Department Labs

Communications and Signal Processing Laboratory (CSPL)

Director:  Prof. Athina Petropulu
Location: 96 Frelinghuysen Road, Room 532, Piscataway, NJ 08854
Email:  athinap @ rutgers.edu

CSPL focuses on research in theoretical issues in statistical signal processing, system modeling, system identification. Applications of interest include wireless communications, networking, radar systems, biomedicine. Recent project include cooperative approaches for low power wireless communications, physical layer security, mobile beamforming, and compressive sensing based MIMO radar.

 

Cyber Physical Systems (CPS) Lab

Director:  Prof. Dario Pompili
Location: 96 Frelinghuysen Road, Room 615, Piscataway, NJ 08854
Email: dario.pompili @ rutgers.edu

The Cyber Physical Systems (CPS) Laboratory's overarching mission is to propose novel sensing paradigms to transform raw sensed heterogeneous data into valuable information (by giving semantic meaning to the collected data) and, finally, into knowledge through information fusion and integrat ion. These paradigms will apply to those distributed systems that need to timely react to sensor information with an effective action such as cyber-physical systems, which feature a tight combination of, and coordination between, the system’s computational and physical elements. The significance of the research is to leverage the acquired knowledge to broaden the potential of cyber-physical systems in several dimensions, including: augmentation of human capabilities, understanding of human activities, coordination of heterogeneous (infrared) cameras, operation in dangerous or inaccessible environments, and efficiency.

 

Coding and Securing Information (CSI) Lab

Location: 96 Frelinghuysen Road, Room 733, Piscataway, NJ 08854
 
At CSI Lab, we are interested in solving reliability, security and privacy problems arising from communicating, storing and processing large amounts of data in distributed systems, using tools from information theory and coding theory. Our current research projects include:
  • Private information retrieval and search in distributed systems.
  • Distributed algorithms and codes for the synchronization and deduplication of coded data.
  • Secure machine learning algorithms with information theoretical guarantees

 

Data Analysis and Information Security (DAISY) Lab

Location: 96 Frelinghuysen Road, Room 507, Piscataway, NJ 08854
 

As mobile device and technologies continue to have an important impact on our life and eventually become a part of our social fabric, the information infrastructure will increasingly become the tempting targets for malicious attacks. Furthermore, with the huge amount of information transmitted over the networks and eventually displayed in the Internet, the main question that people asked about is what should constitute “fair use” of the information. The Data Analysis and Information SecuritY (DAISY) Laboratory focuses on both addressing the problems in information security, system privacy, and data integrity using statistical approaches and machine learning techniques, as well as building test beds to facilitate research in these areas.

Current Research Areas:

  • Cyber Security and Privacy
  • Mobile Healthcare and its Security Issues
  • Mobile Computing and Sensing
  • Connected Vehicles

 

Human-Computer Interaction and Security Engineering Laboratory

Director:   Prof. Janne Lindqvist
Location:  96 Frelinghuysen Rd., Room 529, Piscataway, NJ 08854
Email:       janne.lindqvist @ rutgers.edu
 
This laboratory focuses on world-class graduate and undergraduate research and education at the interface of security engineering, mobile computing and human-computer interaction. Research approaches include mobile app prototyping, user studies, interaction design, machine learning, secure protocol design, and signal processing, among others. The laboratory is active contributor in terms of scientific publications, and has enjoyed substantial attention from media around the world. 

 

Information, Networks, and Signal Processing Research (INSPIRE) Laboratory

Director:  Prof. Waheed U. Bajwa
Location: 96 Frelinghuysen Rd., Room 729, Piscataway, NJ 08854
Email:      waheed.bajwa @ rutgers.edu

Research conducted at the Information, Networks, and Signal Processing Research (INSPIRE) Lab provides a fundamental mathematical understanding of and theoretically optimal, computationally efficient, and algorithmically robust solutions for some of the most pressing problems arising in information processing—an umbrella term that subsumes mathematical signal processing, high-dimensional statistics and machine learning—and networked systems, such as (online) social networks, wireless sensor networks, communication networks, multiagent systems, and brain networks.
 

Integrated Circuits and NeuroImaging Laboratory

Director:  Prof. Laleh Najafizadeh
Location: 96 Frelinghuysen Rd., Room 536, Piscataway, NJ 08854
Email:      laleh.najafizadeh @ rutgers.edu
 
This a multidisciplinary research group that combines techniques in microelectronics and signal processing to address the existing problems in a variety of domains including neuroscience, cognitive rehabilitation, low-power systems and biosensors.
 
Research Areas:

a. Neuroimaging: Functional Brain Imaging, Diffuse Optical Brain Imaging, Brain Connectivity, Cognitive Neuroscience, Brain Computer Interface, Cognitive Rehabilitation; and
b. Analog, Mixed-Signal, VLSI, and mmw Circuit Design: Ultra Low-Power Circuits for Biomedical Applications, Ultra Fast Circuits, System on Chip.

 

NanoBioTechnology Lab

Director:  Prof. Mehdi Javanmard
Location: 94 Brett Road, Room 112, Piscataway, NJ 08854
Email:      mehdi.javanmard @ rutgers.edu
 
The NanoBioTechnology Lab applies nanotechnology with biomedical applications to solve current health and medical problems. The high cost of diagnostic exams in the clinical setting has resulted in a healthcare crisis both nationally and globally. The lack of sensitivity in current state-of-the-art biosensing platforms used in the clinical setting has resulted in slow and expensive diagnostic exams. This makes it economically unfeasible to regularly screen patients for a wide panel of biomarkers, making impossible the diagnosis of diseases at early stages while still curable. By making use of the advantages offered by micro and nanotechnologies, we aim to develop sensing platforms which will decrease cost, increase assay speed, and improve limit of detection in biomolecular assays.
 

Tele-Rehabilitation Institute

Director :  Prof. Grigore (Greg) Burdea
Location: 96 Frelinghuysen Road, Room 735, Piscataway, NJ 08854
Email:      burdea @ jove.rutgers.edu
Phone:     (848) 445-5309

Tele-rehabilitation is the provision of therapy at a distance. To realize its full potential, it needs better computing and communication technology and well as better prepared medical professionals.

The Tele-rehabilitation Institute mission is three-fold, in areas of Research, Clinical Development and Education:
       • Research - to develop highly innovative technology that allows fun and efficacious therapy to occur in the home. This alleviates the need to go to clinics, while therapists remotely monitor and adjust your home treatment;
     • Clinical Development - to measure the efficacy and improve the new systems based on patient clinical use in a controlled and safe environment;
       • Education - to form the new generation of therapists that understand and fully exploit the capabilities of the new Tele-rehabilitation therapy.

 

Visualization Lab (Vizlab)

Director :  Prof. Deborah Silver
Email:      dsilver @ rutgers.edu
 
Our research is in the area of scientific visualization, computer graphics, volume graphics, medical visualization, and acoustic imaging.
 
As we rush into the era of parallel computing, scientific simulations are capitalizing to produce ultrascale datasets. To help analyze datasets extending to the order of thousands of petabytes, Vizlab is currently focusing on tools to sift and detect activities of interest in such huge datasets. Some of our latest projects include automatically detecting activities of interest and tracking  groups as well as interactions betweens different groups in a simulation.
 
Visualization involves projecting data into alternate (parameter) spaces to isolate or identify regions of interest. Tracking them to study their evolution forms the next step culminating in the formulation of reduced models to explain & quantify the phenomenon generating the data. These advanced methods were transparently applied to the graphical visualization of data as varied as plasma physics of the Tokamak (PPPL) and the jet engine unstart problem.