At the TryEngineering Summer Institute (https://tryengineeringinstitute.ieee.org/), teens will explore various engineering fields, such as electrical, civil, mechanical, and aerospace. Our STEM summer course allows you to meet working engineers and experience VIP tours of engineering companies and centers. Learn new skills and engage in hands-on projects that explore how engineers can solve real-world problems. Program highlights found here: https://tryengineeringinstitute.ieee.org/summer-program/ See tuition information for enrollment in one 10-day session online-- these are on-campus residential camps with commuter-day options. Philadelphia, PA (University of Pennsylvania) - Session 1: July 9, 2023 - July 18, 2023 - sold out - Session 2: July 21, 2023 - July 30, 2023 Houston, Texas (Rice University) - Session 1: June 30, 2023 - July 9, 2023 - Session 2: July 12, 2023 - July 21, 2023 San Diego, California (University of San Diego) - Session 1: June 30, 2023 - July 9, 2023 - Session 2: July 12, 2023 - July 21, 2023 Co-sponsored by: IEEE Educational Activities - TryEngineering Summer Institutes San Diego, California, United States, 92110

Nuclear Fusion has advanced significantly in the past 20 years from a university‐driven, academic, government‐funded field to a private, privately funded industry. Today there are more than 30 firms around the world with stated plans to build the world’s first power producing fusion power plant. These companies have raised over 6 billion dollars in private capital and in November 2021, private investment into fusion surpassed government funding into fusion for the first time in US history. Certainly, many of these firms will fail, due to the high risk, but if one firm succeeds it would offer the world a fundamentally new energy source. NLF Consulting was founded in 2018 to help investors understand the field of nuclear fusion. The firm assembles teams of fusion subject matter experts (mostly retired staff from academia, government laboratories and industry) to assess the quality of startup pitches on behalf of investors. NLF has worked with Honda, Westinghouse, the Naval Research Laboratory, and other organizations to navigate this space. In this talk, the founder of NLF will walk through the kinds of questions that investors ask when evaluating fusion as an investment opportunity and will lay out good resources (books, etc..) for outsider who are trying to get involved with this field. The talk will also discuss the broad industry trend of adding superconducting wire and magnet to existing fusion approaches and what that means for future fusion devices. Co-sponsored by: Joe Kalasky Speaker(s): Dr. Matt Moynihan Virtual: https://events.vtools.ieee.org/m/365280

You may use the following link to write a summary of any monthly updates from your committee, chapter or affinity group. Information received by 8 AM on WEDNESDAY the week of the event will be incorporated into the meeting agenda. https://docs.google.com/document/d/1DQ4v-STH_PWcWuo0x5NkYzDQsaOaEf5haloM13esVrs/edit?usp=sharing IEEE members can access prior meeting minutes hosted on the Pittsburgh Section's (https://drive.google.com/drive/folders/1_UTt5t_dxNP1M5dO87OOeR25t8P7qQHp?usp=sharing). Access to the shared drive is restricted to the (https://www.ieee.org/membership/products/google-apps.html). Location for this event is virtual. Meeting link and call-in information will be emailed one hour before the event. --------------------------------------------------------------- New to IEEE Pittsburgh? For those new to the Pittsburgh Section Executive and Administrative Meeting, we welcome all IEEE members in the area to attend! This is a standing meeting held on the 3rd Thursday of every month. We review our upcoming activities relevant to engineers in our section. Feel free to use the report link above to ask any questions you may have, join us on Slack, or read through our welcome guide for more information about how you can get involved with IEEE Pittsburgh. (https://ieeepittsburgh.slack.com/) (https://docs.google.com/document/d/1lyWneXlANAQAiJN2p6Bi9kAatooxIQ-YzlGpWRmRGBw/edit?usp=sharing) (https://webinabox.vtools.ieee.org/wibp_calendar/index/R20037) Agenda: First 30 minutes of the event are reserved for socializing. The meeting portion starts at 7 pm (eastern time zone). The meeting agenda will be emailed on Monday the week of the event for early registrants. Room: 102, Bldg: Benedum Hall, 3700 O'Hara Street, Pittsburgh, Pennsylvania, United States, 15213, Virtual: https://events.vtools.ieee.org/m/365908

This is a weekly session of the CIT Summer Series, with Nael Abu-Ghazaleh presenting Security challenges and opportunities at the Intersection of Architecture and ML/AI : Machine learning is an increasingly important computational workload as data-driven deep learning models are becoming increasingly important in a wide range of application spaces. Computer systems, from the architecture up, have been impacted by ML in two primary directions: (1) ML is an increasingly important computing workload, with new accelerators and systems targeted to support both training and inference at scale; and (2) ML supporting architecture decisions, with new machine learning based algorithms controlling systems to optimize their performance, reliability and robustness. In this talk, I will explore the intersection of security, ML and architecture, identifying both security challenges and opportunities. Machine learning systems are vulnerable to new attacks including adversarial attacks crafted to fool a classifier to the attacker’s advantage, membership inference attacks attempting to compromise the privacy of the training data, and model extraction attacks seeking to recover the hyperparameters of a (secret) model. Architecture can be a target of these attacks when supporting ML, but also provides an opportunity to develop defenses against them, which I will illustrate with three examples from our recent work. First, I show how ML based hardware malware detectors can be attacked with adversarial perturbations to the Malware and how we can develop detectors that resist these attacks. Second, I will also show an example of a microarchitectural side channel attacks that can be used to extract the secret parameters of a neural network and potential defenses against it. Finally, I will also discuss how architecture can be used to make ML more robust against adversarial and membership inference attacks using the idea of approximate computing. I will conclude with describing some other potential open problems. Speaker(s): Nael Abu-Ghazaleh, Virtual: https://events.vtools.ieee.org/m/364001