Chapter Open House and talk on Securing Agentic AI
Join us for an essential perspective on the future of AI systems and get insights into the state of the Chapter.
As organizations accelerate the adoption of generative and agentic AI, two pressing challenges have emerged:
1️⃣ Identifying emerging threats
2️⃣ Securing autonomous systems
This event features a leading industry expert addressing these critical issues, followed by updates on the state of our chapter from the IEEE CIS SCV Chair.
🎤 Talk 1
Securing Agentic AI: From Security Risks to Practical Defenses for Autonomous Systems
Speaker: Dewank Pant, Engineer and Researcher
🎤 Talk 2
State of the Chapter
Speaker: Dr. Vishnu S. Pendyala, Chair, IEEE CIS Santa Clara Valley Chapter
Date and Time
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- Dr. Martin Luther King, Jr. Library (SJSU)
- 150 E San Fernando St San Jose, California 95112
- San Jose, California
- United States
- Room Number: MLK Room 225
- Click here for Map
- Contact Event Hosts
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Sravan Kanukolanu
Event Organizer
IEEE CIS – Santa Clara Valley Chapter
Email: kanukolanu.ds@gmail.com - Co-sponsored by Vishnu S. Pendyala, San Jose State University
Speakers
Dewank
Securing Agentic AI: From Security Risks to Practical Defenses for Autonomous Systems
Agentic AI systems combine autonomy with real-world tool use, offering transformative potential but also introducing novel risks. This talk will introduce agentic AI and outline key vulnerabilities, including jailbreaks, tool hijacking, model misuse, and indirect exploitation through prompt injection. It will then focus on security risks associated with the Model Context Protocol (MCP) and conclude with mitigation strategies and practical defenses to enhance the safety of autonomous AI systems in real-world deployments.
Biography:
Dr. Vishnu S Pendyala of San Jose State University
State of the Chapter
Biography:
Vishnu S. Pendyala, PhD, is a faculty member in Applied Data Science and a University Senator with San Jose State University, current chair of the Santa Clara Valley Chapters of IEEE Computer and Computational Intelligence Societies, Area 4 Coordinator for Region 6, and a Distinguished Contributor of the IEEE Computer Society. He also taught at Kyungpook National University (ranked #698 in Best Global Universities), South Korea, as a visiting scholar. As a past ACM Distinguished Speaker, researcher, and industry expert, he gave nearly 100 talks and tutorial sessions in various forums such as faculty development programs, the 12th IEEE GHTC, IEEE ANTS, 12th IACC, 10th ICMC, IUCEE, 12thACM IKDD CODS and 30th COMAD to audiences at venues such as Stanford University, Google, University of Wisconsin (Madison), University of Hawaii, Computer History Museum, Universidad de Ingeniería y Tecnología, Lima, Peru, IIIT Hyderabad, KREA, IIT Jodhpur, University of Hyderabad, IIT Indore, IIIT Bhubaneswar. Some of these talks are available on YouTube and IEEE.tv.
Dr. Pendyala is a senior member of the IEEE and ACM. He has over two decades of experience in the software industry in Silicon Valley, USA. His book, “Veracity of Big Data,” is available in several libraries, including those of MIT, Stanford, CMU, the US Congress, and internationally. Two other books on machine learning and software development that he edited are also well-received and have been included in the US Library of Congress and other reputed libraries. Dr. Pendyala taught a one-week course sponsored by the Ministry of Human Resource Development (MHRD), Government of India, under the GIAN program in 2017 to Computer Science faculty from all over the country and delivered the keynote in a similar program sponsored by AICTE, Government of India, in 2022. Dr. Pendyala served on the US government's National Science Foundation (NSF) proposal review panel in 2023. He received the Ramanujan Memorial Gold Medal and a shield for his college at the State Math Olympiad. He also played an active role in the Computer Society of India and was the Program Secretary for its annual national convention.
Address:One Washington Sq, San Jose State University, San Jose, United States, 95192-0250
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 may be recorded and will be made available for public viewing.