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    Prof. Laleh Najafizadeh and students Yi Huang and Li Zhu with IBM Bi CMOS implemented IC
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  • The Visual MIMO research team at work
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    Prof. Laleh Najafizadeh with Yi Huang and Li Zhu working on IC implemented with IBM Bi CMOS
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Research Highlights

Robust, scalable, distributed semantic mapping for search-and-rescue and manufacturing co-robots.

Associate Professor Dario Pompili has won a new NSF award for the project...

Seeing Surfaces: Actionable Surface Properties from Vision

Professor Kristin Dana has won a new NSF award for the project titled "Seeing...

Timely Updating: Principles and Applications

Distinguished Professor Roy Yates has won a new NSF award for the project...

CIF:Small:Collaborative Research:Codes for Storage with Queues for Access

Professor Emina Soljanin has received a new NSF award for the project titled "...

ECE and The Media


Assistant Professor Vishal Patel's research on Active Biometric Authentication...

Janne Lindqvist's News Article on World Password Day

ECE Assistant Professor Janne Lindqvist, whose research focuses on gesture...

Professor Janne Lindqvist's research on smartphone interruptions featured in popular media

Janne Lindqvist's recent work on smartphone interruptions has received a lot of...

Janne Lindqvist's research featured in "Rutgers Today"

Smartphone Interruptions: Are Yours Relentless and Annoying?  A Rutgers study, featured in...

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WINLAB Team Wins prize in Ettus-Xilinx Software Defined Radio Challenge

Submitted by admin on August 20, 2017 - 7:45pm

A team from WINLAB comprising ECE graduate student Bhargav Gokalgandhi, researcher Prasanthi Maddala and Associate Director Ivan Seskar has won the 3rd prize at the RF Network on Chip (RFNoC) and Vivaldo Challenge. This challenge sponsored by Ettus Research and Xilinx Inc. rewards engineers for creating innovative open-source RF Network on Chip (RFNoC) blocks that will add to the library of available open-source blocks for programming FPGAs in Software Defined Radio development and production. The team designed a wide band channel sounder that computes the power delay profile of a multipath channel in a massive multiple antenna system.

Please find more details about the competition here.

Congratulations Bhargav, Prasanthi and Ivan!

Rutgers Team receives NSF EAGER Grant

Submitted by admin on August 20, 2017 - 5:59pm

A team from Rutgers comprising ECE Professors Narayan Mandayam and Janne Lindqvist along with Professor Arnold Glass from Psychology has received an Early Concept Grant for Exploratory Research (EAGER) award from the NSF for a project titled "Simulated and Synthetic Data for Interdependent Communications and Energy Critical Infrastructures." This is a 2 year $200,000 project in collaboration with Florida International University (FIU), with Rutgers' share of the award being $100,000.

As part of this exploratory project, the Rutgers and FIU team will develop new mathematical foundations and computer-based learning theories for generating a wide range of simulated data sets (obtained via down sampling, aggregation of actual data) and fully-synthetic data sets (obtained via emulation and human subject studies) that model interdependence between communications and energy infrastructures. Specifically, the Rutgers team will develop synthetic data for communications critical infrastructure using the ORBIT Testbed as well as human subject studies for prosumer participation in the smart grid under emergencies. The synthetic data generated will be linked to the simulated power system data generated at FIU using transfer learning techniques. These enhanced data sets and associated data building tools will provide large-scale test data related to interdependent critical infrastructures operation.

Congratulations Narayan, Janne and Arnold!

Dario Pompili receives NSF Grant

Submitted by admin on August 15, 2017 - 10:30am

Associate Professor Dario Pompili has won a new NSF award for the project titled "Robust, scalable, distributed semantic mapping for search-and-rescue and manufacturing co-robots." This is a three-year $850,000 collaborative effort between Boston University and Rutgers University. Rutgers' share of this award is $426,161.

The goal of this project is to enable multiple co-robots to map and understand the environment they are in to collaborate among themselves and with human operators in education, medical assistance, agriculture, and manufacturing applications. The first characteristic of this project is that the environment is modeled semantically, that is, it contains human-interpretable labels (e.g., object category names) in addition to geometric data. This is achieved through a novel, robust integration of methods from both computer vision and robotics, and allows easier communications between robots and humans in the field. The second characteristic is that the increased computation load due to the addition of human-interpretable information is handled by judiciously approximating and spreading the computations across the entire network.

Specifically, as part of this project, Dario and his team will propose a new optimization framework for semantic mapping that can handle large, dynamic, uncertain environments under significant measurement errors, studying interactions and information exchanges with humans, and allowing an intelligent sharing of the limited computational resources possessed by the network of co-robots as a whole by enabling approximations and balancing of the computations. The novel developed methods will be evaluated by emulating real-world scenarios in manufacturing and for search-and-rescue operations.

You can find more details on the project at the NSF page here:

Congratulations Dario!

Kristin Dana receives NSF Grant

Submitted by admin on August 15, 2017 - 9:38am

Professor Kristin Dana has won 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.

Congratulations Kristin!

Roy Yates receives NSF Grant

Submitted by admin on August 15, 2017 - 8:47am

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.

As part of this groundbreaking project, Roy will study the foundations of timely updating of information. With the emergence of cyber-physical systems, real-time status updates have become an important and ubiquitous form of communication. Applications that employ vehicular status messages, security reports from computers, homes, and offices, and surveillance video from remote-controlled systems need status updates to be as timely as possible; however, this is typically constrained by limited network resources.This project will examine these real-time status updating systems using Age-of-Information metrics.

You can find more details on the project at the NSF page here.

Congratulations Roy!