[Workshop Overview]

In a world increasingly defined by the fusion of the physical and digital components, cognitive sensing is poised to revolutionize how edge devices perceive and respond to their environments. This workshop invites novel research contributions at the intersection of cognitive sensing, neuromorphic computing, and resilient edge inference. We seek to bring together experts from academia and industry to chart the future of intelligent, low-power, and robust edge computing systems. We plan to invite talks that explore algorithms, hardware/system architectures, and design methodologies enabling efficient, real-time, and uncertainty-aware sensing and computing at the edge.

[Topics of Interest]

• Cognitive and Context-Aware Sensing

  • Sensor fusion and intelligent sampling

  • Embedded AI for smart cognitive sensing

• Distributed and Edge Inference

  • Real-time, decentralized AI processing

  • Communication-efficient inference algorithms

  • Resource-aware workload distribution

• Neuromorphic Computing Algorithm/Architecture

  • Recent innovation in spiking neural networks (SNNs)

  • Hardware acceleration for neuromorphic workloads

  • Energy-efficient SNN processors

[Speakers]

• Minah Lee, University of Texas at Dallas, USA (8:10~8:45)

"Cross-layer Cognitive Sensing for Resilient Edge Intelligence"

• Jong Hwan Ko, Sungkyunkwan University, South Korea (8:45~9:20)

     "Adaptive Quantization Techniques for Efficient Edge Intelligence"

• Mingu Kang, University of California San Diego, USA (9:20~9:55)

"Energy-efficient Continual On-device Learning with Brain-inspired Hyperdimensional Computing"

• William J. Song, Yonsei University, South Korea (9:55~10:30)

      "Wear Leveling of Processing Elements in Neural Accelerators"

• Saibal Mukhopadhyay, Georgia Institute of Technology, USA (10:30~11:05)

• Jaeha Kung, Korea University, South Korea (11:05~11:40)

"Single-spike-based SNNs and Hardware Architecture for Spike-based Computing"

[Organizers]

• Saibal Mukhopadhyay, Georgia Institute of Technology, USA

• Jaeha Kung, Korea University, South Korea

• Amit R. Trivedi, University of Illinois Chicago, USA