Secure and Trustworthy Machine Learning and AI for Multi-Domain Applications

Abstract

Machine Learning (ML) algorithms and Artificial Intelligence (AI) systems have already had an immense impact on our society and have been shown to be able to create machine cognition comparable to or even better than human cognition for some applications. Machine learning algorithms are now regarded as very useful for data-driven applications including cybersecurity solutions for different emerging applications. However, because ML algorithms and AI systems can be controlled, dodged, biased, and misled through flawed learning models and input data, they need robust security features and trust. It is very important to design, evaluate and test ML algorithms and AI systems that produce reliable, robust, trustworthy, explainable, and fair/ unbiased outcomes to make them acceptable by diverse users for different applications.

This talk will focus on both AI for cybersecurity and cybersecurity for AI for multi-domain operations and applications.

This talk will also cover emerging applications and use cases of secure and trustworthy AI/ML and their success and pitfalls.

Agenda:

5:00 - 5:15 pm PST : Networking

5:15 - 5:30 pm PST : Intro, Housekeeping and Chapter Activities

5:30 - 5:40 pm PST : ACM Sacramento Chapter Summer 2026 Preceptorship Program

5:40 - 6:40 pm PST : Talk by Dr Danda Rawat on Secure and Trustworthy Machine Learning and AI for Multi-Domain Applications

6:40 - 6:55 pm PST : Q & A

6:55 - 7:00 pm PST : Closing Comments and Open Discussions

Note: This will be a virtual event - zoom meeting link will be provided upon registration

ACM Sacramento Chapter Officers

Chairperson - Dr. Harsh Verma
Vice-Chairperson – Dr. Abida Mukarram
Treasurer - Michael Brady
Co-Chair, Semantic Web and Webmaster - Savita Farooqui

ACM FCUSD Student Chapter

Chapter Patron: Ms Shanan Spears
Student Chapter Founding President: Atulya Kaduri