Professor Kristin Dana has been awarded a new NSF award for the project titled "Seeing Surfaces: Actionable Surface Properties from Vision." This is a three year $500,000 collaborative effort between Rutgers University (Kristin Dana, PI) and Drexel University. Rutgers' share of this award is $249,931.00.
As part of this project, Kristin and her team will develop models and algorithms for estimating actionable, physical properties of surfaces from their appearance for applications in scene understanding, robotic action planning, and efficient visual sensing. The research will address the fundamental question of how computer vision can anticipate the physical properties of a surface, laying the foundation for computational vision-for-action. The research activities are centered on four specific aims: 1) large-scale data collection of actionable physical properties and appearance measurements of everyday surfaces, 2) derivation of prediction models for deducing physical properties from local surface appearance, 3) integration of global semantic context including object and scene information, and 4) development of efficient appearance-capture optics and hardware for use in novel physics-from-appearance sensing.
You can find more details on the project at the NSF page here.
Distinguished Professor Roy Yates has won a new NSF award for the project titled "Timely Updating: Principles and Applications." This is a three year $500,000 project.
Professor Emina Soljanin has received a new NSF award for the project titled "Codes for Data Storage with Queues for Data Access." This is a three year $500,000 collaborative effort between Rutgers University (Emina Soljanin, PI) and Texas A&M University. Rutgers' share of this award is $309,236.
As part of this project, Emina and her team will develop efficient algorithms for distributed storage and access of large files. Large volumes of data, which are being collected for the purpose of knowledge extraction, have to be reliably, efficiently, and securely stored. Retrieval of large data files from storage has to be fast (and often anonymous and private). Large-scale cloud data storage and distributed file systems, e.g., Amazon EBS and Google FS, have become the backbone of many applications such as web searching, e-commerce, and cluster computing. Cloud services are implemented on top of a distributed storage layer that acts as a middleware to the applications, and also provides the desired content to the users, whose interests range from performing data analytics to watching movies. This project focuses on efficient data access in distributed file systems that employ erasure codes for reliable and efficient storage.
You can find more details on the project at the NSF page at http://"https://www.nsf.gov/awardsearch/showAward…".
Professor Marco Gruteser has been elected chair of the Association for Computing Machinery (ACM) Special Interest Group on Mobile Computing (ACM SIGMOBILE). ACM SIGMOBILE is the international professional organization for scientists, engineers, executives, educators, and students dedicated to all things mobile.
As exemplified by the inaugural test-of-time awards, its members have pioneered: medium access mechanisms that underpin Wi-Fi and IoT sensor communications, positioning systems used in factories and every smart phone, file system caching techniques that inspired Dropbox, as well as congestion control and mesh networking techniques for faster and more ubiquitous wireless broadband data access.
SIGMOBILE also sponsors and is responsible for a series of highly selective international conferences in the field of mobile computing, including MobiCom, MobiSys, MobiHoc, UbiComp, and Sensys.
Congratulations on this recognition of professional achievement, Marco!
Professor Mehdi Javanmard is the recipient of a DARPA award for the project titled "The Proteomic Smartpatch Phase IB: Transcutaneous Monitoring of Molecular Biomarkers in Blood Using Flexible and Natural Substrates." This is a six month $200,000 collaborative effort between Rutgers University (Mehdi Javanmard, PI) and University of Pennsylvania (Mark Allen, Co-PI). Rutgers' share for this award is $100,000.
As part of this project, Mehdi and his team will continue development of a wearable biosensing platform whose purpose is to continuously monitor biomarkers of inflammation in the bloodstream in response to stimulation of the peripheral nervous system for treatment of chronic inflammatory diseases. This project is part of DARPA's effort to fulfill the vision of the Agency’s Electrical Prescriptions (ElectRx) program, which has as its goal the development of a closed-loop system that treats diseases by modulating the activity of peripheral nerves. The teams will initially pursue a diverse array of research and technological breakthroughs in support of the program’s technical goals. Ultimately, the program envisions a complete system that can be tested in human clinical trials aimed at conditions such as chronic pain, inflammatory disease, post-traumatic stress and other illnesses that may not be responsive to traditional treatments.
The average computer user has 27 passwords, and it can be tough to keep track of them all. But our devices themselves contain biometric sensors that can read all kinds of identifying information about us. That could put an end to the password. CBS reporter Brook Silva-Braga explores Assistant Professor Vishal Patel's research on Active Biometric Authentication.
Enjoy the video at http://www.cbsnews.com/videos/will-biometric-active-authentication-help-...
Distinguished Professor Athina Petropulu has won the 2017 Electrical and Computer Engineering Department Heads Association (ECEDHA) Diversity Award.
The Diversity Award is given to individuals or departments in recognition of proactive efforts to increase cultural, ethnic, and gender diversity within the ECE student body and among ECE faculty, that go well beyond and above the normal institutional recruiting practices. The award recognized Professor Petropulu’s leadership in continually identifying and enhancing opportunities for women and underrepresented minorities nationwide in the field of electrical and computer engineering, through recruiting, mentoring, and advocating.
The award was given to Prof. Petropulu at the ECEDHA Awards Banquet during the 2017 ECEDHA Annual Conference, which was held at the Hilton Sandestin Beach Resort & Spa in Miramar Beach, Florida (please see attached a photo from the awards banquet where Professor Petropulu is seen with ECEDHA President Prof. Khalil Najafi, EECS Chair, University of Michigan (left), and Prof. Zhihua Qu, ECEDHA Awards Committee Chair and Chair of ECE at University of Central Florida (right)).
Congratulations on this wonderful recognition, Athina!
Assistant Professor Mehdi Javanmard is the recipient of a new NSF award for the project titled "A Microfluidic-CMOS Cross-cut Approach Enabling Tri-Modal Biorecognition for Highly Accurate Viral Diagnostics." This is a three year $450,000 collaborative effort between Rutgers University (<b>Mehdi Javanmard</b>, PI) and Princeton University (<b>Kaushik Sengupta</b>, PI). Rutgers' share for this award is $225,000.
As part of this project, Mehdi and his team will develop a finger-stick sized instrument whose purpose is to rapidly diagnose viral infections in blood. The proposed point-of-use device can be utilized for rapidly screening subjects at airports, emergency rooms, or other crowded areas where the potential to spread viral disease is high. The proposed innovation is based on miniaturization of sample, reagent, and buffer handling in microfluidics using low power electronically actuated micro-valves, reconfigurable electroosmotic pumps, and multiplexed detection of fluorescence-labeled proteins and nucleic acids in silicon ICS with integrated nanoplasmonic filters that remove the necessity of complex optical scanners, lenses, collimators. The platform is envisioned to be generic and reconfigurable and the pre-functionalized cartridges can be swapped out for different infectious diseases. Specifically, the proposed research aims to investigate and develop multi-modal detection capability through electronically actuated fluidic valves and pumps enabling on-chip immunoassays for protein detection and on-chip nucleic acid purification, amplification, and hybridization for viral load determination as well as light guiding, packaging and additive manufacturing techniques for enabling a sample-to-answer platform.
Congratulations on this success, Mehdi!