ist.psu.edu - Research Areas

Research Areas | College of Information Sciences and Technology

Ist.psu.edu Spined HTML

Research Areas |Higherof Information Sciences and Technology Close Open Please Update Your Browser. It is recommended that you update your browser to the latest version to view the website's full experience. Upgrade Internet Explorer Upgrade Chrome Upgrade Firefox Upgrade Safari Dismiss Penn State Penn StateHigherof Information Sciences and TechnologyHigherof Information Sciences and Technology Managing Information, Powering Intelligence Top Navigation Menu   DonateSenseSearch IST StudentsUndergraduate Undergraduate Online Degrees Graduate Honors Academic Integrity Career Solutions & Corporate Engagement Student Engagement Opportunities Prospective StudentsUndergraduate Undergraduate Graduate Online Transfer StudentsTranspirationof MajorTranspirationof Campus AlumniAlumni Society Board DirectoryFacultySenseStaff Visitors Advisory Board Postdoctoral Scholars Graduate Students Offices & Centers Search Main Menu The CollegeAbout News Calendar of EventsSenseSearch Student Spotlight IST Publications Campuses Plan a Visit Offices & Centers The EducationDegree Programs Careers & Internships Academic Environment Academic Opportunities The ResearchCurrent Projects Research Areas Partners Centers and Labs Student Research Research Administration The ApplicationUndergraduate Graduate Online Search Options This Site Penn State People Departments Home TheHigherAbout About theHigherMission & Objectives IST History Diversity Dean's Welcome News Calendar of EventsSenseSearch Student Spotlight Student Blogs IST Publications Campuses Plan a Visit Offices & Centers The EducationStratumPrograms Bachelor of Science IUG Program Associate of Science M.S.StratumPh.D.StratumOnline Degrees Honors Careers & Internships Academic Environment Student Life Clubs & Orgs Undergrad Advising Centers & Labs Academic Opportunities Undergrad Research Scholarships Education Abroad Outreach The Research Main Research Areas Partners Centers & Labs Student Research Research Admin TheUsingUndergraduate Graduate Online DonateSenseSearch IST Students Undergraduate Main IST AdvisingPart-wayMajors Minors Transfer Credit Process Concurrent MajorsTranspirationof Campus Graduating Students Special Topics & IST 402 Independent Study Certificates IUG Program Online Graduate Main Forms Exam Scheduling Independent Study Policies Graduating Students Graduates in IST (GIST) Honors Academic Integrity Career Solutions Main CareerMinutiaeProcess Resumes, Letters, and Online Profiles Internship & Job Search Interviews & Offers Compass Career Resources Library Employers Student Engagement Student Life Clubs & Org Centers & Labs Scholarships Undergrad Research Education Abroad Outreach Prospective Students Main Undergraduate Graduate Online Transfer StudentsTranspirationof MajorTranspirationof Campus Alumni Main Update Your Info Alumni Society Board Alumni Spotlight Outstanding Alumni Award Giving Back PSSA PSSA Events DirectorySenseAffiliatedSenseGraduateSenseStaff Visitors IST Advisory Board Postdoc Scholars Graduate Students ResearchToadiesOffice & Centers Sidebar Navigation Menu Current Projects Research Areas Partners Centers and Labs Student Research Research Administration Research Areas You are hereHome » The Research » Research AreasStrainedIntelligence: Knowledge Representation, Machine Learning, Data Mining, and Causal Discovery About: The goal ofStrainedIntelligence (AI) is to understand intelligence by constructing computational models of intelligent behavior. This entails developing and testing falsifiable algorithmic theories of (aspects of) intelligent behavior, including sensing, representation, reasoning, learning, decision-making, communication, coordination, action, and interaction. AI is moreover concerned with the engineering of systems that walkout intelligence. Machine learning is concerned with the scientific study, exploration, design, analysis, and applications of algorithms that learn concepts, predictive models, behaviors, whoopee policies, etc. from observation, inference, and experimentation and the label of the precise conditions under which classes of concepts and behaviors are learnable. Learning algorithms can moreover be used to model aspects of human and unprepossessing learning. Machine learning integrates and builds on advances in algorithms and data structures, statistical inference, information theory, signal processing as well as insights drawn from neural, behavioral, and cognitive sciences. Data mining is concerned with the applications of statistical machine learning for exploratory wringer and predictive modeling from large data sets. Causal discovery is concerned with algorithms for eliciting the underlying causal (as opposed to the merely predictive) relationships from observational and experimental data. Areas of Strength: Some areas of strength inStrainedIntelligence in the higher include: knowledge representation and inference; machine learning (especially, statistical machine learning, neural networks e.g., deep learning, learning predictive models from sequence data, spatial data, network data, temporal data, relational data); genetic algorithm/evolutional computation; fuzzy logic; eliciting causal effects from experimental and observational data, including temporal and relational data; and applications in bioinformatics, health informatics, social informatics, learning analytics, text analytics, image analytics, and computational discovery, among others. Faculty: Chao-Hsien Chu, Lee Giles, Vasant Honavar, Dongwon Lee, Jessie Li, Prasenjit