School of Interactive Computing overview

INSIDE 2 History 3 Organization Chart 4 Faculty Research 12 IC Facts 14 Research Stories 16 Community Stories 19 SWOT Analysis

Establishment and History of the School of Interactive Computing at Georgia Tech The SCHOOL OF INTERACTIVE COMPUTING was established in 2007. At the time, the Computing at Georgia Tech was elevated to the level of a College (forming the College of Computing) and two schools underneath it: the School of Computer Science and School of Interactive Computing. The mission and focus of IC was (and remains) to act as a leader in research and education at the intersection of computer science and human-computer interaction. With its inception, Aaron Bobick was appointed the Chair of the school. The School of Interactive Computing (IC) aims to redefine the human experience of computing using two primary tools: research and innovation in computing education.

IC offers a diverse range of undergraduate and graduate programs, including Bachelor of Science, Master of Science, and Ph.D. degrees. Our School has taken the initiative in creating new, more effective techniques and practices for computing education. At the doctoral level, we led the development of Georgia Tech’s Ph.D. in robotics; we’ve led a national trend in offering a Ph.D. in human-centered computing; and we offer a Ph.D. in computer science. At the undergraduate level, we play a fundamental role in the College of Computing’s Threads program and are responsible for the four most interdisciplinary and outwardfacing of the Threads: Media, Intelligence, People, and Devices.

that empower people and machines to affect the world.

Through innovation in education, we are preparing a new generation of computational scholars.

Our faculty conceived the discipline of interactive computing to examine the impacts computation and computing-mediated interactions have on life’s “big issues,” such as health care and national security, but also on the everyday activities in which all of us engage, such as children playing video games, adults keeping in touch with elderly parents, and professionals using computers as tools in the workplace. These interactions take place not in laboratories, but in homes, offices, schools, and hospitals — and computation plays a central role.

The degree programs offered in IC include: Doctoral Degrees: n PhD in Computer Science n PhD in Machine Learning n PhD in Human-Centered Computing n PhD in Robotics Master’s Degrees: n MS in Computer Science n MS in Human-Computer Interaction Bachelor’s Degrees n BS in Computer Science n BS in Computational Media Our School nurtures an open, inclusive, and supportive environment made stronger through multiple perspectives and diverse expertise. Research takes faculty and students on a path to study and invent computational capabilities

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SCHOOL OF INTERACTIVE COMPUTING / COLLEGE OF COMPUTING

Our research focuses on artificial intelligence and machine learning; geometry, graphics, and animation; humancentered computing and cognitive science; information visualization and visual analytics; learning science and technology, and computing education; robotics and computational perception; social computing and computational journalism; ubiquitous and wearable computing; and virtual and augmented environments.

Together, these areas form a rich, panoramic view of the myriad ways computing and computational devices interact with their human creators and users.

Our 60-plus faculty members strive for scholarly excellence and prominence. We contribute to scientific knowledge. We create technology that focuses the power of computing to address the world’s needs, from the individual all the way to society and everywhere in between.

In short, we redefine the human experience of computing.

School of Interactive Computing Organization Chart Staff

Faculty

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Research in the School of Interactive Computing ARTIFICIAL INTELLIGENCE & MACHINE LEARNING Artificial intelligence (AI) and machine learning (ML) focus on core research problems in intelligence involving fundamental advances in artificial intelligence, machine learning, and deep learning, as well as challenges in computer vision, natural language processing, and other application areas.

We also study the implications of AI and ML in explainable AI, computational creativity, and fairness in the context of ML models. Finally, our faculty work where AI and ML intersect with other areas and fields such as robotics, human computerinteraction, cognitive science, and computer graphics.

AI & ML Faculty Sonia Chernova: Robotics and artificial intelligence, including semantic reasoning, adaptive autonomy, humanrobot interaction and explainable AI. Serves as the Director for NSF-CARING, an NSF-funded AI Institute whose mission is to develop the next generation of personalized collaborative AI systems that improve the quality of life and independence of aging adults living at home.

Irfan Essa: Computer vision, machine learning, computer graphics, computational perception, computer animation, and social computing, with potential impact on autonomous systems, computational photography, image-based modeling and rendering, human-computer interaction and computational journalism.

Animesh Garg: Generalizable autonomy, which involves representations and algorithms for reinforcement learning, control, and perception. He currently studies three aspects: learning structured inductive biases in sequential decision making, using data-driven causal discovery, and transfer to real robots — all in the purview of embodied systems.

Kartik Goyal: Natural language processing and machine learning problems pertaining to modeling data with structured random variables for development of efficient, interpretable and controllable probabilistic models. A particular interest in the intersection of these problems with Digital Humanities.

Larry Heck: Next-generation virtual assistants, including every aspect of modern AVAs — human-computer interaction design, single vs. multimodal interactions, situated interactions over screens and mixed reality (AR/

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VR), task-oriented conversations to open-domain chit-chat to both, explicit to implicit knowledge-driven conversations, and higher level inference and reasoning.

Judy Hoffman: Research lies at the intersection of computer vision and machine learning with specialization in domain adaptation, transfer learning, adversarial robustness, and algorithmic fairness.

