the campus as a model for society. Emerging applications of robotics are certain to bring significant changes in individuals' lives and profound social impacts, including the future workforce of the nation. Key questions are: What are societal impacts of robotic technology? How can these impacts be predicted and evaluated in order to influence next-generation technology? How can robotics be developed in a socially cognizant manner? While the potential of robotics is often postulated, the realization of ubiquitous robot assistants augmenting an individual's productivity and quality of life has not been realized. This training program seeks to identify the critical societal needs that technology can realistically address to catalyze and guide meaningful research. The interdisciplinary theme of SOCRATES unites technologists and social scientists in order to steer the development of robotics and intelligent systems toward the benefit of society. The program aims to train a new type of professional, the socially cognizant roboticist, through the convergence of the socially aware technologists and the technology-aware social scientist. The proposed theme of (SOCRATES) Socially Cognizant Robotics for a Technology Enhanced Society will catalyze a new paradigm of integrative graduate training at the burgeoning interface of society and intelligent devices. The program will differ substantially from traditional robotics programs by integrating technology disciplines and social sciences towards beneficial societal impact. Multi-year cohorts of over 35 graduate students will be impacted by the program, comprised of 17 NRT-funded students, as well as 20 non-NRT-funded students. The program will be offered at the MS and PhD level. A larger community of MS/PhD students across four major academic units (Engineering, Computer Science, Behavioral Sciences, and Public Policy) will be impacted, bringing the expected total to approximately 100 students benefiting from some component of the program over five years.
 
You can find more details on the project at the NSF page here. 
 
Congratulations to Kristin and her team!
 

August 12th Nicholas Paraskevopoulos to be interviewed by Rutgers Engineers in Action

Rutgers School of Engineering is hosting a YouTube live event on Wednesday, August 12 from 3:30 PM to 4:40 PM. Nicholas Paraskevopoulos is an alumnus of the ECE Department and will be interviewed by ECE student ambassador Atmika Ponnusamy (class of 2021) , a member of the Rutgers Engineering Honors Academy and currently interning at Google.

Dr. Paraskevopoulos is currently the Sector Vice President for Emerging Capabilities Development and Chief Technology Officer for Northrop Grumman Mission Systems.

If you want to learn more about his career trajectory or current work priorities/environment, please sign up to receive the event link at https://soe.rutgers.edu/reg-rueng-alum-in-action

This public event will be broadcasted on YouTube Live. We are please to offer prospective students, parents, teachers, counselors and others a chance to learn about the Rutgers Engineering experience from the perspective of our alumni.

More NSF SII planning grant good news

A team of Rutgers researchers is part of a multi-university initiative that has been awarded a $300K/1yr Spectrum Innovation Initiative (SII) Planning Grant from the NSF. The other universities in this collaborative effort are Virginia Tech, CMU, University of Florida, MIT, Purdue University, UT Austin and University of Washington.The Rutgers team is led by Professor Wade Trappe (PI). The co-PIs from Rutgers include ECE Professor Yingying Chen and Physics and Astronomy Professor Andrew Baker. SII is a recently announced program at NSF which includes funding for a planned $25M/5yrs research center with full proposals due in March 2021. An abstract of the project is given below:

This award is for planning activities for an envisioned center with three primary research activities aligned with national priorities: (1) increase of spectrum efficiency and agility; (2) enabling near real-time spectrum awareness and automated spectrum decision making; and (3) enforcement and security, passive use protection, and safety of radio frequency emissions. The team will carry out and promote research associated with spectrum flexibility and agility that will enable the use of multiple spectral bands, and novel multi-functional waveforms. They will carry out and promote research that provides the ability to manage and access spectrum at a high-level of fidelity and fine granularity while maximizing automation. And they will carry out and promote research that advances the state-of-the-art in spectrum rule enforcement and incumbent user protection, with a particular focus on protecting passive users of spectrum.

Congratulations to Wade, Yingying and Andrew!

