Active Funded Research

Active Funded Research


Active Research

 

REU Supplement: PFI: AIR-TT: Market Driven Innovations and Scaling up of Twitris - A System for Collective Social Intelligence

Description: REU Supplement: PFI: AIR-TT: Market Driven Innovations and Scaling up of Twitris - A System for Collective Social Intelligence

Research Funding Dates: April 1, 2016 - March 31, 2018

Awarded Through: NSF, Miscellaneous

Amount Awarded:$12,000

Awarded To: Amit Sheth

 

Employee and Job Search Semantic Engine:  Phase I

Description:  Employee and Job Search Semantic Engine:  Phase I

Research Funding Dates: January 1, 2016 – April 30, 2018

Awarded Through: Universal Freelancer dba EZcruiting

Amount Awarded: $30,000

Awarded To: Principal Investigator (PI) Amit Sheth

 

Autonomous Aerial Vehicles for Force Health Protection Response

Description: Autonomous Aerial Vehicles for Force Health Protection Response

Research Funding Dates: January 5, 2017 - April 30, 2017; and January 5, 2017 - April 30, 2018

Awarded Through: Universal Energy Systems, Inc.

Amount Awarded: $7,800; and $59,200

Awarded To: John Gallagher

 

 Center for Continuous Cybersecurity Education and Training (C3ET) in West Ohio

Description: Center for Continuous Cybersecurity Education and Training (C3ET) in West Ohio

Research Funding Dates: July 1, 2016 - June 30, 2018

Awarded Through: Ohio Department of Higher Education

Amount Awarded: $541,294

Awarded To: Junjie Zhang, Vance M. Saunders, Adam Bryant, Marty Emmert, and Jiafeng Xie

 

IIS: Medium: Context-Aware Harrassment Detection on Social Media

Description: IIS: Medium: Context-Aware Harrassment Detection on Social Media

Research Funding Dates: September 1, 2015 to August 31, 2018

Awarded Through: NSF, Miscellaneous

Amount Awarded: $925,104; and $16,000

Awarded To: Principal Investigator (PI) Amit Sheth Co-Principal Investigator (Co-PI) Krishnaprasad Thirunarayan, Valerie L. Shalin

 

EAGER: Collaborative Research: A New Science of Visual Experience

Description: The essence of human experience is interacting with the natural and man-made environments through the five human senses, and through vision in particular. The objective of this EArly-concept Grant for Exploratory Research (EAGER) project is to build analytical foundations for a new science of visual experience that will bridge basic approaches from cognitive science and systems engineering. Specifically, the research will build mathematical and computational models of a human navigating a three dimensional space such as a factory, museum, or retail store. The idea is to gain insights into the limits on observability and controllability in human-technology systems, and to improve the user's situational awareness. If the research is successful, researchers will be able to describe situations in terms of possibilities for action and access to information. Such quantitative tools will allow engineers to design environments to achieve outcomes such as increased focus, improved safety, better wayfinding, and improved experience. In time, it might be possible to engineer interactive environments that adapt to the personal attributes and identities of the humans that inhabit them. The results of the research have the potential to be used by many disciplines such as engineering, business, architecture, psychology, cognition, and human factors. The specific focus of this grant will be on developing a general set of analytical models that emerge from the analysis of a variety of context-specific human-environment interactions (e.g., nurse in CCU, shopper in a retail store). With a solid grounding in the basic psychology of Perception-Action, the analytical models will integrate three-dimensional spatial relationships with the human eye's field of vision and the physical attributes of a human. Most significantly, the research will consider complex dynamics resulting from human movement in the space, with all the attendant changes in visual angles, and the appearance and disappearance of visual obstacles. Human performance will be empirically examined in a Virtual Environment in order to validate the analytical metrics of visual experience.