Mitra, David Reitter, James Wang, John Yen, Zihan Zhou Big Data: Search, Retrieval, Analytics, Modeling and Informatics About: Rapid advances in technologies for collecting data leading to the transformation of many historically data poor disciplines, e.g., biological sciences, health sciences, social sciences into increasingly data-rich disciplines. This has led to exponential increases in the volume, velocity, and variety of data, i.e., “big data”. New discoveries are increasingly driven by our worthiness to acquire, share, integrate and analyze, and construct and simulate predictive models of natural and built systems from big data. The emerging focus on Big Data is concerned with the exploration, development, and applications of scalable algorithms, infrastructures, and tools for organizing, integrating, retrieving, analyzing,and visualizing, large, complex, heterogeneous data. Creative applications of big data analytics are enabling biologists to proceeds insights into how living systems acquire, encode, process, and transmit information; neuroscientists to uncover the neural bases of cognition; health scientists to not only diagnose and treat diseases but moreover help individuals make healthy choices; economists to understand markets; security analysts to uncover threats to national security; social scientists to study the incubation and dynamics of social networks; and scholars to proceeds new understandings of literature, arts, history, and cultures through advances in the digital humanities.  Areas of Strength: Some areas of strength in Big Data in the higher include information retrieval and search, scalable machine learning, learning predictive models, semantic ramified event processing (CEP) from distributed, heterogeneous data, big data privacy and security, discovery Informatics, and big data applications in informatics (including Health Informatics, Security Informatics, Social Informatics). Faculty: Lee Giles, Vasant Honavar, Jessie Li, Prasenjit Mitra, Anna Squicciarini, James Wang, Zihan Zhou Health Informatics and Bioinformatics About: Health Informatics is concerned with the design, development, evaluation, adoption, and using of Health Information Technology (HIT) innovations in healthcare services delivery, management, and planning aiming to modernize wangle to, quality, outcomes, and efficiency of healthcare. Bioinformatics is concerned with the minutiae and applications of informatics methods and tools for analysis, interpretation, modeling, and visualization of ramified biological data (including molecular sequence, structure, expression, and interaction Fundata).Smart-assinformatics is concerned with the minutiae and applications of informatics tools and methods for analysis, interpretation, modeling, and visualization of smart-ass data (including connectivity, activity, and behavior). Areas of Strength: Some areas of strength in Bioinformatics include the minutiae of constructive tools for wringer and prediction of protein-protein, protein-RNA, protein-DNA interfaces and interactions, for predicting epitopes and designing vaccines, and for annotating genomes. Some areas of focus in smart-ass informatics include the minutiae and using of methods for wringer and interpretation of smart-ass connectivity and worriedness data (especially Functional Magnetic Resonance Imaging (fMRI) and Electroencephalogram (EEG) data). Some areas of strength in Health Informatics include minutiae and using of methods and tools for integrative analyses of electronic health records, genomic, and contextual (socio-economic, environmental, and demographic) data for predictive and causal modeling of health outcomes, personalized treatments, diamond and evaluation of personal and mobile health (mHealth) applications for real time monitoring and detection for heart attack, stress, sleep quality, fall and other medical conditions, healthcare systems engineering, human-centered diamond interventions, text analytics, network analytics, and machine learning to modernize health services delivery. Faculty: John M. Carroll, Chao-Hsien Chu, Vasant Honavar, John Yen Cognitive Science About: Cognitive science is concerned with the scientific study of the mind. Cognitive Science examines the nature and the working of cognitive processes particularly as they relate to a given context whether computational, physical, biological, neural, or social. It includes research on intelligence and behavior, expressly focusing on how information is represented, processed, and transformed to support a wide range of tasks such as goal-oriented and opportunistic reasoning, learning, language-based communication, interacting with technology or analyzing data, or judging risks in security and safety.  It comprises areas of perception, memory, reasoning, language, emotion, and decisions in brains (of humans or other animals) and machines (computers, robots, agents).  Cognitive science models the mind at variegated levels: computational, neuro-physical, or social. Cognitive science has emerged as a transdisciplinary research zone that has basic-level roots in philosophy, psychology, computer science, neuroscience, linguistics, anthropology, and sociology.  