Current Research Projects

Research in IST cuts across traditional boundaries to drive interdisciplinary discovery and innovation. Our research is sponsored by a variety of national and international agencies, and we collaborate with diverse groups of scholars within and beyond Penn State. Explore our funded projects to see how IST's transformative research is addressing the world's most complex problems at the intersection of information, technology, and society.

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Researcher: Benjamin Hanrahan
Sponsoring Agency: National Science Foundation
This project studies the ways that algorithmic management, using digital tools to automate and remotely manage workers, may negatively impact workers and their rights. The research will look specifically at ride-hailing platforms, which are rapidly replacing traditional taxi services. Researchers will develop an experimental ride-hailing platform that gives drivers and passengers control over parameters that impact algorithmic outcomes, as a means to understand and interact with the platform. Learn more...
Research Areas: Artificial Intelligence and Big Data, Human-Computer Interaction, Social and Organizational Informatics
Term: -
Researcher: Prasenjit Mitra
Sponsoring Agency:
This project investigates the cognitive and motivational factors that support deep engagement with teacher’s data and which drive change. Specifically, we are investigating three outcomes: change in teachers’ beliefs regarding classroom discussion, change in teachers’ knowledge of effective strategies, and change in teachers’ behavior regarding the implementation of these strategies. Learn more...
Research Areas: Artificial Intelligence and Big Data, Social and Organizational Informatics
Term: -
Researcher: John M. Carroll, Zihan Zhou, Mary Beth Rosson
Sponsoring Agency: National Library of Medicine
The project will investigate prosthetic support for people with visual impairment (PVI) that integrates computer vision-based prosthetics with video-mediated human-in-the-loop prosthetics. We will employ a human-centered design approach, identifying a set of key assistive interaction scenarios that represent authentic needs and concerns of PVIs. Learn more...
Research Areas: Artificial Intelligence and Big Data, Human-Computer Interaction, Social and Organizational Informatics
Term: -
Researcher: Zhenhui (Jessie) Li
Sponsoring Agency: National Science Foundation
This project develops novel data mining techniques to help people uncover the complicated correlations in the big urban data. Ultimately, this project strives to advance the techniques in urban computing, a nascent interdisciplinary research field that addresses the challenges and opportunities in the fast-evolving urban environments. Learn more...
Research Areas: Artificial Intelligence and Big Data, Social and Organizational Informatics
Term: -
Researcher: Andrea Tapia
Sponsoring Agency: National Science Foundation
The project investigates the use of big data analysis techniques for classifying crisis-related data in social media with respect to situational awareness categories, such as caution, advice, fatality, injury, and support, with the goal of helping emergency response teams identify useful information. Learn more...
Research Areas: Artificial Intelligence and Big Data, Human-Computer Interaction, Social and Organizational Informatics
Term: -
Researcher: Suhang Wang, Dongwon Lee
Sponsoring Agency: National Science Foundation
This project explores effective labeled data generation via generative adversarial learning and proposes novel approaches based on generative adversarial learning for effective labeled data generation to facilitate deep learning with limited label information, investigates associated fundamental research issues and develops effective algorithms. Learn more...
Research Areas: Artificial Intelligence and Big Data, Human-Computer Interaction, Privacy and Security, Social and Organizational Informatics
Term: -
Researcher: Peng Liu
Sponsoring Agency: National Science Foundation
This research project seeks to develop new techniques and tools for insecurity analysis of middleware on mobile platforms (MoMP) like Android Framework and consequently lead to more secure and trustworthy computing environments for the huge number of smartphone and Internet-of-Things (IoT) device users. The project will develop new architectural designs, algorithms and techniques for precise and automated insecurity analysis of MoMP. Learn more...
Research Areas: Privacy and Security, Social and Organizational Informatics
Term: -
Researcher: Zihan Zhou
Sponsoring Agency: National Science Foundation
This project develops a novel data-driven framework for structure discovery in computer vision, leveraging the availability of massive data and recent advances in machine learning techniques. The techniques developed in this project can be applied to a wide spectrum of real-world applications such as 3D reconstruction of man-made environments, virtual and augmented reality, and indoor rescue robots. Learn more...
Research Areas: Artificial Intelligence and Big Data, Social and Organizational Informatics
Term: -
Researcher: Anna Squicciarini, Peter Forster
Sponsoring Agency: National Science Foundation
This project aims to build mathematical and data-driven models to understand the dynamics of extremist groups at scale, the patterns of their influence, and integrated micro (individual-level) and macro (group-level or system-level) data-driven models that can guide future interventions. This project provides a greater understanding of users' behavioral patterns and social dynamics related to online extremism. Learn more...
Research Areas: Artificial Intelligence and Big Data, Privacy and Security, Social and Organizational Informatics
Term: -
Researcher: Aiping Xiong, Dongwon Lee
Sponsoring Agency: National Science Foundation
This project will use social media data to examine the memory illusion with online information, and to understand how it is associated with people's trust in information on social media. Better understanding on the extent and impact of the memory illusion phenomenon using big data will inform machine-learning approaches to better measure trust in information with an additional human information-processing perspective. Learn more...
Research Areas: Artificial Intelligence and Big Data, Privacy and Security, Social and Organizational Informatics
Term: -
Researcher: Dongwon Lee, Aiping Xiong
Sponsoring Agency: National Science Foundation
This funding establishes a new Research Experiences for Undergraduates (REU) Site at Pennsylvania State University. An interdisciplinary team of experienced faculty mentors will guide undergraduate students in summer research projects focused on applying machine learning methods to solve cybersecurity problems, particularly cyber-attacks. Learn more...
Research Areas: Artificial Intelligence and Big Data, Privacy and Security, Social and Organizational Informatics
Term: -
Researcher: Sarah Rajtmajer, Aiping Xiong
Sponsoring Agency: Quantitative Scientific Solutions LLC
The proposed work will develop tools to provide users with the information and the backend support they need to reclaim control of their experience on social media. The Sociolinguistic Information Filtering Tool (SIFT) will consist of a desktop extension and associated mobile app initially based on machine learning, natural language processing and network theory techniques. Motivated by recent work understanding human information processing in the context of warning mechanisms, the project will build these tools iteratively, with humans-in-the-loop via in-depth user studies. Proposed work will evaluate and refine algorithmic approaches for account filtering and user-initiated bulk action toward automated, malicious, or otherwise unwanted accounts. Learn more...
Research Areas: Artificial Intelligence and Big Data, Privacy and Security, Social and Organizational Informatics
Term: -
Researcher: Suhang Wang
Sponsoring Agency: National Science Foundation
This project proposes novel principles and mechanisms for scalable and interpretable graph neural networks to facilitate the adoption of GNNs on critical domains, investigates associated fundamental research issues and develops effective algorithms. The project offers the first comprehensive investigation on these directions, and the designed novel methodologies and tasks will deepen our understanding on the inner working mechanisms of GNNs and contribute to real-world applications. Learn more...
Research Areas: Artificial Intelligence and Big Data, Social and Organizational Informatics
Term: -
Researcher: Carleen Maitland
Sponsoring Agency: National Science Foundation
This IRES SITTE project will train 18 U.S. master's students in multicriteria design of and policies for IoT systems with the aim of making local IoT data available to global data scientists. This research will highlight current trends in Rwandan IoT use, system vulnerabilities, as well as national and organizational policies that may affect data sharing practices and hinder access by Big Data scientists. Learn more...
Research Areas: Artificial Intelligence and Big Data, Social and Organizational Informatics
Term: -