Zsolt Kira: Learning methods for sensor processing and robotics, novel machine learning algorithms and formulations that move beyond supervised learning (un/ semi/self-supervised and continual/lifelong learning) as well as distributed perception (multi-modal fusion, learning to incorporate information across a group of robots, etc.).

Christopher MacLellan: Development of computational models of human learning and how these models can support the development of effective learning technologies at scale. Methods for end-users to teach cognitive systems new capabilities, similar to how they would teach another person.

Mark Riedl: The development of artificial intelligence and machine learning technologies that understand and interact with human users in more natural ways. Recent work has focused on story understanding and generation, computational creativity, explainable AI, and teaching virtual agents to behave safely.

Alan Ritter: Natural language processing, specifically questions regarding robust models that work across many domains and languages, while requiring fewer labels, and making efficient use of computational resources. Also datadriven dialogue agents that safely and naturally converse on any topic.

Humphrey Shi: Computer vision, machine learning, and AI systems & applications. Basic research and interdisciplinary collaborations motivated by important applications, with current focuses on creative, efficient, and responsible multimodal AI to understand, emulate, and interact with the visual world we live in.

Danfei Xu: Visuomotor skill learning, structured world models for long-horizon planning, and data-driven approaches to human-robot collaboration, with a goal

of enabling physical autonomy in everyday human environments with minimum expert intervention.

Wei Xu: Natural language processing, machine learning, and social media. Her recent work focuses on text generation, stylistics, information extraction, robustness and controllability of machine learning models, and reading and writing assistive technology.

and social computing, with potential impact on autonomous systems, computational photography, image-based modeling and rendering, human-computer interaction and computational journalism.

James Hayes: Computer vision, robotics and machine learning, specifically problems related to recognition, synthesis and manipulation. Research often involves finding new data sources to exploit, or creating new data sets where none existed.

COMPUTER GRAPHICS Computer graphics is the art of producing digital images using computer programs, which is a core technology of photography, movie, animations, computer games, digital arts, and computer displays. Our faculty in computer graphics is at the forefront of cutting-edge research and innovation that deals with the creation, modeling, animation, control, simulation, design, transmission, and visualization of interactive virtual worlds. Particularly, our faculty members focus on two exciting fields of computer graphics: computer animation and computer simulation.

Judy Hoffman: Research lies at the intersection of computer vision and machine learning with specialization in domain adaptation, transfer learning, adversarial robustness, and algorithmic fairness.

Computer Graphics Faculty Sehoon Ha: Research interests lie at the intersection between computer graphics and robotics, including physics-based animation, deep reinforcement learning, and computational robot design.

Danfei Xu: Visuomotor skill learning, structured world models for long-horizon planning, and data-driven approaches to human-robot collaboration, with a goal of enabling physical autonomy in everyday human environments with minimum expert intervention.

Greg Turk: Computer graphics, biological simulation and scientific visualization. Brought the “Stanford bunny,” a frequently used example object in computer graphics research, into the CGI lexicon.

Bo Zhu: Computer graphics, computational physics, computational design and fabrication, and scientific machine learning, centered around physics simulation.

He has has pioneered cutting-edge, high-performance numerical algorithms to address intricate computational challenges inherent in diverse physical systems.

COMPUTER VISION Computer Vision is the use of artificial intelligence to extract data from images, allowing computers to use real-world data in decision-making. Specific topics include camera calibration, boundary detection, alignment, and image recognition.

Computer Vision Faculty Irfan Essa: Computer vision, machine learning, computer graphics, computational perception, computer animation,

Humphrey Shi: Computer vision, machine learning, and AI systems & applications. Basic research and interdisciplinary collaborations motivated by important applications, with current focuses on creative, efficient, and responsible multimodal AI to understand, emulate, and interact with the visual world we live in.

COGNITIVE AND LEARNING SCIENCES Cognitive and Learning Sciences investigates human cognition and learning, and the role technology may play in cognition and learning through the design and study of learning environments — in school, online, in the workplace, at home, and in informal settings, as well as in self-directed learning.

Cognitive and Learning Sciences Faculty: Betsy DiSalvo: Educational games, sustainable STEM education, physical computing and maker spaces, makeroriented learning approaches to increase transfer and reflection in CS courses, and the DataWorks project, an authentic working environment for minority young adults that provides CS education through entry-level jobs.

Ashok Goel: Cognitive systems at the intersection of artificial intelligence and cognitive science with a focus on computational design and creativity. Recent research has focused on AI in education and education in AI. He is the director of NSF-ALOE, the Institute for Adult Learning and Online Education.

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David Joyner: Online education and learning at scale, especially in for-credit offerings at the graduate and undergraduate levels. Learning experiences that leverage the opportunities of online learning to compensate for the loss of synchronous collocated class time. Executive Director of the OMSCS program.

HEALTH INFORMATICS Health Informatics is the study of the collection and analysis of data coming out of health systems. The goal is to aggregate data to improve public health, the diagnosis and treatment of diseases, and the efficiency and effectiveness of hospitals and health care systems.

