Workshop date: Sunday, Jul 19, 2020
Time: 9:00am – 2:40pm PDT | 12:00pm – 5:40pm EDT
The workshop is free. Please register here.
| EDT | Speaker and title |
| Session 1 – Algorithms and Neuroscientific Abstractions: What do spiking networks offer to approach brain-like capabilities? | |
| 12:00-12:15pm | Prof. Kaushik Roy, Purdue University. Title: Re-engineering computing with spike based learning: Algorithms to Devices. Abstract. |
| 12:20-12:35pm | Prof. Yiran Chen, Duke University. Title: Spiking Neuromorphic System Design Through Abstraction: Circuit and Algorithm Techniques in Brain-inspired Computing. Abstract. |
| 12:40-12:55pm | Prof. Priya Panda, Yale University. Title: Towards Scalable, Efficient and Accurate Deep Spiking Neural Networks. Abstract. |
| 01:00-01:20pm | Discussion and break |
| Session 2 – Architectures and Systems: Where are we and what are we missing | |
| 01:20-01:35pm | Prof. Rajit Manohar, Yale University. Title: Self-Timed Neuromorphic Systems. Abstract. |
| 01:40-01:55pm | Prof. Jae-sun Seo, Arizona State University. Title: Fully Spike-based Architecture with Front-end Dynamic Vision Sensor and Back-end Spiking Neural Network. Abstract. |
| 02:00-02:15pm | Prof. Yu Cao, Arizona State University. Title: Continual learning at the edge: Neural inspiration, model robustness and hardware efficiency. Abstract. |
| 02:20-02:35pm | Prof. Gert Cauwenberghs, UC San Diego. Title: Towards Efficient Neuromorphic Learning and Inference at Scale. Abstract. |
| 02:40-03:00pm | Discussion and break |
| Session 3 – Devices, Circuits, and Physical Substrates: How can we harness emerging devices and their characteristics for extreme efficiency? | |
| 03:00-03:15pm | Prof. Abhronil Sengupta, Pennsylvania State University. Title: Spintronics Enabled Neuromorphic Computing: Hardware-Algorithm Co-Design. Abstract. |
| 03:20-03:35pm | Prof. Emre Neftci, UC Irvine. Title: Data and Power Efficient Intelligence with Neuromorphic Hardware. Abstract. |
| 03:40-03:55pm | Prof. Joshua Yang, University of Southern California. Title: Resistive and capacitive crossbar arrays for neuromorphic computing. Abstract. |
| 04:00-04:20pm | Discussion and break |
| Session 4 – Industry and Applications Perspective: What is needed for ubiquitous intelligence? | |
| 04:20-04:35pm | Dr. John Paul Strachan, HP Labs. Title: Pushing the benefits of neuromorphic computing toward broad applications and broad adoption. Abstract. |
| 04:40-04:55pm | Dr. Hsinyu Tsai, IBM. Title: Analog Memory-based techniques for Accelerating Deep Neural Networks. Abstract. |
| 05:00-05:15pm | Dr. Narayan Srinivasa, Intel. Title: Towards Learning Systems that Understand. Abstract. |
| 05:20-05:40pm | Discussion |