Agenda: September 16, 2025
1 p.m. | Introduction and Welcome Remarks
Rama Chellappa, Johns Hopkins Data Science and AI Institute Interim Director
Corey Oses, Assistant Professor, Department of Materials Science and Engineering
1:15 p.m. | Toward Sustainable Data Centers for Artificial Intelligence
Benjamin Lee, Professor in the Department of Electrical and Systems Engineering and the Department of Computer and Information Science, University of Pennsylvania
Abstract: As the impact of artificial intelligence (AI) continues to proliferate, computer architects must assess and mitigate its energy demands. This talk will survey strategies for mitigating the energy used by AI computation and datacenter infrastructure, drawing on data and experiences from industrial, hyperscale systems. First, we analyze the energy implications of super-linear AI growth. Second, we re-think datacenter infrastructure and define a solution space for sustainable computation with renewable energy, utility-scale batteries, and job scheduling. Finally, we develop strategies for datacenter demand response, incentivizing workloads to modulate power usage in ways that reflect their performance goals. In summary, the talk provides a broad perspective on sustainable computing and outlines the many remaining directions for future work.
1:55 p.m. | Worker, Citizen, Robot (This presentation is pre-recorded.)
John Tasioulas, Professor of Ethics and Legal Philosophy and Director of the Institute for Ethics in AI, University of Oxford
Abstract: Two fundamental dimensions of “daily life” are the activities we pursue as workers and as democratic citizens. The development of AI technology, with the threat it poses in terms of a massive reduction of job opportunities for humans, forces us to re-examine the values that are realised through work and the extent to which they can be achieved through non-work activities, such as play. Relatedly, we need to re-examine the connection between work and active democratic citizenship: to what extent does a healthy democratic ethos depend upon widespread participation on the part of citizens in work?
2:35 p.m. | Engineering Better Healthcare – An Incomplete Perspective
Mathias Unberath, John C. Malone Associate Professor in the Department of Computer Science, Johns Hopkins University
Abstract: Despite persistent criticism, AI is now undoubtedly part of everyday life including healthcare. The opportunities for AI and related technology to benefit healthcare delivery and operations and sheer limitless, ranging from decision support systems for scheduling and triage to autonomous surgery. In this talk, I will highlight some of our recent advances in AI-assisted healthcare showcasing some of the transformative potential this technology holds for delivering better care.
2:50 p.m. | Autonomous Robotic Surgery: Science Fiction or Reality?
Axel Krieger, Associate Professor in the Department of Mechanical Engineering and Carol Croft Linde Faculty Scholar, Johns Hopkins University
Abstract: Robotic assisted surgery (RAS) systems incorporate highly dexterous tools, hand tremor filtering, and motion scaling to enable a minimally invasive surgical approach, reducing collateral damage and patient recovery times. However, current state-of-the-art telerobotic surgery requires a surgeon operating every motion of the robot, resulting in long procedure times and inconsistent results. The advantages of autonomous robotic functionality have been demonstrated in applications outside of medicine, such as manufacturing and aviation. A limited form of autonomous RAS with pre-planned functionality was introduced in orthopedic procedures, radiotherapy, and cochlear implants. Efforts in automating soft tissue surgeries have been limited so far to elemental tasks such as knot tying, needle insertion, and executing predefined motions. The fundamental problems in soft tissue surgery include unpredictable shape changes, tissue deformations, and perception challenges.
The research goal is to transform current manual and teleoperated robotic soft tissue surgery to autonomous robotic surgery, improving patient outcomes by reducing the reliance on the operating surgeon, eliminating human errors, and increasing precision and speed. This presentation will discuss our novel strategies to overcome the challenges encountered in soft tissue autonomous surgery. Presentation topics will include a robotic system for supervised autonomous laparoscopic anastomosis and our latest work in end-to-end imitation learning of surgical tasks and procedures, which we recently published in Science Robotics.
3:20 p.m. | Panel Discussion
Panel moderator: Swaroop Vedula, Associate Research Professor in the Malone Center for Engineering in Healthcare and member of the Data Science and AI Institute
Panelists: Benjamin Lee, Axel Krieger, Mathias Unberath, Debra Mathews, Zih-Yun “Sarah” Chiu
3:50 p.m. | Lightning Talks
Machine Learning and Causal Inference for Extreme Event Attribution in Climate Science, Cassie Chou, Department of Biostatistics
Towards Sustainable Distributed Computing: Integrating Energy Costs and Benefits for Optimal Growth in Traffic Autonomy, Junyue Jiang, Department of Civil and Systems Engineering
Bridging the AI Literacy Chasm: Initial Insights from “Project X: Algebra Engineering Lab” in Baltimore City High Schools, Alexis Daniels, Center for Educational Outreach