Christopher MacLellan: Development of computational models of human learning and how these models can support the development of effective learning technologies at scale. Methods for end-users to teach cognitive systems new capabilities, similar to how they would teach another person.

Health Informatics Faculty Alexander Adams: Designing, fabricating, and implementing new ubiquitous and wearable sensing systems. In particular, developing these systems using equity-driven design principles for healthcare. Leveraging sensing, signal processing, and fabrication techniques to design, deploy, and evaluate novel sensing technologies.

Jessica Roberts: Geospatial analysis and visualization in informal learning. The design of learning environments in a variety of contexts. Technology-mediated social learning experiences in environments such as museums and citizen science.

Judith Uchidiuno: Culturally informed CS education technologies, and access to computer science education in sustainable ways for students from low income and underserved communities. Co-designed a state-wide curriculum in artificial intelligence for middle-school students.

Sashank Varma: Mathematical cognition, computational thinking, language understanding, learning, and problem solving (e.g., optimization under constraints). He also investigates the neural correlations of cognitive mechanisms and the educational implications of cognitive learning principles.

CYBERSECURITY AND PRIVACY: As more and more data comes to be gathered into computing systems, it becomes ever more vital to control access to that data and protect the privacy of individuals.

Cybersecurity and Privacy is the study of the technological, social and political factors that can secure or endanger private data.

Cybersecurity and Privacy Faculty: Annie Anton: Methods and tools to support the specification of complete, correct behavior of software systems used in environments that pose risks of loss as a consequence of failures and misuse. Current extensions to this work include the analysis of federal security and privacy regulations, and compliance practices.

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Rosa Arriaga: Chronic care management and mental health. Systems to address gaps in chronic care and mental health management. Computational systems that foster engagement, facilitate continuity of care, promote patient self-advocacy, and mediate communication between patient and healthcare providers.

Shaowen Bardzell: Women’s health (menstruation, sexuality, menopause) leveraging humanistic traditions of critical theory, interpretivist social science and feminist social science epistemology and methods, as well as interventionist approaches to design and deploy technological solutions.

Josiah Hester: Untethered computing devices — wearables, implantables, energy harvesting sensors. Radically new hardware designs, software techniques, tools, an dprogramming abstractions for designing, debugging and deploying intricate application that work in spite of frequent power failures and unpredictable conditions.

Jennifer Kim: Human-computer interaction and digital health, specifically how social and health information systems can be designed to promote diversity, advocacy, and empathy. A special focus on impacting the lives of neurodiverse people and the communities around them.

Neha Kumar: Human-computer interaction and global sustainable development, with a focus on global health and community informatics. Feminist perspectives on the design and integration of emerging technologies across marginalized contexts in the Global South.

Andrea Grimes-Parker: Digital health at the intersection of human-computer interaction (HCI), social computing,

and public health. Software tools that help people manage their health and wellness, with a focus on health equity, racial, ethnic and economic health disparities and the social context of health management.

Agata Rozga: Computational behavioral science, or the measurement, analysis, and understanding of healthrelated behaviors by leveraging advances in sensing, wearable and mobile technologies, and computational analysis methods. Tools for better detection, monitoring, and treatment of a variety of chronic health conditions.

HUMAN-COMPUTER INTERACTION Human-Computer Interaction (HCI) is an interdisciplinary field that encompasses the study of how individuals interact with computers and technology throughout their lives.

The primary objective of HCI research is to develop user interfaces that are not only useful and usable but also enjoyable for individuals. It encompasses a broad range of activities, including design, development, and evaluation of computer systems, all with the aim of understanding the impact of technology on people and society.

The overarching goal of the HCI community is to create transformative technologies, experiences, and systems that empower individuals to reimagine and redesign their lives.

This involves engaging people worldwide in meaningful and creative experiences that integrate art, science, design, and engineering. By exploring the intersection of humanity and technology, the HCI community collaborates with organizations and communities globally to turn ideas into reality through exceptional education, research, innovation, and the cultivation of creativity.

Human-Computer Interaction Faculty Rosa Arriaga: Chronic care management and mental health. Systems to address gaps in chronic care and mental health management. Computational systems that foster engagement, facilitate continuity of care, promote patient self-advocacy, and mediate communication between patient and healthcare providers.

Shaowen Bardzell: Bardzell pursues a humanistic research agenda within the research and practice of Human Computer Interaction (HCI). A common thread throughout her work is the exploration of the contributions of feminism, design, and social science to support technology’s role in social change.

Carrie Bruce: In person-environment interaction in healthcare, rehabilitation, HCI, accessibility, and inclusive design. Design issues as they relate to people’s abilities and methodologies that measure the impact of physical and social environment factors on activity, performance, and participation.

Carl DiSalvo: Design that supplies novel contributions to local democracy by drawing together theory and practice, making and reflection. Research into the ways that the relentless pursuit of innovation, uncritical embrace of the new, and treatment of all things as design problems can lead to cultural imperialism.

Keith Edwards: Human-centered perspectives on computer networking, particularly in the home; he has also been active in developing more usable approaches to information security systems. Social impacts of computing technology, and understanding how technology can support the work of non-profits and NGOs. Beki Grinter: Understanding the human experience in the building and using of technologies. Her work contributes to the fields of human-computer interaction, ubiquitous computing, and computer supported cooperative work.

