ACM TechTalks
ACM members and non-members alike are welcome to attend our popular series of free TechTalks by expert industry professionals, distinguished ACM award laureates, and visionary researchers from industry and academia. Focused on keeping our global audience of busy practitioners at the forefront of technical trends, professional development, and emerging technologies, the TechTalks are also popular with students and educators. Recent talks have covered topics in Artificial Intelligence and Machine Learning, Big Data and Data Science, Blockchain, Computer Vision, Deep Learning, JavaScript, Microservices, Python, Quantum Computing, and more. Registration is free and the TechTalks can be attended both live and on-demand, on desktop and mobile devices. Check this page frequently for upcoming events as well as our on-demand archive. To subscribe to our TechTalk announcements, email [email protected].
View Our Recent TechTalk
Developing Vascular Digital Twins to Shift from Reactive to Proactive Care
The emergence of digital twin technology is transforming healthcare by shifting the paradigm from reactive to proactive care. These sophisticated, personalized virtual models of human physiology are especially impactful in simulating vascular systems, enabling the noninvasive diagnosis and treatment of conditions like stenosis. However, practical deployment in clinical settings faces significant challenges, such as managing vast datasets, computational complexity, and the need for real-time processing. This talk will focus on how high-performance computing addresses these obstacles through the development of the Longitudinal Hemodynamic Mapping Framework (LHMF). Unlike current models limited to single-heartbeat simulations, LHMF enables continuous, long-term hemodynamic analysis, simulating over 4.5 million heartbeats with negligible error. I will present its deployment on both traditional and cloud-based platforms, demonstrating its scalability and clinical relevance.
Furthermore, the integration of continuous physiological data from wearable technologies with digital twin models offers new possibilities for monitoring disease progression over time. This synergy, combined with advances in virtual reality, enhances clinician interaction with complex models, facilitating early disease detection and personalized treatment planning. By leveraging advanced computational methods and digital health innovations, digital twins have the potential to revolutionize healthcare, driving a proactive approach that improves patient outcomes.
ACM Learning Center TechTalk Archive
ACM award winners, leading researchers, industry veterans, thought leaders, and innovators address today and tomorrow's hottest topics and issues in computing for busy practitioners, as well as educators, students, and researchers. Check out our archive of these ACM TechTalks, free for members and non-members alike.
TechTalks on Artificial Intelligence & Machine Learning
Talks from some of the leading visionaries and bleeding-edge researchers in AI/ML: Fei-Fei Li on visual intelligence in computers and ImageNet; Eric Horvitz on AI solutions in the open world; and Tom Mitchell on using ML to study how the brain creates and represents language.
Scott Tilley TechTalk
Register now for the next free ACM TechTalk, "Testing the System: A Holistic Approach to Security in Systems Development," presented on Thursday, January 23 at 12:00 PM ET/17:00 UTC by Scott Tilley, an Emeritus Professor at the Florida Institute of Technology. Will Tracz, former Chair of ACM SIGSOFT and member of the ACM Professional Development Committee, will moderate the questions and answers session following the talk. Continue the discussion on ACM's Discourse Page.
Rush Shahani TechTalk
View for the recent ACM TechTalk, "Research to Reality: Building Production-Ready LLM Apps Users Can Trust," presented by Rush Shahani, CTO and Co-Founder of Persana AI. Oana Olteanu, ML Engineer at SignalFire, moderated the questions and answers session following the talk. Continue the discussion on ACM's Discourse Page.