More NSF SII planning grant good news

A team of Rutgers researchers is part of a multi-university initiative that has been awarded a $300K/1yr Spectrum Innovation Initiative (SII) Planning Grant from the NSF. The other universities in this collaborative effort are Virginia Tech, CMU, University of Florida, MIT, Purdue University, UT Austin and University of Washington.The Rutgers team is led by Professor Wade Trappe (PI). The co-PIs from Rutgers include ECE Professor Yingying Chen and Physics and Astronomy Professor Andrew Baker. SII is a recently announced program at NSF which includes funding for a planned $25M/5yrs research center with full proposals due in March 2021. An abstract of the project is given below:

This award is for planning activities for an envisioned center with three primary research activities aligned with national priorities: (1) increase of spectrum efficiency and agility; (2) enabling near real-time spectrum awareness and automated spectrum decision making; and (3) enforcement and security, passive use protection, and safety of radio frequency emissions. The team will carry out and promote research associated with spectrum flexibility and agility that will enable the use of multiple spectral bands, and novel multi-functional waveforms. They will carry out and promote research that provides the ability to manage and access spectrum at a high-level of fidelity and fine granularity while maximizing automation. And they will carry out and promote research that advances the state-of-the-art in spectrum rule enforcement and incumbent user protection, with a particular focus on protecting passive users of spectrum.

Congratulations to Wade, Yingying and Andrew!

Emina Soljanin receives NSF Grant for Advancing Quantum Key Distribution

ECE Professor Emina Soljanin is the recipient of a new NSF award for the research project titled "Towards Full Photon Utilization by Adaptive Modulation and Coding on Quantum Links."  This is a two-year $500,000 collaborative effort between Rutgers and UCLA.

 
In this project, Dr. Soljanin and her team advance secure quantum communications.  Secure communication has long been an indispensable part of numerous systems, ranging from the more traditional such as finance and defense to the emerging ones such as the Internet of (battlefield) Things and health data management. The main advantage of private key encryption over the currently popular methods is that as long as the key bits are truly secret, it is provably secure, that is, insensitive to advances in classical and quantum computing algorithms. A Quantum Key Distribution (QKD) protocol describes how two parties, commonly referred to as Alice and Bob, can establish a secret key by communicating over a quantum and a public classical channel when both channels can be accessed by an eavesdropper Eve. For the widespread adoption of QKD, it is mandatory to provide high key rates over long distances. What has emerged as a bottleneck in practice is the inability to maximize the utility of information-bearing quantum states.  This project seeks to solve this inefficiency problem for frequency-time entanglement based QKD. The results will pave the way for practical quantum networks in which multiple Bobs communicate with Alice simultaneously though a multi-channel entanglement distribution in the presence of multiple Eves.
 
You can find more details on the project at the NSF page here. 
 
Congratulations Emina! 

Emina Soljanin receives NSF Grant for Advancing Quantum Key Distribution

ECE Professor Emina Soljanin is the recipient of a new NSF award for the research project titled "Towards Full Photon Utilization by Adaptive Modulation and Coding on Quantum Links."  This is a two-year $500,000 collaborative effort between Rutgers and UCLA.

In this project, Dr. Soljanin and her team advance secure quantum communications.  Secure communication has long been an indispensable part of numerous systems, ranging from the more traditional such as finance and defense to the emerging ones such as the Internet of (battlefield) Things and health data management. The main advantage of private key encryption over the currently popular methods is that as long as the key bits are truly secret, it is provably secure, that is, insensitive to advances in classical and quantum computing algorithms. A Quantum Key Distribution (QKD) protocol describes how two parties, commonly referred to as Alice and Bob, can establish a secret key by communicating over a quantum and a public classical channel when both channels can be accessed by an eavesdropper Eve. For the widespread adoption of QKD, it is mandatory to provide high key rates over long distances. What has emerged as a bottleneck in practice is the inability to maximize the utility of information-bearing quantum states.  This project seeks to solve this inefficiency problem for frequency-time entanglement based QKD. The results will pave the way for practical quantum networks in which multiple Bobs communicate with Alice simultaneously though a multi-channel entanglement distribution in the presence of multiple Eves.
 
You can find more details on the project at the NSF page here. 
 
Congratulations Emina! 

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