She has also worked in the areas of robotics, networking, security, and software engineering.

Richard Henneman: Design management, user interface design, usability, user experience, and information architecture. Director of the M.S. program in HumanJennifer Kim: Human-computer interaction and digital health, specifically how social and health information systems can be designed to promote diversity, advocacy, and empathy. A special focus on impacting the lives of neurodiverse people and the communities around them.

Neha Kumar: Human-computer interaction and global sustainable development, with a focus on global health and community informatics. Feminist perspectives on the design and integration of emerging technologies across marginalized contexts in the Global South.

HyunJoo Oh: Computing technologies to extend and transform familiar and accessible materials both as tools and as materials, broadening creative possibilities for designers. Works with a broad spectrum of designers from professional designers and hobbyist makers to K-12 educators and students.

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Andrea Grimes-Parker: Digital health at the intersection of human-computer interaction (HCI), social computing, and public health. Software tools that help people manage their health and wellness, with a focus on health equity, racial, ethnic and economic health disparities and the social context of health management.

Thad Starner: Computational interfaces and agents for use in everyday mobile environments. Combining wearable and ubiquitous computing technologies with techniques from the fields of artificial intelligence (AI), pattern recognition, and human-computer interaction (HCI). Current focus is on assistive technology for the Deaf community.

Judith Uchidiuno: Culturally informed CS education technologies, and access to computer science education in sustainable ways for students from low income and underserved communities. Co-designed a state-wide curriculum in artificial intelligence for middle-school students.

Bruce Walker: Human-computer interaction (HCI) issues in non-traditional interfaces, ranging from mobile devices to cockpits and displays in vehicles to multimodal interfaces in education and in complex task environments. Research interests include sonification and auditory displays, assistive technology, and driving.

INFORMATION VISUALIZATION Information visualization is an area of research that helps people analyze and understand data using visualization techniques. The multi-disciplinary area draws from other areas of science, including human-computer interaction, data science, psychology, and art to develop new visualization methods and understand how (and why) they are effective.

Our researchers are developing new, interactive visualization techniques and systems that provide multiple and flexible perspectives on the data being examined. These systems help people and organizations to browse, explore and analyze data that is important to them. Fundamentally, these interactive visualizations are tools for sense-making; they assist us in understanding data by presenting it in a form that can be organized, queried, and explored in order to gain new perspectives and insights about it.

Information Visualization Faculty: Clio Andris: Interpersonal relationships and social networks in geographic space. Mathematical models of social networks, social flows, and interpersonal

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relationships, applied to issues of urban planning, visualization, transportation, and geography.

Alex Endert: Interactive visual tools help people make sense of data and AI. His lab often tests these advances in domains including intelligence analysis, cyber security, decision-making, manufacturing safety, and others.

John Stasko: Information visualization and visual analytics tools to help people explore, analyze, understand and communicate data sets. Specifically, systems to support “sense-making” activities on data sets such as large document collections. Techniques and systems for providing people with peripheral awareness of useful information.

Cindy Xiong: Bridging the fields of psychology and data visualization, using uses empirical studies and computational models to understand the cognitive and perceptual processes that underlie visual data interpretation.

Yalong Yang: Visualization, virtual reality, human-computer interaction, geovisualization, evaluation, visual analytics and immersive analytics.

INTERNATIONAL DEVELOPMENT Computer systems are often designed in wealthy countries and implemented in poor countries without any thought to differences in culture and context. The study of computing in international development considers the technologies needed to build sustainable communities around the globe.

International Development Faculty: Michael Best: Mobile phones, the internet, and internet-enabled services and their design, impact, and importance – their risks and rewards – for people and communities especially in Africa and Asia. Engineering, public policy, usability, and sustainability issues as well as methods to assess and evaluate social, economic, and political development outcomes.

Neha Kumar: Human-computer interaction and global sustainable development, with a focus on global health and community informatics. Feminist perspectives on the design and integration of emerging technologies across marginalized contexts in the Global South.

INTERNATIONAL DEVELOPMENT Computer systems are often designed in wealthy countries and implemented in poor countries without any thought to

differences in culture and context. The study of computing in international development considers the technologies needed to build sustainable communities around the globe.

the next generation of personalized collaborative AI systems that improve the quality of life and independence of aging adults living at home.

International Development Faculty: Michael Best: Mobile phones, the internet, and internetenabled services and their design, impact, and importance – their risks and rewards – for people and communities especially in Africa and Asia. Engineering, public policy, usability, and sustainability issues as well as methods to assess and evaluate social, economic, and political development outcomes.

Animesh Garg: Generalizable autonomy, which involves representations and algorithms for reinforcement learning, control, and perception. He currently studies three aspects: learning structured inductive biases in sequential decision making, using data-driven causal discovery, and transfer to real robots — all in the purview of embodied systems.

Neha Kumar: Human-computer interaction and global sustainable development, with a focus on global health and community informatics. Feminist perspectives on the design and integration of emerging technologies across marginalized contexts in the Global South.

