The School of Interactive Computing (SIC), focuses on computing’s interaction with users and the environment. Students learn as much about modeling people or the world as they do about computers. Research questions focus broadly on how computers impact the quality of people’s lives. SIC connects to a large range of non-computing disciplines including psychology, mechanical engineering, music, and art.

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Recent Submissions

  • Improved search techniques for structured prediction 

    Vijayakumar, Ashwin Kalyan (Georgia Institute of Technology, 2020-07-29)
    Many useful AI tasks like machine translation, captioning or program syn- thesis to name a few can be abstracted as structured prediction problems. For these problems, the search space is well-defined but extremely large ...
  • Search-based collision-free motion planning for robotic sculpting 

    Jain, Abhinav (Georgia Institute of Technology, 2020-07-28)
    In this work, I explore the task of robot sculpting. I propose a search-based planning algorithm to solve the problem of sculpting by material removal with a multi-axis manipulator. I generate collision free trajectories ...
  • Measuring the effect of user experience and engagement on learning using interactive simulations 

    Tomlinson, Brianna J. (Georgia Institute of Technology, 2020-07-21)
    Previous studies have explored the best methods to measure emotional, cognitive, and physical engagement, but these methods have not been applied to fully understand the impact of multimodal interactive simulations on ...
  • Human-guided task transfer for interactive robots 

    Fitzgerald, Tesca Kate (Georgia Institute of Technology, 2020-07-06)
    Adaptability is an essential skill in human cognition, enabling us to draw from our extensive, life-long experiences with various objects and tasks in order to address novel problems. To date, robots do not have this kind ...
  • Digital self-harm: Implications of eating disordered behaviors online 

    Pater, Jessica A. (Georgia Institute of Technology, 2020-07-21)
    It is estimated that 10%-20% of the US population will struggle with an eating disorder at some point in their lifetime [258]. Eating disorders is a complex set of psychiatric disorders that, regardless of classification, ...
  • Efficient trajectory and policy optimization using dynamics models 

    Yan, Xinyan (Georgia Institute of Technology, 2020-07-22)
    Data-driven approaches hold the promise of creating the next wave of robots that can perform diverse tasks and adapt to unstructured environments. However, gathering data of physical systems is often a labor-intensive, ...
  • Designing collaborative mobile health experiences for adolescent patients 

    Hong, Matthew K. (Georgia Institute of Technology, 2020-05-17)
    The proliferation of patient-generated data and mobile health (mHealth) technologies has provided unprecedented opportunities for patients' everyday health management and active participation in health care. Designing and ...
  • Low-shot learning for object recognition, detection, and segmentation 

    Shaban, Amirreza (Georgia Institute of Technology, 2020-05-17)
    Deep Neural Networks are powerful at solving classification problems in computer vision. However, learning classifiers with these models requires a large amount of labeled training data, and recent approaches have struggled ...
  • Detecting and mitigating human bias in visual analytics 

    Wall, Emily (Georgia Institute of Technology, 2020-05-17)
    People are susceptible to a multitude of biases, including perceptual biases and illusions; cognitive biases like confirmation bias or anchoring bias; and social biases like racial or gender bias that are borne of cultural ...
  • Grasp contact between hand and object: Capture, analysis, and applications 

    Brahmbhatt, Samarth Manoj (Georgia Institute of Technology, 2020-05-13)
    Contact is an important but often oversimplified component of human grasping. Capturing hand-object contact in detail can lead to important insights about grasping behavior, and enable applications in diverse fields like ...
  • LEARNING TO WALK USING DEEP REINFORCEMENT LEARNING AND TRANSFER LEARNING 

    Yu, Wenhao (Georgia Institute of Technology, 2020-05-17)
    We seek to develop computational tools to reproduce the locomotion of humans and animals in complex and unpredictable environments. Such tools can have significant impact in computer graphics, robotics, machine learning, ...
  • Visualization by Demonstration 

    Saket, Bahador (Georgia Institute of Technology, 2020-05-05)
    A key component of visualization systems that helps human sensemaking is interactivity. Thoughtfully designed interactions make the visual analysis process a conversation between the user and the interface that results in ...
  • Autonomous Rally Racing with AutoRally and Model Predictive Control 

    Goldfain, Brian (Georgia Institute of Technology, 2019-07-30)
    The ability to conduct experiments in the real world is a critical step for roboticists working to create autonomous systems that achieve human-level task performance. Self-driving vehicles are a domain that has received ...
  • Modeling Human and Robot Behavior During Dressing Tasks 

    Clegg, Alexander William
    Human dressing assistance tasks present a multitude of privacy, safety, and independence concerns for the daily lives of a vast number of individuals across the world, providing strong motivation for the application of ...
  • Developing a Document Trained Automated Advisor 

    Gregori, Eric (Georgia Institute of Technology, 2018-08)
    This paper covers the development of a system to automatically answer questions about the content of a document. For example, a class syllabus or project specification. The system trains on the document’s content to build ...
  • Encoding 3D contextual information for dynamic scene understanding 

    Hickson, Steven D. (Georgia Institute of Technology, 2020-04-27)
    This thesis aims to demonstrate how using 3D cues improves semantic labeling and object classification. Specifically, we will consider depth, surface normals, object classification, and pixel-wise semantic labeling in this ...
  • Policy-based exploration for efficient reinforcement learning 

    Subramanian, Kaushik (Georgia Institute of Technology, 2020-04-25)
    Reinforcement Learning (RL) is the field of research focused on solving sequential decision-making tasks modeled as Markov Decision Processes. Researchers have shown RL to be successful at solving a variety of problems ...
  • Disentangling neural network representations for improved generalization 

    Cogswell, Michael Andrew (Georgia Institute of Technology, 2020-04-24)
    Despite the increasingly broad perceptual capabilities of neural networks, applying them to new tasks requires significant engineering effort in data collection and model design. Generally, inductive biases can make this ...
  • Advanced machine learning approaches for characterization of transcriptional regulatory elements and genome-wide associations 

    Hassanzadeh, Hamid Reza (Georgia Institute of Technology, 2020-03-20)
    The deep learning revolution has initiated a surge of remarkable achievements in diverse research areas where large volumes of data that underlie complex processes exist. Despite the successful application of deep models ...
  • Identifying opportunities to improve content moderation 

    Jhaver, Shagun (Georgia Institute of Technology, 2020-03-18)
    This thesis contributes a nuanced understanding of the challenges inherent in the design and implementation of fair and efficient content moderation systems. Using large-scale data analyses, participant observations, survey ...

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