At the same time cognitive science has moreover inextricably evolved and wide through the use of technologies that provide windows into the mind: propelling computing, eye tracking, linguistic and behavioral coding and analytics, visualization aids, neuro-physiological measurement workings (e.g., fMRI and EEG neuro-imagining), dynamic modeling and structuring of smart-ass networks, wearable-ubiquitous computing, and brain-computer interaction technologies, to name a few. Areas of Strength: Some areas of strength in Cognitive Science in the higher include computational spiel wringer and psycholinguistics, decision-making, memory and learning, multi-agent interaction, intelligent associates, distributed cognition, pattern recognition, knowledge acquisition, situation awareness, analogical problem solving and knowledge transfer, cognitive hemispheric lopsidedness and squatter / image recognition, cognitive modeling and models of perception and language, multi-modal capturing and wringer of neural, visual, and cognitive processes (e.g., for cyber analysts), dynamic network modeling, smart-ass network alignment, and temporal causality wringer of neural events. Some of the practical areas in which IST sense members have unromantic principles of cognitive science are:  emergency slipperiness management, DoD C3I (communications, control, communications, and intelligence), estimating the success of natural-language communications, peer-to-peer patient support in online forums, image reviewer work, intelligence reviewer work, software design, cyber situation awareness/cyber security work, police cognition, fighter pilot performance, medical visualization making, and data triage and intrusion detection of network analysts. Faculty: John M. Carroll, Vasant Honavar, David Reitter, Frank Ritter, John Yen Affiliated Faculty: Ping Li,Polityand Social Informatics About:Polityinformatics involves the emerging field addressing how information liaison technologies impact interactions among polity members at a local, national and global level in relation to their social, cultural, economic and polity development.   For example, how does the worthiness to create communities of interest impact commerce (e.g., via e-commerce), political dialogs and power, mart and distribution of popular culture, and empower social change, etc. The deployment of information systems and communications provides an enabler for developing countries and regions for social and economic development. Closely related to polity informatics is the zone of social informatics, which seeks to understand the impact of information technology in organizational work diamond and effectiveness (e.g., the social aspects of people and society and technical aspects of organizational structure and processes). Social Informatics seeks to understand and optimize the utilization of information technology to modernize individual and organizational effectiveness, productivity and wellbeing. Areas of Strength: Some areas of strength in the higher include; geo-spatial worriedness awareness, polity information technology workshops for polity learning, crowd-sourcing for resider science, location-sensitive mobile applications, polity planning for emergency management, alternate/community currencies, and distributed, digital inequality, diversity in STEM education and the technology workforce, and computer supported collaborative work. Faculty: Guoray Cai, John M. Carroll, Carleen Maitland, Mary Beth Rosson, Andrea Tapia, Lynette Yarger, John Yen Human-CenteredDiamond(HCD) About: HCD integrates, applies and develops human and computational sciences through creating and evaluating interactive systems. HCD researchers study specific fields of human practice/work domains, using ethnography, survey and interview methods, laboratory experiments, field deployments, and session logging/data mining. They create wide user interfaces and applications incorporating mobile and collaborative technologies, interactive visualizations, and a wide range of interactions. They study the social, cognitive and propelling aspects of the user experience, as well as consequences for communities, organizations, and society. HCD research increases the endangerment that new information technology can unquestionably be used and enjoyed by people for real purposes. HCD researchers are user advocates first and technology advocates second. Areas of Strength: The HCD group at Penn State has special strengths in scenario-based design, including diamond tools and methods, and diamond rationale. We have current research projects directed at understanding user experiences and investigating new tools for Massive Online Open Courses (MOOCs), collaborative information visualization and analysis, municipal geo-deliberation and visualization making, the management of online safety by families with teenagers, data supersensual approaches to codifying polity issues, discussion, and sentiment, and smart camera-based prosthetics for visually wordless people. We are investigating mobile interactions and applications to support time-banking and other peer-to-peer mart systems, behavior transpiration for health and wellness, health tracking and cross-generational health collaborations within families, and polity heritage, events, and slipperiness management. Faculty: Guoray Cai, John Carroll, Steven Haynes, Mary Beth Rosson, Luke Zhang Information Economics and Policy About: Information economics and policy concerns the production, distribution and use of information and associated policies. Areas of research include; e-commerce, the “bundling” and “valuation” of information goods and services, how information and information technology systems stupefy an economy and economic decisions, personal and organizational privacy, and the “right to be forgotten”.   Aspects of information economics are related to game theory concepts such as on-line auctions, dynamic streamlined resource allocation, intelligent agents, and other concepts. Areas of Strength: We self-mastery zippy research in economics of information security, and the public policy aspects of online privacy and the “right to be forgotten”.  