ROBOTICS Robotics research in the School of Interactive Computing at Georgia Tech takes a wholistic, integrated view in developing intelligent, physically-embodied systems. Our work spans from developing computational approaches to cognitive reasoning and representations to enabling robots to act within our dynamic world. Our research covers the spectrum of robotic intelligence: perception, multi-agent communication (including via natural language), decisionmaking, learning and evaluation in simulation (and sim2real transfer), task and motion planning, and control. Our faculty also design novel robot hardware and develop new humanrobot interaction mechanisms. We contribute to diverse applications (e.g., manipulation, navigation, and locomotion) in a wide range of domains, such as autonomous driving, consumer robotics, manufacturing, and warehouse automation.

Robotics Faculty: Ron Arkin: Behavior-based reactive control and actionoriented perception for mobile robots and unmanned aerial vehicles, hybrid deliberative/reactive software architectures, robot survivability, multiagent robotic systems, biorobotics, human-robot interaction, robot ethics, and learning in autonomous systems.

Sonia Chernova: Robotics and artificial intelligence, including semantic reasoning, adaptive autonomy, humanrobot interaction and explainable AI. Serves as lead for NSF-CARING, an AI institute whose mission is to develop

Matthew Gombolay: Robots that can learn from interaction with people and their environments, explain to their human partners what was learned from those interactions, and collaborate in human-robot teams in domains ranging from home healthcare to manufacturing, autonomous driving, disaster response, and national security.

Sehoon Ha: Research interests lie at the intersection between computer graphics and robotics, including physics-based animation, deep reinforcement learning, and computational robot design.

James Hayes: Computer vision, robotics and machine learning, specifically problems related to recognition, synthesis and manipulation. Research often involves finding new data sources to exploit, or creating new data sets where none existed.

Seth Hutchinson: Visual servo control, planning with uncertainty, pursuit-evasion games, and mainstream problems from path planning and computer vision. Serves as director of the Institute for Robotics and Intelligent Machines (IRIM).

Zsolt Kira: Learning methods for sensor processing and robotics, novel machine learning algorithms and formulations that move beyond supervised learning (un/ semi/self-supervised and continual/lifelong learning) as well as distributed perception (multi-modal fusion, learning to incorporate information across a group of robots, etc.).

Harish Ravichandar: Robot learning, human-robot interaction, and multi-agent systems, with a focus on structured algorithms that help robots reliably operate and collaborate in unstructured environments alongside humans.

Danfei Xu: Visuomotor skill learning, structured world models for long-horizon planning, and data-driven approaches to human-robot collaboration, with a goal of enabling physical autonomy in everyday human environments with minimum expert intervention.

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SOCIAL COMPUTING Social computing is concerned with the interaction of social behavior and computer systems, particularly in the way that social conventions are created or recreated through technology. This area focuses particularly on social media and related phenomena such as blogs, instant messaging, wikis, and e-mail.

Social Computing Faculty: Amy Bruckman: Social computing with interests in online collaboration, understanding across differences, and content moderation. A pioneer in the study of internet communities and the online construction of knowledge.

Thad Starner: Computational interfaces and agents for use in everyday mobile environments. Combining wearable and ubiquitous computing technologies with techniques from the fields of artificial intelligence (AI), pattern recognition, and human-computer interaction (HCI). Current focus is on assistive technology for the Deaf community.

Munmun De Choudhury: Large-scale data analytics, machine learning, and artificial intelligence techniques for understanding human behavior and dynamics in online environments. A highly interdisciplinary approach blends insights from psychology, sociology, medicine, and public health with advanced computational methods.

Thomas Ploetz: Applied machine learning that is developing systems and innovative sensor data analysis methods for real world applications. Primary application is computational behavior analysis, or methods for automated and objective behavior assessments in naturalistic environments.

UBIQUITOUS COMPUTING Ubiquitous computing is a concept in software engineering, hardware engineering and computer science where computing is made to appear anytime and everywhere. Much of our work is situated in settings of everyday activity, such as the classroom, the office, the home, and on-the-body in mobile settings. Our research focuses on several topics: automated capture and access to live experiences, context-aware computing, applications and services in the home, natural interaction for mobile and wearable computing, software architecture, security and privacy issues, technology for individuals with special needs, and personal informatics.

Ubiquitous Computing faculty: Alexander Adams: Designing, fabricating, and implementing new ubiquitous and wearable sensing systems. In particular, developing these systems using equity-driven design principles for healthcare. Leveraging sensing, signal processing, and fabrication techniques to design, deploy, and evaluate novel sensing technologies.

Josiah Hester: Untethered computing devices — wearables, implantables, energy harvesting sensors. Radically new hardware designs, software techniques, tools, and programming abstractions for designing, debugging and deploying intricate application that work in spite of frequent power failures and unpredictable conditions.

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Melody Jackson: Real-world applications for direct brain interfaces and other biometric interfaces. Part of the first team to implant a human being with a chronic recording electrode in 1998, and has extensively explored noninvasive brain-computer interfaces with technologies such as EEG and functional Near Infrared (fNIR) imaging.

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Our mission is to examine the impact computation and computing-mediated interactions have on large-scale societal issues as well as the everyday activities in which we all engage.

Enrollment (March 2024):

185

Ph.D. (all programs)

Research budget:

142

M.S. (all programs)

PhD degrees

FY2023

The School of Interactive Computing participates in five Ph.D. programs:

Computing. Policies and regulations related to the PhD ML program are documented in the ML PhD handbook.

n Ph.D. in Computer Science. This is a college-run

n PhD in Robotics (Robo), which is run by multiple

program which includes all four research schools.

A college-wide PhD CS handbook governs the PhD CS program overall. n Ph.D. in Interactive Computing, which operates

in accordance with the C.S. Ph.D. handbook.

Our students may choose from the following specializations: n Intelligent Systems (IS) n Human Computer Interaction (HCI) n Social Computing (SocComp) n Learning Sciences and Technologies (LST) n Information Visualization (InfoVis) n Computer Graphics (CG) n Each of these areas has a distinct curriculum and qualifying exams ( their qualifying exams and specifics of the curriculum. n PhD in Machine Learning (ML), which is run by

multiple colleges, including Computing, with participation from the School of Interactive

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colleges, including Computing, with participation from the School of Interactive Computing. Policies and regulations related to the PhD Robotics program are documented in the Robotics PhD handbook. n PhD in Human Centered Computing (HCC), run

and owned by the School of Interactive Computing, with participation from other colleges. Policies and regulations are documented in the Course of Study overview.

MS programs

SIC participates in four CS-related MS programs as detailed below. In addition, students from other MS programs on campus enroll into classes taught (and owned) by SIC. n MS in Computer Science (MSCS), owned by the

College, with participation from the four schools with graduate programs.

n Online MS in Computer Science (OMSCS), the

n Annual PhD student reviews: The goal of the

largest CS-related MS program in the country.

The School of Interactive Computing participates through a range of classes taught by our faculty.

PhD review process in the School of Interactive Computing is to give students feedback on their progress in the program, in relationship to clearly articulated expectations and milestones. Each year, the school faculty conducts two PhD Reviews as follows. n Fall Review: This review is scheduled in early November. All PhD students with the exception of first years are reviewed in the Fall. n Spring Review: This review is scheduled at the end of April. All first years and students on less-than Satisfactory status in the fall are reviewed. Details of the SIC PhD student reviews are provided in the PhD Review Procedures and Guidelines.

n MS in Robotics (MSRobo), an interdisciplinary

program in which a range of colleges and schools participate, including the College of Computing and the School of Interactive Computing. n MS in Human-Computer Interaction (MS-HCI),

designed, created by, and owned by the School of Interactive Computing. This two-year program specifically targets students interested in developing a deeper understanding of all humancomputer interaction.

About the Ph.D. in Interactive Computing

n Special workshops and activities we do for our

graduate students n Writing workshop organized by Judith Uchidiuno

n Graduate Studies Guidebook n SIC PhD Student information

We shape the future of computing through:

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Impactful transdisciplinary research and scholarship, with attention to local and global challenges

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Fusing computing innovation and ethics to make a positive impact on the world and improve the lives of all people

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Achieving long-term sustainability of the field by focusing on the interplay of people, society, and technology

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Transformative computing education with relevant curriculum to reflect new frontiers in technology and societal needs

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Developing motivated and exceptional leaders in computing research and industry

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Top 10 Research Stories Associate Professor Joins Fight Against Cancer with Sensing Technology A surgically implantable device the size of a pinky finger could be a huge step toward a cure for cancer. A multi-institutional team of researchers that includes Georgia Tech faculty received $45 million from the Advanced Research Projects Agency for Health (ARPA-H) to develop sense-and-respond implant technology for cancer treatment.

Josiah Hester, an associate professor in Georgia Tech’s School of Interactive Computing, is a co-principal investigator on the project and is responsible for the sensing and computing technology in the implantable device. He will also assist with large-scale experimentations and coordinate the integration of the technology.

Tennis Robot Serves up Advancements in Fast-Movement Robotics Matthew Gombolay grew up playing a variety of sports, but none appealed to him more than tennis. He said he had been playing with the idea of constructing a tennis robot that could go beyond training against a stationary ball feeder to help a player improve his skills.

What if he could have a tennis partner that could play with or against him any time he wanted and could help him improve the weakest areas of his game or complement him in a doubles match?

New ADA-funded App Could Save Diabetic Foot Patients from Amputations A new app Rosa Arriaga has in development amplifies the voices of patients with diabetes and diabetic foot ulcers — a severe complication for more than one third of people living with diabetes that often goes unaddressed until it’s too late.

If left untreated, a diabetic foot ulcer can become infected and lead to amputation. Arriaga’s app may be the tool that prevents the situation from ever coming to that. The app detects the presence of ulcers and tracks whether the conditions of the ulcers worsen.

Researchers Earn $1.8M to Increase Air Pollution Data Literacy Atlanta residents will soon have easy access to air pollution data that enables them to make data-driven decisions that positively impact their local environment.

Georgia Tech researchers Jessica Roberts, Alex Endert, and Jayma Koval earned a $1.8 million grant from the National Science Foundation to boost their efforts in promoting air pollution data literacy among middle school students and the public.

