IEEE CAS Seasonal School: Intelligent Memory & Sensor at the Edge (IMS 2023)

Artificial Intelligence (AI) accelerator designs for the edge devices have attracted vast interest, where accelerating Deep Neural Network (DNN) using Processing-in-Memory (PIM) and Processing-in Sensor (PIS) platforms is an actively-explored direction with great potential. Such accelerators, which simultaneously aim to address power- and memory-wall bottlenecks, have shown orders of performance enhancement in comparison to the conventional computing platforms with Von-Neumann architecture. As one direction of accelerating DNN in PIM/PIS, resistive memory array (aka. crossbar) has drawn great research interest owing to its analog current mode weighted summation operation which intrinsically matches the dominant Multiplication-and-Accumulation (MAC) operation in DNN, making it one of the most promising candidates. An alternative direction is through bulk bit-wise logic operations directly performed on the content in digital memories.

The main goal of this seasonal school is to dive deep into therapidly developing field of PIM and PIS with a focus on the intelligent memory and sensor circuit and system at the edge and cover its cross-layer design challengesfrom device to algorithms. The IEEE Seasonal School in Circuits and Systems on Intelligent Memory & Sensor at the Edge (IMS 2023) offers talks and tutorials by leading researchers from multiple disciplines and prominent universities and promotes student short presentations to demonstrate new research and results, discuss the potential and challenges of the edge accelerators, future research needs, and directions, and shape collaborations.

Co-sponsored by: IEEE North Jersey Section

Agenda:
Event Time: 9:00 AM to 5:00 PM

Venue: Kiernan Conference Room (ECE 202), ECEC, NJIT, Newark

9:00 AM – 9:30 AM Breakfast, Coffee, Registration and Networking

9:30 AM – 10:00 AM Student Presentations

10:00 AM – 10:10 AM Welcome and Opening Remarks by Dr. Angizi, Vice-Chair CASS/EDS Chapter

10:10 AM – 10:50 AM Talk by Dr. Maryam Parsa (George Mason University) on Bayesian Brain-Inspired Computing

10:50 AM – 11:30 AM Talk by Dr. Yao Ma (New Jersey Institute of Technology) on Understanding and Enhancing Graph Neural Networks with A Unified Framework

11:30 AM – 1:00 PM Lunch and Networking

1:00 PM – 1:40 PM Talk by Dr. Adnan Siraj Rakin (Binghamton University (SUNY)) on Exploring Security and Privacy Challenges through Adversarial Weight Perturbation in Deep Learning Models

1:40 PM – 2:20 PM Talk by Dr. Shaahin Angizi (New Jersey Institute of Technology) on Energy-Efficient Approximate Convolution-in-Pixel Scheme for Neural Network Acceleration

2:20 PM – 3:00 PM Coffee Break

3:00 PM – 3:40 PM Talk by Dr. Ajay Poddar (Chief Scientist, Synergy Microwave, NJ) on Design Challenges in High-Frequency Low-Phase Noise Signal Sources

3:40 PM – 4:30 PM Networking and Concluding Remark by ECE Dep. Chair Dr. Misra

Seminar in ECE 202 All Welcome: There is no fee/charge for attending IEEE technical seminar. You don’t have to be an IEEE Member to attend. Refreshment is free for all attendees. Please invite your friends and colleagues to take advantage of this Invited Distinguished Lecture.

Room: 202, Bldg: ECEC, 154 Summit Street, Newark, NJ 07102, NJIT, Newark, New Jersey, United States, 07102