Booz Allen Hamilton Colloquium: Reza Ghanadan, Senior Manager, Google Cloud AI

Friday, November 13, 2020
3:30 p.m.-4:30 p.m.
Online
Kara Stamets
301 405 4471
stametsk@umd.edu

Talk Title: TBA

Reza Ghanadan
Senior Manager, Google Cloud AI

RSVPgo.umd.edu/ghanadan

Bio: Reza Ghanadan joined Google AI in 2017 and is leading the Cloud AI research and strategic technology programs. His current research focuses on investigating methods for creating safe, robust and reliable AI systems for real-world applications. Reza received his Ph.D. in Electrical Engineering from University of Maryland College Park. He also holds an Executive MBA from NYU, MS in Electrical Engineering, and two B.S. degrees in EE and in Physics (both Summa Cum Laude). Prior to joining Google, Reza held several executive and technical leadership positions centered on AI and Autonomy research at high-tech organizations in DARPA, Boeing, BAE Systems, and AT&T Bell Laboratories. At DARPA, he formed several cross disciplinary teams across academia, industry, and government, to tackle some of the most challenging problems in AI, ML, autonomy, as well as applications of these in science and engineering. He directed execution of 5+ complex and cross disciplinary AI/ML and data science initiatives in excess of $120M+ funding with teams of 200+ scientists and engineers, including Fundamental Limits of Learning (FUN LOL) program, Simplifying Complexity in Scientific Discovery (SIMPLEX), Mathematics of Sensing, Exploration and Exploitation; GRAPHS; Compressive Sensing; and Collaborating with Machines. Through these programs, his teams demonstrated several foundational applications of AI and ML in a number of complex domains including video intelligence, robotics, IoT, neuroscience, personalized medicine, knowledge extraction, finance, material science, 3D printing, human-machine interaction, social-cognitive systems, and anthropology. In 2015, one of his AI/autonomy research programs demonstrated a novel learning technique: “machines that learn tasks from watching YouTube videos”, which ranked in the Top 10 most popular DARPA programs based on nearly 20 million website visits. Prior to DARPA, Reza was a Boeing Technical Fellow, where he led a team of 50+ software and systems engineers to launch a large-scale distributed mobile autonomous network of mobiles, robots, UAV’s, and mobile sensors. He received the Boeing Technology Innovation Award. At BAE systems, Reza was an Engineering Fellow, the highest technical ranking at BAE, and Technical Director for the information processing department where he led research focused on adaptive algorithms and autonomous information networks. He received global BAE’s Gold Chairman’s Award for Innovation for inventing and launching a robust secure autonomous mobile networking protocol with real-time adaptation to traffic and the high dynamic variations in the network topology as was successfully demonstrated in F-15 fighter jets. Reza was a founding team member of Flarion Technologies, a startup later acquired by Qualcomm for $800M, and a member of the technical staff at AT&T Bell Laboratories, where he was a group leader for research centered on real-time adaptive autonomous systems, which he successfully applied to Navy submarines, high performance jet engines and wireless communication infrastructure. Reza has 18 patents awarded in the areas of AI, autonomy, and signal processing, and has 36 peer-reviewed publications. Most recently he was an invited speaker at the workshop on Explainable AI at the Pacific Symposium for Biocomputing (PSB 2018), invited keynote speaker at Gamesec in Nov. 2019, and speaker at the NSF’s 70th anniversary panel on industries of the future in Feb 2020. His research areas of interest are: robust and intelligent autonomous systems, AI/ML, data science, and applications of these in science, engineering, and a wide range of products. Most recently, he has been investigating methods for creating robust and reliable AI systems for real-world applications, understanding vulnerability in AI based systems, explainable AI technology, privacy-preserving learning and augmented learning.

Audience: Clark School  Graduate  Undergraduate  Faculty  Staff  Post-Docs  Alumni 

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