Research Funding Dates: 09/01/2015 - 08/31/2017

Awarded Through: NSF

Amount Awarded: $195,845

Awarded To: PI: Pratik Parikh; Co-PIs: Thomas Wischgoll, John Flach

 

REU Supplement: IIS: Medium: Context-Aware Harrassment Detection on Social Media

Description: REU Supplement: IIS: Medium: Context-Aware Harrassment Detection on Social Media

Research Funding Dates: September 1, 2015 to August 31, 2018

Awarded Through: NSF, Miscellaneous

Amount Awarded: $16,000

Awarded To: Principal Investigator (PI) Amit Sheth

 

TWC SBE: Medium: Context-Aware Harassment Detection on Social Media

Description: The aim of this project is to develop comprehensive and reliable context-aware techniques (using machine learning, text mining, natural language processing, and social network analysis) to glean information about the people involved and their interconnected network of relationships, and to determine and evaluate potential harassment and harassers. An interdisciplinary team of computer scientists, social scientists, urban and public affairs professionals, educators, and the participation of college and high schools students in the research will ensure wide impact of scientific research on the support for safe social interactions.

Research Funding Dates: October 1, 2015 to August 31, 2018

Awarded Through: NSF

Amount Awarded: $925,104

Awarded To: Principal Investigator (PI) Amit Sheth, Co-Principal Investigator (Co-PI) Valerie Shalin, T.K. Prasad

Website: Context Aware Harassment Detection of Social Media

 

REU Site: Data-Driven Cyber Security Research

Description: REU Site: Data-Driven Cyber Security Research

Research Funding Dates: March 1, 2016 – February 28, 2019

Awarded Through: NSF, Miscellaneous

Amount Awarded: $359,772

Awarded To: Principal Investigator (PI) Junjie Zhang, Bin Wang

 

Hazard SEES: Social and Physical Sensing Enabled Decision Support for Disaster Management and Response

Description: In this project the team will design novel, multi-dimensional cross-modal aggregation and inference methods to compensate for the uneven coverage of sensing modalities across an affected region. By assimilating data from social and physical sensors and their integrated modeling and analysis, methodology to predict and help prioritize the temporally and conceptually extended consequences of damage to people, civil infrastructure (transportation, power, waterways) and their components (e.g. bridges, traffic signals) will be designed. The team will also develop innovative technology to support the identification of new background knowledge and structured data to improve object extraction, location identification, correlation or integration of relevant data across multiple sources and modalities (social, physical and Web).

Research Funding Dates: July 1, 2015 to July 31, 2019

Awarded Through: NSF and WSU

Amount Awarded: $1,975,000 (NSF) $787,500 (WSU)

Awarded To: Principal Investigator (PI) Parthasanthy (OSU), Amit Sheth, Co-Principal Investigator (Co-PI) Liu (OSU), Kubatko (OSU), Valerie Shalin, T.K. Prasad

Website: Hazard SEES

 

 Collaborative Research: Engaged Student Learning: Re-conceptualizing and Evaluating a Core Computer Science Course for Active Learning and STEM Student Success

Description: Collaborative Research: Engaged Student Learning: Re-conceptualizing and Evaluating a Core Computer Science Course for Active Learning and STEM Student Success.

Research Funding Dates: August 15, 2017 - July 31, 2020

Awarded Through: NSF, Miscellaneous

Amount Awarded: $81,308

Awarded To: Adam Bryant

 

Assessing the Reliability of Medical Information on Online Social Media

Research Funding Dates: 05/01/2015 -

Awarded Through: WSU Research Initiation Grant

Amount Awarded: $24,426

Awarded To:  PI: Daniel Asamoah; Co-PI: Derek Doran

 

The Fels Longitudinal Study and Related Projects

Description: The Fels Longitudinal Study is the world's largest and longest running study of human development, growth, body composition and aging. The LHRC draws on the strength of the Fels Longitudinal Study and other population-based studies past and present. The Fels Study was originally designed to study child growth and development. Physical growth, maturation and the psychological development of children were early key research areas of interest in the Fels Longitudinal Study. Today, the Fels Longitudinal Study focuses on physical growth, skeletal maturation, body composition, risk factors for cardiovascular disease and obesity, skeletal and dental biology, longitudinal biostatistical analyses and aging.

Research Funding Dates: 01/01/2016

Awarded Through: BSOM

Amount Awarded: $3,000

Awarded To: Investigator: Tanvi Banerjee

Additional Information: