Scholarly Events

Recent Submissions

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  Life After Stroke: Adapting and Overcoming

  (Georgia Institute of Technology, 2025-03-27) Ferguson, Ella ; Hornbuckle, Ken ; Parks, Robyn ; Singh, Jennifer ; Singh, Tushar ; Taylor, Diana

  Discover the inspiring stories of stroke survivors who have adapted to life after their strokes. These panelists will discuss their paths to recovery, the obstacles they've overcome, and the ongoing journey of adaptation and resilience.
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  Examining dexterous motor control in children born with a below elbow deficiency

  (Georgia Institute of Technology, 2025-03-10) Joiner, Wilsaan

  Dr. Wilsaan Joiner's laboratory studies how we use different sources of information to aid behavior, ranging from visual perception to movement planning and updating. Specifically, we are interested in how external and internally-generated sensory information is integrated in healthy individuals, in comparison to certain disease and impaired populations (e.g., Schizophrenia and upper extremity amputees). Achieving this understanding may lead to better methods for diagnosing and treating impairments of the nervous system.
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  Learning Coordinated Performant Flight with 20 Neurons

  (Georgia Institute of Technology, 2025-04-09) Sukhatme, Gaurav

  We have recently demonstrated the possibility of learning controllers that are zero-shot transferable to groups of real quadrotors via large-scale, multi-agent, end-to-end reinforcement learning. We train policies parameterized by neural networks that can control individual drones in a group in a fully decentralized manner. Our policies, trained in simulated environments with realistic quadrotor physics, demonstrate advanced flocking behaviors, perform aggressive maneuvers in tight formations while avoiding collisions with each other, break and re-establish formations to avoid collisions with moving obstacles, and efficiently coordinate in pursuit-evasion tasks. The model learned in simulation transfers to highly resource-constrained physical quadrotors. Motivated by these results and the observation that neural control of memory-constrained, agile robots requires small yet highly performant models, the talk will conclude with some thoughts on coaxing learned models onto devices with modest computational capabilities.
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  Resilient Autonomy for Extreme and Uncertain Environments

  (Georgia Institute of Technology, 2025-03-26) Scherer, Sebastian

  Robustness in AI and robotics shows great promise if systems can transition from the lab to real-world environments, moving beyond the single-operator per robot paradigm. However, the unstructured nature of the real-world demands nuanced decision-making from robots. In this talk, Prof. Scherer will outline approaches, progress, and results in multi-modal sensing, nuanced perception inputs, navigation in difficult terrain, and extensions to multi-robot teams, as well as future research directions.
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  Autistic Lived Experience: Advocacy and Acceptance

  (Georgia Institute of Technology, 2025-02-25) Coleman, Laura Suzanna ; Niederhoffer, Eren ; Rodriguez, Kayla ; Celedon-Garcia, Victoria ; Maurer, Erin ; Singh, Jennifer

  Autistic individuals share their experiences and insights on advocating for effective treatments and support systems, highlighting the unique challenges they face in their communities and the strategies they employ.
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  Computational Symmetry and Learning for Robotics

  (Georgia Institute of Technology, 2025-03-05) Ghaffari, Maani

  Forthcoming mobile robots require efficient generalizable algorithms to operate in challenging and unknown environments without human intervention while collaborating with humans. Today, despite the rapid progress in robotics and autonomy, no robot can deliver human-level performance in everyday tasks and missions such as search and rescue, exploration, and environmental monitoring and conservation. In this talk, I will put forward a vision for enabling efficiency and generalization requirements of real-world robotics via computational symmetry and learning. I will walk you through structures that arise from combining symmetry, geometry, and learning in various foundational problems in robotics and showcase their performance in experiments ranging from perception to control. In the end, I will share my thoughts on promising future directions and opportunities based on lessons learned on the field and campus.
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  Divergence in Architectural Research: Proceeding Book of ConCave Ph.D. Symposium 2024

  (Georgia Institute of Technology, 2025-03)

  This third volume of Divergence in Architectural Research brings together twenty-three illuminating papers from the latest international ConCave Ph.D. Symposium. This symposium was organized by the ConCave Ph.D. student group with the support of the School of Architecture and the College of Design at the Georgia Institute of Technology and took place in Atlanta on April 4th and 5th, 2024. The third ConCave Ph.D. Symposium “Divergence in Architectural Research” aimed to promote interdisciplinary dialogue and collaboration among students and disciplines. It invited scholars and doctoral students from architecture and related fields to share their pioneering research. It aimed to create a supportive environment conducive to constructive feedback which would provide participants with valuable insights to refine their ideas and advance their doctoral research. Ideas discussed during the ConCave symposium focused on the concept of divergence in architectural research. This concept represents the agency for expanding the disciplinary boundaries of architecture and cultivating new fields of knowledge emerging from within the architectural domain. We argue that architecture serves as a nexus of various fields and that acknowledging its inherent ambiguity allows for transformative connections between different epistemological frameworks. Embracing diverse methodologies and learning to read different perspectives prepare scholars to contribute richly across a spectrum of intellectual landscapes.
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  Autonomous Systems in the Intersection of Control, Learning, and Formal Methods

  (Georgia Institute of Technology, 2025-02-19) Topcu, Ufuk

  Autonomous systems are emerging as a driving technology for countlessly many applications. Numerous disciplines tackle the challenges toward making these systems trustworthy, adaptable, user-friendly, and economical. On the other hand, the existing disciplinary boundaries delay and possibly even obstruct progress. He argues that the nonconventional problems that arise in designing and verifying autonomous systems require hybrid solutions at the intersection of control, learning, and formal methods (among other disciplines). He presents examples of such hybrid solutions in the context of learning in sequential decision-making processes. These results offer novel means for effectively integrating physics-based, contextual, or structural prior knowledge into data-driven learning algorithms. They improve data efficiency by several orders of magnitude and generalizability to environments and tasks the system had not previously experienced. He concludes with remarks on a few promising future research directions.
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  Mobile Sign Language Recognition: Creating Useful and Usable Interfaces for the Deaf

  (Georgia Institute of Technology, 2025-02-20) Starner, Thad

  The Oscar best picture winning movie CODA has helped introduce Deaf culture to many in the hearing community. The capital "D" in Deaf is used when referring to the Deaf culture, whereas small "d" deaf refers to the medical condition. In the Deaf community, sign language is used to communicate, and sign has a rich history in film, the arts, and education. Learning about the Deaf culture in the United States and the importance of American Sign Language in that culture has been key to choosing projects that are useful and usable for the Deaf. This talk will review 30 years of effort in sign language recognition and working with the Deaf community and will feature several upcoming products such as PopSignAI, a smartphone game that helps hearing parents of Deaf infants learn sign language.
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  Autographic Design – the Matter of Data in a Self-Inscribing World

  (Georgia Institute of Technology, 2025-01-30) Offenhuber, Dietmar

  Data analysis and visualization are crucial tools in today’s society, and digital representations have steadily become the default for presenting claims about the state of the world. Yet, more and more often, we find that citizen scientists, environmental activists, and amateur forensic investigators are using analog methods to present evidence of pollution, climate change, and the spread of disinformation. In my talk, I will discuss Autographic design as a non-representational framework of visualization based on the notion that data are material entities rather than abstract representations. Focusing on the materiality of data generation, the goal of autographic design is to make the process of data generation legible and accountable. In the institutional politics of whose data is accepted as trustworthy, autographic design reverses representational rules – instead of adopting experts’ methods and representations, it challenges these representations through sensory displays that emphasize traces, imprints, and self-inscriptions.