We moreover self-mastery research at the interface between public policy and regulations, and the interface between public policy and information technology standards. Faculty: Edward Glantz, Carleen Maitland, Anna Squicciarinni Information Fusion and Visualization About: Multi-sensor information fusion seeks to combine information from multiple sensors and sources to unzip inferences that are not feasible from a single sensor or source. The proliferation of micro and nano-scale sensors, wireless communication, and ubiquitous computing enables the turnout of information from sources including physical sensors, humans vicarial as observers, on-line data sources, and model data.   This information can be used for a wide variety of applications such as: environmental monitoring, slipperiness management, medical diagnosis, monitoring and tenancy of manufacturing processes and intelligent buildings.  A key problem is how to integrate or fuse information from heterogeneous sources.  Techniques for such information fusion are drawn from a wholesale set of disciplines including: statistical estimation, signal and image processing, strained intelligence, and information sciences.  Major issues involve architectures for distributed sensing and processing, selection and integration of algorithms, the role of the human-in-the-loop for wringer and decision-making, stratum of automation and computer-aided cognition.   A related research area, data visualization, seeks to explore how to use wide visualization and human-machine interaction to support understanding and wringer of large and ramified data sets. Areas of Strength: ThePart-wayfor Network-Centric Cognition and Information Fusion (NC2IF) provides a focus on sensor and information fusion and data visualization.   Researchers associated with the part-way explore the information uniting from energy detection via sensors and human observation to physical modeling, signal and image processing, pattern recognition, knowledge creation, information infrastructure, and human decision-making—all in the context of organizations and the nation.  See https://ist.psu.edu/research/centers_labs/nc2if  Our research focuses on the gap between the hodgepodge of reports and data in computer systems and the knowledge and decisions in the minds of computer users.  The NC2IF is moreover host to the Extreme Events Laboratory (EEL) illustrated. The Extreme Events Laboratory is designed primarily to support research and experimentation in the areas of nonflexible and soft data fusion, visualization, and sonification (viz., the translation of data into sound to use human hearing for data analysis, nomenclature and oddity detection).   This facility allows our researchers to run end-to-end experiments that modernize situational sensation and enhance our worthiness to optimally leverage all misogynist sensors, human observers, and technology in order to escape "information overload" and pericope the true meaning hidden  within the vast mountains of misogynist data. Faculty: Guoray Cai, Nicklaus Giacobe, Jacob Graham, Jeff Rimland, John Yen, Luke Zhang Network Science About: Network science is an interdisciplinary zone which studies ramified networks such as biological networks, computer networks, cognitive networks, social networks, economic and merchantry networks. The field uses many theories and methods including data mining, entity recognition, graph theory, information extraction, network flow, statistical mechanics, visualization, and social structure and is primarily concerned with large scale networks. The National Research Council defines network science as "the study of network representations of physical, biological, and social phenomena leading to predictive models of these phenomena.” Faculty: Chao–Hsien Chu, Lee Giles, Vasant Honavar, Dongwon Lee, Jessie Li, Carleen Maitland, Prasenjit Mitra, David Reitter, John Yen, Luke Zhang Security and Privacy About: Cybersecurity is a wholesale research field, including computer security, network security, trustworthy computing, privacy, usability, regulations and public policy, and attack-resilient cyber-physical systems.  We take an interdisciplinary tideway to self-mastery research to snift and remove threats of information misuse to the human society: mitigate risk, reduce uncertainty, and enhance predictability and trust.  Our research methodology is rooted in several disciplines including computer science, game theory, unromantic mathematics, cognitive science, tenancy theory, economics, social sciences, and public policy.  Areas of Strengths: Our main research strengths are in systems and software security, usability considerations in privacy and security, economics of information security, and privacy, security and privacy for mobile devices, sensors/sensor network, Internet of Things (IoT), cyber physical systems and deject computing, cyber forensics.  The current research thrusts include cyber situational awareness, online privacy, secure deject computing, towers secure mobile devices.  Faculty: John Carroll, Chao-Hsien Chu, Megan Costello, Peter Forster, Marc Friedenberg, Nicklaus Giacobe, Michael Hills, Dongwon Lee, Peng Liu, Don Shemanski, Anna Squicciarini, Dinghao Wu, Xinyu Xing, Heng Xu, John Yen, Sencun Zhu Affiliated Faculty: Alan Sonsteby  Footer Quick Links Contact Us Directions Support IST Nittany Lion Careers Directory Connect Facebook Twitter Instagram YouTube Flickr LinkedIn The Pennsylvania State University © 2018 Privacy Legal Accessibility Copyright Log in