The grant will fund the researchers’ top two projects — designing and installing a public information kiosk and organizing a summer camp that uses environmental data to teach data literacy to middle schoolers.

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Large Language Models Help Humans to Communicate with Robots Roboticists have a new way to communicate instructions to robots — large language models (LLMs).

Georgia Tech robotics researchers Animesh Garg and Danfei Xu think LLMs like ChatGPT make the best human-to-robot translators when it comes to training robots.

Garg said LLMs have a healthy understanding of human language and can communicate instantly with robots by translating instructions into code. This expedites the training process by weeks and, in some cases, months Student Shows ChatGPT Can Save Time, Resources for Sensory Data Researchers A new data-gathering method could save sensory technology and humanactivity recognition (HAR) researchers and data collectors a significant amount of time and money spent on resources.

In a recent paper, Georgia Tech third-year computer science major Zikang Leng introduced a large-language model approach with ChatGPT that could revolutionize how researchers collect sensory data.

Stress Test Method Detects When Object Recognition Models are Using Shortcuts A new “stress test” method created by a Georgia Tech researcher allows programmers to more easily determine if trained visual recognition models are sensitive to input changes or rely too heavily on context clues to perform their tasks.

Viraj Prabhu, a Ph.D. student in Georgia Tech’s School of Interactive Computing, introduced the LANCE (Language-Guided Counterfactuals) method in a recent research paper that shows how deep object recognition models are prone to taking shortcuts through context clues to produce images Researchers Use Novel Approach to Teach Robot to Navigate Over Obstacles Quadrupedal robots may be able to step directly over obstacles in their paths thanks to the efforts of a trio of Georgia Tech Ph.D. students.

When it comes to robotic locomotion and navigation, Naoki Yokoyama says most four-legged robots are trained to regain their footing if an obstacle causes them to stumble. Working toward a larger effort to develop a housekeeping robot, Yokoyama and his collaborators — Simar Kareer and Joanne Truong — set out to train their robot to walk over clutter it might encounter in a home.

Like Humans and Animals, AI Agents Find Their Way Through Memory Memory may be just as important to artificial intelligence (AI) agents in creating ‘mental maps’ as it is to humans and animals.

A recent paper authored by Georgia Tech researchers makes a surprising discovery — blind AI agents use memory to create maps and navigate through their surrounding environment.

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Erik Wijmans, the lead author of the paper, said the idea for his research began by asking if AI agents might mimic human and animal behavior in how they navigate and adjust to their environments.

Misinformation Detection Models are Vulnerable to ChatGPT and Other LLMs Existing machine learning (ML) models used to detect online misinformation are less effective when matched against content created by ChatGPT or other large language models (LLMs), according to new research from Georgia Tech.

Current ML models designed for and trained on human-written content have significant performance discrepancies in detecting paired human-generated misinformation and misinformation generated by artificial intelligence (AI) systems, said Jiawei Zhou, a Ph.D. student in Georgia Tech’s School of Interactive Computing. n

New AI Ethics Network Will Amplify Atlanta Voices

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Atlanta communities most vulnerable to bias and inequity in artificial intelligence (AI) are the focus of a new Atlanta-based ethics initiative being funded by a $1.3 million Mellon Foundation grant.

The Atlanta Interdisciplinary Artificial Intelligence (AIAI) Network, brings together computing, humanities, and social justice researchers from Georgia Tech, Clark Atlanta University, Emory University, and community partner DataedX. Carl DiSalvo, Georgia Tech School of Interactive Computing professor, is an AIAI co-principal investigator (co-PI). Andre Brock, an associate professor in the School of Literature, Media, and Communication serves on the network’s steering committee.

Report Says Social Media Companies Putting Youth Mental Health at Risk Munmun De Choudhury, an associate professor in Georgia Tech’s School of Interactive Computing, served on a 12-person committee appointed by NASEM to answer pressing questions about social media and adolescent mental health and well-being.

On December 12, the committee released its 250-page report titled Assessment of the Impact of Social Media on the Health and Well-Being of Adolescents and Children. The report offers recommendations for social media companies, Congress, the U.S. Department of Education, and others.

Students Partner with Discovery Education to Develop New AR Education Tool

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When it comes to expanding immersive technologies in the classroom, little progress has been made in creating interactive ways for high school students to learn higher-level math.

It’s a problem that three Georgia Tech graduate students studying human-computer interaction (HCI) are addressing by designing a new augmented reality (AR) tool.

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What started as a master’s project turned into a potential breakthrough when Doris Amouzou, Madeleine Paulsen, and Tymirra Smith approached Discovery Education with their idea for an AR learning tool for higher-level math subjects such as geometry, trigonometry, and calculus.

New Faculty Member Seeks to Expand Computer Science in Urban Communities When Judith Uchidiuno considered the place where she wanted to work and the city she wanted to live in, Georgia Tech and Atlanta checked all the boxes. Atlanta offered the perfect mix of urban culture with a nearby university that prides itself in diverse, interdisciplinary research, Uchidiuno said.

