IEEE Princeton Central Jersey Section

Senior member is the highest grade for which IEEE members can apply. IEEE members can self-nominate, or be nominated, for Senior Member grade. This talk by Kaustav Ghosal tries to demystify the process. It is part of a continued effort to help increase the nomination pool size each year, particularly from underrepresented technical disciplines, such as industry, standards, education, and underrepresented groups to enhance Equity and Diversity. Topics include: 1) IEEE senior membership grade requirements, 2) Finding a mentor/sponsor, 3) Importance of your nomination package, and 4) Reference resources Speaker(s): Kaustav Ghoshal, Virtual: https://events.vtools.ieee.org/m/417494

Machine learning (ML) is the driving application of the next-generation computational hardware. How to design ML hardware to achieve a high performance, efficiency, and flexibility to support fast growing ML workloads is a key challenge. Besides dataflow-optimized systolic arrays and single instruction, multiple data (SIMD) engines, efficient ML accelerators have been designed to take advantage of static and dynamic data sparsity. To accommodate the fast-evolving ML workloads, matrix engines can be integrated with an FPGA to provide the efficiency of kernel computation and the flexibility of control. To support the increasing ML model complexity, modular chiplets can be tiled on a 2.5D interposer and stacked in a 3D package. We envision that a combination of these techniques will be required to address the needs of future ML applications. Speaker(s): Dr Zhengya Zhang, ***CANCELED*** Agenda: 6:00 PM - 7:00 PM EST : Talk 7:00 PM - 7:30 PM EST : Q/A Virtual: https://events.vtools.ieee.org/m/408028

IEEE PCJS Volunteers, spouses, local section leadership, Region 1 leaders and Awardees are invited to this Awards Banquet. We will host this banquet at Mercer Oaks Golf Course in West Windsor, NJ on May 8. Buffet Dinner with beef, eggplant, potatoes and vegetables Cash Bar Dessert with tea/coffee Agenda: 6:00 pm Registration and Networking - Appetizers 7:00 pm Awards Presentation 7:30 pm Awards Dinner 8:15 pm Featured Speaker (TBD) Mercer Oaks Golf Club, 725 Village Road West, Princeton Junction, New Jersey, United States, 08550

Lifelong Learning (or Lifelong Machine Learning) is an advanced Machine Learning (ML) paradigm: an architecture for ML systems that learn continuously, accumulate knowledge learned in the past, and use that knowledge to help future learning and problem solving. This talk will explore three aspects of Lifelong Learning. First, traditional ML is generally an energy-hungry process: the process of building and training of the model requires huge computational resources. It might be expected that Lifelong Learning might be limited to cloud and off-line computing only. But this talk will explain some ways that Lifelong Learning avoids that constraint – by introducing a signal propagation approach that combines learning into the inference process, enabling the system to add classes to its knowledge model at the same time it is being used to solve problems. Second, most ML approaches are limited in their ability to utilize temporal patterns in its computation. But in Lifelong Learning, there are some new mechanisms that can make the AI temporally aware, mechanisms which can improve the system's ability to work effectively with limited data as well as a significant savings in size and power usage. Third, Lifelong Learning research continues to explore new models of computation – going beyond the traditional Turing computation model. Lifelong Learning researchers have been investigating “Super-Turing computation,” a model of computation that resembles biological learning. Speaker(s): Hava Siegelmann, Room: Room 105, Bldg: Computer Science Building, 35 Olden St., Princeton University, Princeton, New Jersey, United States, 08544, Virtual: https://events.vtools.ieee.org/m/375905

The Secure Use of Artificial Intelligence Author: Dr. Nancy M Landreville Monay, May 20, 2024 at 6:30 PM - 8:00 PM - Virtual Co-sponsored by: Power Energy Speaker(s): Nancy Landreville, Agenda: Virtual: https://events.vtools.ieee.org/m/418243