Social Computing Research (SCoRe) Lab

Dept. of Computer Science and Engineering
University of South Florida

Director: Dr. Sriram Chellappan

Location: 342 Engineering Building II


Brief Overview                 Research Projects                 Members                 Equipment                 Recent Publications                 Collaborators                


Brief Overview

    The Social Computing Research Lab conducts theoretical and experimental research to overcome critical emerging problems when societies and computing technologies interact closely with each other, while simultaneously enabling new applications. There is a significant emphasis within the group on addressing big-data challenges via effective data mining, data fusion and machine learning techniques, along with security and privacy of designed services and applications. The group's research is strongly multi-disciplinary involving collaborators in computer science, electrical engineering, behavioral sciences, clinical psychiatry, environmental engineering and education. Practical applications of our research are in cyber safety, digital privacy, cyber security, smart healthcare, disaster management, environmental sustenance and more. Students are constantly encouraged to innovate and transition outcomes from the lab to industry.


Current/ Recent Research Projects

  • Multi-disciplinary and Privacy Preserving Techniques to Combat Cyber Risks among Teens
  • - This project integrates data mining techniques, learning algorithms, social science theories and privacy expectations of end users to design context and data driven solutions to model, and detect risks to teens emanating from cyber use. This project is supported by National Science Foundation [Project 1] [Project 2].

  • Assessing Human Behavior from Internet Usage
  • - This project designs techniques for extracting meaningful data emerging from human interactions with emerging technologies like Internet and Smart-Phones, and subsequently design classification algorithms to understand human behavior. Applications of this research are in pervasive mental health care, advancing cyber security and detecting cyber bullying. This project is supported by National Science Foundation [Project].

  • Designing Citizen Science Applications for Water Management
  • - Modern smart-phones come equipped with a number of sensors like accelerometers, gyroscopes, humidity, light-intensity sensors and more. This project designs effective algorithms to enable real-time sensing, transmission and processing of such multi-modal sensor data from a number of devices to enable new citizne science applications in the realm of water management, disaster prediction, environmental sustenance and more. This project is supported by National Science Foundation [Project].

  • A Multi-disciplinary Framework to Model Cyber Criminals
  • - This project integrates theories from criminology with learning algorithms in computer science to understand the evolution of crimes and criminals in cyber space. Applications of this project lie in understanding group behavior of cyber criminals, early detection and intervention for cyber criminals, and early detection of cyber crimes. This project is supported by National Science Foundation [Project].

  • Secure Communications in Wireless Sensor Networks
  • - This project designs and deploys cross-layer algorithms for enhnacing security and privacy of wireless sensor networks operating in the presence of adversaries.

  • Trustworthy, Secure and Privacy Preserved Communications in Vehicular Networks
  • - This project designs algorithms integrating theories from computer sciences (wireless communications, information theory and machine learning) with theories from transportaiton engineering (platoon dispersion and level of service) to enhance trust, security and privacy in emerging intelligent transportation systems.

  • Protecting Information Confidentiality in Critical Infrastructure Systems
  • - This project designs algorithms for protecting confidentiality in modern critical infrastructures like Smart-Grids which are characterized by tight cyber-physical interactions. The algorithms designed seamlessly integrate network topology design, formal methods and control theory.

 

Current Group Members

  • Bharti Goel (PhD)
  •      Wearable Computing Applications
  • Hye-Seon Yi (PhD)
  •      Social Media Analytics
  • Arup Dey (PhD)
  •      Machine Learning for Elder Care
  • Tanvir Bhuiyan (PhD)
  •      Wearable Assisted Activity Recognition
  • Ashik Barua (PhD)
  •      Participatory Sensing
  • Meghna Chaudhary (PhD)
  •      Social Networking
  • Anthony Windmon (PhD)
  •      Signal Processing from Smart-phone Audios for Healthcare
  • Mona Minakshi (PhD)
  •      Participatory Sensing for Environmental Health
  • Ravi Sharma (PhD)
  •      Mining Social Media

