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

  • 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 ...
  • Building Agents that can See, Talk, and Act 

    Das, Abhishek (Georgia Institute of Technology, 2020-04-25)
    A long-term goal in AI is to build general-purpose intelligent agents that simultaneously possess the ability to perceive the rich visual environment around us (through vision, audition, or other sensors), reason and infer ...
  • Manipulating State Space Distributions for Sample-Efficient Imitation-Learning 

    Schroecker, Yannick Karl Daniel (Georgia Institute of Technology, 2020-03-16)
    Imitation learning has emerged as one of the most effective approaches to train agents to act intelligently in unstructured and unknown domains. On its own or in combination with reinforcement learning, it enables agents ...
  • Structured Visual Understanding, Generation and Reasoning 

    Yang, Jianwei (Georgia Institute of Technology, 2020-01-13)
    The world around us is highly structured. In the real world, a single object usually consists of multiple components organized in some structures (e.g., a person has different body parts), and multiple objects usually exist ...
  • Efficient and principled robot learning: theory and algorithms 

    Cheng, Ching An (Georgia Institute of Technology, 2020-01-07)
    Roboticists have long envisioned fully-automated robots that can operate reliably in unstructured environments. This is an exciting but extremely difficult problem; in order to succeed, robots must reason about sequential ...
  • Tools for Measuring and Understanding the Proximity of Users to Their Smartphones 

    Park, Jung Wook; Evans, Hayley I.; Watson, Hue L.; Abowd, Gregory D.; Arriaga, Rosa I. (Georgia Institute of Technology, 2020-03)
    Two studies in ubiquitous computing examined the proximity of users to their smartphones in 2006 and in 2011. Both studies have used a passive data collection tool and the day reconstruction method. Additionally, Dey at ...
  • Towards natural human-AI interactions in vision and language 

    Chandrasekaran, Arjun (Georgia Institute of Technology, 2019-11-07)
    Inter-human interaction is a rich form of communication. Human interactions typically leverage a good theory of mind, involve pragmatics, story-telling, humor, sarcasm, empathy, sympathy, etc. Recently, we have seen a ...
  • An analysis of supports and barriers to offering computer science in Georgia public high schools 

    Parker, Miranda C. (Georgia Institute of Technology, 2019-11-08)
    There is a growing international movement to provide every child access to high-quality computing education. Despite the widespread effort, most children in the US do not take any computing classes in primary or secondary ...
  • Map-Centric Visual Data Association Across Seasons in a Natural Environment 

    Griffith, Shane David (Georgia Institute of Technology, 2019-11-01)
    Vision is one of the primary sensory modalities of animals and robots, yet among robots it still has limited power in natural environments. Dynamic processes of Nature continuously change how an environment looks, which ...
  • Managing Learning Interactions for Collaborative Robot Learning 

    Bullard, Kalesha (Georgia Institute of Technology, 2019-09-11)
    Robotic assistants should be able to actively engage their human partner(s) to generalize knowledge about relevant tasks within their shared environment. Yet a key challenge is not all human partners will be proficient at ...
  • Visual Question Answering and Beyond 

    Agrawal, Aishwarya (Georgia Institute of Technology, 2019-09-03)
    In this dissertation, I propose and study a multi-modal Artificial Intelligence (AI) task called Visual Question Answering (VQA) -- given an image and a natural language question about the image (e.g., "What kind of store ...
  • Improvisational Artificial Intelligence for Embodied Co-creativity 

    Jacob, Mikhail (Georgia Institute of Technology, 2019-08-14)
    Improvisational Artificial Intelligence for Embodied Co-creativity Mikhail Jacob 191 Pages Directed by Dr. Brian S. Magerko This dissertation explores embodied agents that can improvise with people in an object-based ...
  • Computational Approaches to Understanding Stylistic Variation in Online Writing 

    Pavalanathan, Umashanthi (Georgia Institute of Technology, 2018-09-28)
    Language use in online interactions varies from community to community, from individual to individual, and even for individuals in different contexts. While prior work has identified these differences, far less is understood ...
  • Computing for Social Science: Characterizing, Quantifying, and Analyzing Social Phenomena in Technology Mediated Communications 

    Hutto, Clayton J. (Georgia Institute of Technology, 2018-08-10)
    Traditional social science methods of analyzing unstructured and semi-structured qualitative content often rely on labor and time intensive methods to transform qualitative data into quantitative representations of phenomena ...
  • JobLex: A Lexico-Semantic Knowledgebase of Occupational Information Descriptors 

    Saha, Koustuv; Reddy, Manikanta D.; De Choudhury, Munmun (Georgia Institute of Technology, 2019-07)
    Technological advancements in several work sectors have influenced evolution of the landscape of work at an unprecedented speed, leading to the demand of continuous skill development [1,8]. In turn, this interests a number ...

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