Week of Events
Thriving in an AI & Emerging Tech World: Opportunities and Challenges for Women Engineers
Thriving in an AI & Emerging Tech World: Opportunities and Challenges for Women Engineers
In celebration of IEEE Women in Engineering (WIE) Day, the IEEE WIE Affinity Groups from Oregon, Hawaii, Utah, Spokane, Santa Clara Valley, San Diego, Richland, Phoenix, and Foothill of IEEE Region 6 and IEEE WIE AG SB DU of IEEE R10 proudly invite you to an empowering and timely panel discussion: “Thriving in an AI & Emerging Tech World: Opportunities and Challenges for Women Engineers” Join us for an inspiring conversation exploring how AI, automation, and digital transformation are reshaping the engineering landscape and redefining the future of work. This dynamic event will bring together globally recognized engineers, researchers, and industry leaders who will share: - The evolving role of engineers in an AI-driven world - Opportunities and challenges uniquely faced by women in emerging technologies - Strategies for upskilling, career advancement, and impactful leadership in a fast-paced tech environment Speaker(s): Prof. Saifur Rahman, Dr. Winnie Ye , Celia Shahnaz, John D. McDonald, P.E, Jill Gostin, David Koehler Virtual: https://events.vtools.ieee.org/m/486034
Generic LLMs in Cybersecurity
Generic LLMs in Cybersecurity
Generic Large Language Models (GLLMs) are continually being released with increased size and capabilities, enhancing the capabilities of these tools as universal problem solvers. While the reliability of GLLMs' responses is questionable in many situations, these models are often augmented or retrofitted with external resources for various applications, including cybersecurity. The talk will discuss major security concerns of these pre-trained models: first, GLLMs are prone to adversarial manipulation, such as model poisoning, reverse engineering, and side-channel cyberattacks. Second, the security issues related to LLM-generated codes using open-source libraries/codelets for software development can involve software supply chain attacks. These may result in information disclosure, access to restricted resources, privilege escalation, and complete system takeover. This talk will also cover the benefits and risks of using GLLMs in cybersecurity, particularly in malware detection, log analysis, intrusion detection, etc. I will highlight the need for diverse AI approaches (non-LLM-based smaller models) trained with application-specific curated data, fine-tuned for well-tested security functionalities in identifying and mitigating emerging cyber threats, including zero-day attacks. Note: - You will require a Zoom account (free to obtain) to join the meeting. This requirement is to avoid Zoom bombing. Please sign in using the email address tied to your Zoom account, not necessarily the one you used to register for the event. Register here: https://sjsu.zoom.us/meeting/register/2XuaGc9ISoCWOu1dt6ANog - By registering for this event, you agree that IEEE and the organizers are not liable to you for any loss, damage, injury, or any incidental, indirect, special, consequential, or economic loss or damage (including loss of opportunity, exemplary or punitive damages). The event will be recorded and will be made available for public viewing. Co-sponsored by: Vishnu S. Pendyala, SJSU Speaker(s): Dr. Vishnu S. Pendyala, Prof. Dipankar Dasgupta, IEEE Fellow, NAI Fellow, AIIA Fellow Virtual: https://events.vtools.ieee.org/m/489327
IEEE Hawaii General Meeting
IEEE Hawaii General Meeting
Learn about IEEE and the Chapters and Affinity Groups we have here in Hawaii! Network with other engineers, IEEE members, and students. [] Aloha Tower Marketplace Map found here: https://alohatower.com/events/images/1st-floor-map.pdf Agenda: 5:30pm - Networking 6:15pm - Hawaii Section Chapter and Affinity Group presentations 7:15pm - Closing remarks 7:30pm - Wrap up Room: Multipurpose Room 2, Bldg: Aloha Tower Marketplace, 1 Aloha Tower Dr, Honolulu, Hawaii, United States, 96813
A System of Systems for Cognitive Decision-Making
A System of Systems for Cognitive Decision-Making
A System of Systems for Cognitive Decision-Making Decision-making is a task that an average person does about 300 to 400 times a day. Most decisions are minor but there are some that are of great importance, that the decision can have great impact. The Butterfly Effect states that a small action in one part of the world can cause a great effect in another part of the world at some later time. The Gartner Group estimates that by 2028 33% of enterprise applications will include agentic AI, and that this will enable 15% of daily work decisions to be made autonomously, without human intervention. . This can be fueled by a combination of shortage of capable humans, an increase in the cost of human involvement, and greater AI accuracy and performance. It should be started on a narrow realm of application, and with knowledge, experience, and success, the realm could be expanded. Human cognitive function is an important part of this paper, except that we try to create it in the machine environment. Some example situations are included to help demonstrate the problem. This paper explains some of the types of decision-making and how they are performed. The paper then continues with how this process, modeled after an intelligent human would perform the task. This discussion combines computer science, decision sciences, psychology, and mathematics to describe this project. Speaker(s): , Dr. Morantz Virtual: https://events.vtools.ieee.org/m/488111
R6 YP Game Night
R6 YP Game Night
skribbl.io game night in the R6 YP discord [] Virtual: https://events.vtools.ieee.org/m/483414