Past Members

  • Adel Al Sheri (PhD - 2019)
  • Soheil Sarmadi (PhD - 2018)
  • Sireesha Dadi (MS - 2018)
  • Karthik Siriyala (MS - 2018)
  • Pratool Bharti (PhD - 2017) - R&D Scientist at Communication Concepts Inc.
  • Surya Kamineni (MS - 2017) - Data Scientist at Cross Country Home Services
  • Srinivas Thandu (PhD - 2016) - Software Engineer at Amazon.
  • Anurag Panwar (MS - 2016) - Data Scientist at Samsung Research America
  • Mark Snyder (PhD - 2014) - Software Development Engineer at Microsoft
  • Neelanjana Dutta (PhD - 2013) - Cloud R&D Engineer at Intel
  • Jake Bielefeldt (MS - 2014) - Software Engineer at Sandia Natl. Labs
  • Ashok Bolla (MS - 2014) - Data Scientist at Paypal
  • Doyal Mukherjee (MS - 2014) - Software Engineer at The Cerner Corp.
  • Sai Preethi Vishwanathan (MS - 2014) - Software Engineer at The Cerner Corp.
  • Muhammad Al Mutaz (MS - 2013)
  • Gerry Howser (MS - 2012) - Faculty at Kalamazoo College
  • Raghavendra Kotikalapudi (MS - 2011) - Machine Learning Software Engineer at Google

Equipment

  • Computing
  •     Nvidia GPU Cluster, Dell T3600 workstations, Dell Latitude E 6330 Laptops, MacBook Pro Laptops

  • Embedded Devices
  •     Gumstix motes, Crossbow motes, LabRat robots

  • Wearable Devices
  •     Shimmer3 GSR Development Kits, Moto Sport Smartwatches

  • Smart-Phones
  •     Samsung GALAXY S3, S4, S5, S6, Motorola Atrix 2, iPhone 6

  • Software
  •     MATLAB, SAS, Intel Math Kernel Library
 

Selected Recent Publications

  • TussisWatch: A Smart-phone System to Identify Cough Episodes as Early Symptoms of Chronic Obstructive Pulmonary Disease and Congestive Heart Failure
  •      IEEE Journal of Biomedical and Health Informatics (J-BHI), Vol 23/4, July 2019.  [.pdf]

  • HuMAn: Complex Activity Recognition with Multi-modal Multi-positional Body Sensing
  •      IEEE Transactions on Mobile Computing (TMC), Vol 18/4, April 2019.  [.pdf]

  • Leveraging Smartphone Sensors to Detect Distracted Driving Activities
  •      in IEEE Transactions on Intelligent Transportation Systems (T-ITS), Oct 2018.  [.pdf]

  • Leveraging Smart-Phone Cameras and Image Processing Techniques to Classify Mosquito Species
  •      15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (MobiQuitous), New York, Nov 2018.  [.pdf]

  • Watch-Dog: Detecting Self-Harming Activities from Wrist Worn Accelerometers
  •      IEEE Journal of Biomedical and Health Informatics (J-BHI), Vol 22/3, May 2018.  [.pdf]

  • On Detecting Chronic Obstructive Pulmonary Disease (COPD) Cough Using Audio Signals Recorded from Smart-Phones
  •      Proc. of 11th International Conference on Health Informatics (HealthInf), Funchal, Portugal, Jan 2018.  [.pdf]

  • A Statistical Framework to Forecast Duration and Volume of Internet Usage Based on Pervasive Monitoring of NetFlow Logs
  •      Proc. of IEEE International Conference on Advanced Information Networking and Applications, Krakow, May 2018  [.pdf]

  • Can You Get into the Middle of Near Field Communication?
  •      Proc. of IEEE Conference on Local Computer Networks (LCN), Singapore, Oct 2017.  [.pdf]

  • Leveraging Multi-modal Smartphone Sensors for Ranging and Estimating the Intensity of Explosion Events
  •      Special Issue on Emerging Technologies in Pervasive Sensing, Journal of Pervasive and Mobile Computing (PMC), Vol 20, Sep 2017.  [.pdf]

  • Multimodal Wearable Sensing for Fine-Grained Activity Recognition in Healthcare
  •      IEEE Internet Computing (IC), Vol 19/5, Sep-Oct 2015.   [.pdf]

  • Associating Internet Usage with Depressive Behavior among College Students
  •      IEEE Technology & Society Magazine, Volume 31, No. 4, Winter 2012.   [.pdf]
         Press Release: NYTimes, MSNBC, Times of India, The Jerusalem Post, ScienceDaily, Slashdot, ACM TechNews, IEEE News, PC World, CNET, TIME, Forbes, PsychCentral


  • Click Here for a Complete List

Collaborators