New seminar on safe #AI with Jason Corso next week—learn more here: https://lnkd.in/gARzywyX
关于我们
The Johns Hopkins Department of Computer Science is diverse, collaborative, and intensely research-focused. Its research program combines core computer science topics with novel interdisciplinary, application-oriented subjects, bringing together colleagues from the Schools of Engineering and Medicine and drawing upon the university’s strengths in areas including robotics and computer vision, natural language processing, information security, AI and machine learning, theory and programming languages, human-computer interaction, and computational health and medicine.
- 网站
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https://www.cs.jhu.edu/
Johns Hopkins Department of Computer Science的外部链接
- 所属行业
- 高等教育
- 规模
- 11-50 人
- 总部
- Baltimore，Maryland
- 领域
- Theory and Programming Languages、Computational Biology and Medicine、Information Security、Robotics, Vision, and Graphics、Systems and Networking、Machine Learning, AI, and Data Science、Computer-Assisted Medicine和Human-Computer Interaction
动态
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Congratulations Hopkins students Dorian Liu, Alex Hu, Aimee Liang, Kaixin Du, and Ryan Zhang, who received recognition in two categories for their blockchain-based charity app at the ETHGlobal Hackathon! Learn more: https://lnkd.in/gadyxgtZ
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Don’t miss Eli Weinstein’s talk on synthesizing #DNA this Thursday after our morning seminar. Learn more: https://lnkd.in/gqyXDEjN
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A new targeted training approach by Chien-Ming Huang, Malone Center postdoctoral fellow Tsung-Chi Lin, and robotics master’s student Juo-Tung Chen can make up for a lack of natural spatial ability in #robot teleoperation tasks. Learn more: https://lnkd.in/gJYXCkRd
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New seminar on #privacy and #AI with Yaxing Yao coming up—learn more here: https://lnkd.in/ggawje6N
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Congratulations to The Johns Hopkins University researchers and recent grads who presented work at IEEE International Symposium on Mixed and Augmented Reality last month! Learn more about their work below: “ARthroNeRF: Field of View Enhancement of Arthroscopic Surgeries using Augmented Reality and Neural Radiance Fields,” a conference paper by Xinrui Zou, Zheyuan Zhang, Alexander Schwarz, Mehran Armand, and Alejandro Martin Gomez, introduces a novel framework that combines neural radiance field-based reconstruction and augmented reality to overcome the limitations of arthroscopic surgery, allowing for the generation of synthetic viewpoints from the perspective of surgical tools without the need for an additional camera. “Calibration of Augmented Reality Headset with External Tracking System Using AX = YB,” a conference paper by Letian Ai, Yihao Liu, Mehran Armand, and Alejandro Martin Gomez, proposes formulating virtual-to-real calibration for head-mounted displays as a hand-eye/robot-world calibration problem using an AX = YB formulation using both the self-localization?of the display and external tracking data. “Evaluating the Effectiveness of Visual Guidance for Out-of-View Object Localization using Mixed Reality Head-Mounted Displays,” a poster paper by Yu-Chun Ku and Alejandro Martin Gomez, explores the effectiveness of three advanced visualization techniques—3D Radar, 3D Arrow, and EyeSee360—to convey information to the users of mixed reality technology in situations that require quick reaction times.
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At a recent Johns Hopkins briefing, CS faculty Russell Taylor and Mathias Unberath explored the evolving role of robotics and artificial intelligence in surgery. See the highlights below:
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Join us on November 14 for a seminar with Murat Kocaoglu on #machinelearning. Learn more here: https://lnkd.in/gX9vw6B9
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Malone researchers Emad Boctor and Brian Caffo are part of two of the four boundary-pushing proposals funded in this year’s cycle of The Johns Hopkins University Applied Physics Laboratory SURPASS initiative. Learn more:
Malone researchers poised to create transformative technologies
https://malonecenter.jhu.edu
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New event with Mathias Unberath happening Friday!
Join us next Friday, November 8 for the final event in the I3R Fall 2024 Speaker Series! Mathias Unberath, Ph.D., John C. Malone Associate Professor of Computer Science at The Johns Hopkins University, will present "Foundation Models – Preparing for the Next 'iPhone Moment' in Medical Image Analysis." Learn how foundation models—powerful machine learning tools trained on vast datasets—are poised to revolutionize medical image analysis, potentially leading to breakthroughs comparable to the "iPhone moment" in this field. ?? Friday, November 8 ? 9:00 - 10:00 AM (CT) ?? 481 S. Shiloh Dr., Fayetteville, AR 72704, online via Zoom, and video-on-demand available later To learn more, visit the link here: https://bit.ly/4e40ePz #SolvingWickedProblems #ComputerScience #UArk #Innovation
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