Uchidiuno begins her new role as an assistant professor at the School of Interactive Computing this semester. She looks to make an immediate impact in the Atlanta community by working with informal learning centers in urban areas of the city to expand accessibility to computer science education and develop new culturally responsive education technologies.

Interactive Computing Associate Professor, Incoming Chair Earn SIGCHI Awards School of Interactive Computing Associate Professor Munmun De Choudhury has spent more than a decade studying social media and online forums with the goal of making the internet a better place.

For her career efforts, De Choudhury is the co-recipient of the 2023 Special Interest Group on Computer-Human Interaction (SIGCHI) Societal Impact Award. SIGCHI, which is supported by the Association for Computing Machinery, announced the winners of its annual awards on Tuesday. Each year, SIGCHI recognizes individuals with its Lifetime Research Award, Lifetime Practice Award, Lifetime Service Award, Societal Impact Award, and Outstanding Dissertation Award.

Other recipients this year include Shaowen Bardzell, who was announced as the new chair of the School of Interactive Computing.

Web App Allows Tenants Facing Eviction to Fight Back Tenants facing eviction in Atlanta may soon have a new app that can help them to understand their rights through the eviction process.

The web-based app is being developed by a group of Georgia Tech Master of Science in Human Computer Interaction (MS-HCI) students. It can inform tenants of their rights, help them to ensure landlords have properly followed the law, and help them to better prepare for their court hearings.

The students have been developing the web app for the Atlanta Volunteer Lawyers Foundation (AVLF), which provides free legal services to residents in Fulton County, including advice for tenants facing evictions.

Professor Deploying Anti-plagiarism Detection Tool on 900-student Course Interactive Computing professor Thad Starner is teaching one of the largest courses ever taught at the College of Computing.

Introduction to Artificial Intelligence (CS3600) has 911 students SCHOOL OF INTERACTIVE COMPUTING / COLLEGE OF COMPUTING

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taking the course for Spring 2023.

To manage a class that size, Starner is using nine classrooms and 18 teaching assistants to livestream his lectures. But the biggest concern he has for the course isn’t logistics — it’s the difficulty of tracking plagiarism.

Georgia Tech Hosting Growing Conference for Robotics and Machine Learning Georgia Tech welcomed global robotics experts at the forefront of research and innovation as it hosted the 2023 Conference on Robot Learning (CoRL).

The 2023 conference had record-setting attendance, with more than 800 people joining the conference at the Starling Hotel in Midtown Atlanta. The international conference brings together top young researchers whose work explores robotics and machine learning. Google created and hosted the first CoRL in 2017 and is a major sponsor of the event. Five Georgia Tech faculty members served on this year’s organizing committee, including general chair Sonia Chernova, an associate professor in the School of Interactive Computing.

Professor Emeritus and GVU Founder Reflects on 50 Years of Attending SIGGRAPH Jim Foley has too many memories to count from attending SIGGRAPH over the years. But if there’s anyone who should tell the story of SIGGRAPH from its inception in 1974 to its most recent conference in August, he would be an ideal candidate. SIGGRAPH celebrated its 50th edition this year, and Foley has been to all but one of them.

Foley and the GVU Center became household names at SIGGRAPH in the 90s. In 1990, Foley published a second edition of Computer Graphics: Principles and Practice, one of the most widely used computer graphics textbooks with more than 500,000 copies sold in 10 languages. After launching the GVU Center in 1991, Foley attracted top faculty, top students, and more funding to Georgia Tech.

Alumna Named to Forbes’ 30 Under 30 Provides Makerspaces to Youth in India As Azra Ismail moves on from Georgia Tech with a Ph.D. in human-centered computing, she leaves behind a legacy that’s steeped in far more than research. That legacy is more than 8,000 miles away in Ismail’s native India, where she’s helped more than 300,000 youths in six states become better equipped for an increasingly competitive job market.

Ismail’s ongoing efforts to promote entrepreneurship and innovation among India’s disadvantaged youth were recently recognized. Just before she graduated in May, Ismail received the news she had been named to Forbes’ 30 Under 30 list for Social Impact in Asia. n

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Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis STRENGTHS I nterdisciplinary and transdisciplinary faculty and research agenda n Strong societal impacts of research n Distinguished faculty n Award-winning quality of students n Cross-school and cross-disciplinary degree programs n High quality instruction and teaching evaluations n

WEAKNESSES

OPPORTUNITIES

op and bottom heavy, with very T few mid-career faculty n Administrating staffing shortages n IC faculty, staff, and students are spread across three buildings on campus, creating cultural, communication, and morale issues n High staff turn-over n Limited space for faculty, staff, and student researchers limits growth and sustaining current size n

Cross-school joint faculty hires with other CoC Schools n Local and international partnerships through research Institutes and Centers n Improved partnerships with industry n

THREATS I and Robotics degrees A and courses are popular, so other Colleges and Schools on campus may create their versions n Limited financial support to execute strategic vision for school n High administrative and staff workload is unsustainable n

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Georgia Institute of Technology College of Computing School of Interactive Computing Technology Square Research Building 85 5th St NW Atlanta, GA 30332

Email: ic.gatech.edu