Amod Jai Ganesh Anandkumar

Eminent Speaker

Short CV: Dr. Amod Anandkumar is the Director of Research at Harman International, a Samsung group company. He leads a multinational research team working on efficient deep learning for advanced mobility and audio systems. Prior to this, he was the Director of Curriculum and Applications at Skill-Lync (a 2023 Top YCombinator ed-tech startup), driving the curriculum, content, and delivery in autonomous and electric vehicles, embedded systems, medical technology, telecom, and VLSI. Previously, he was an Application Engineering Manager at MathWorks where he led a diverse group of application engineers spanning multiple technical areas including AI, autonomous systems, signal processing, and wireless. Amod has also held research roles at Samsung R&D and GE Global Research, working on wireless communications and biomedical signal processing applications.

Amod holds a Ph.D. from Loughborough University, UK where he received the Graduate School Research Student Prize for outstanding academic performance and achievement. He holds a B.Tech degree in Electronics & Communications from National Institute of Technology Karnataka. He has published multiple peer-reviewed research papers and patents. He has served on Board of Studies and advisory committees at academic institutions in addition to being a reviewer for multiple national and international conferences and journals. Amod is a senior member of the IEEE and an ACM India Eminent Speaker.

Title of Talk 1: The Intelligent Edge - A Convergence of Hardware, Software, and Machine Learning

Synopsis: Edge devices are growing more powerful by the day and can be much more than just a pipe between sensors and the cloud. They can serve as independent decision making platforms capable of running analytics while keeping the data on device. On the other hand, deep learning models have grown larger, requiring more compute and data, making it unsuitable for resource-constrained edge devices without modifications. This talk will provide an introduction to techniques for developing and deploying efficient and performant deep learning models on the edge from the ML and systems perspectives. Specifically, we will look at edge-friendly neural network architectures, model compression techniques such as pruning, quantization, and knowledge distillation, and selecting and tuning inference runtimes.

Title of Talk 2: Smart Devices On Wheels: Autonomous Electric Software-Defined Vehicles

Synopsis: The automotive industry is undergoing a massive transformation with advances in autonomy, connectivity, and electrification. This comes with significant shifts in electrical/electronic architecture, middleware, and application software. Simultaneously, consumers expect their cars to be more like smartphones - offer regular updates, apps on demand, personalization, and a rich immersive multimedia experience. This talk will provide an overview of the evolution of the car as a hardware - software - services platform and highlight emerging trends in the automotive industry.

Title of Talk 3: A Neuroscientist, a physicist, and an ML engineer meet in an Uber pool: Insights into inter-disciplinary industry research

Synopsis: Abstract: Real-world problems are complex and span multiple disciplines. Solving such problems requires systems thinking and inter-disciplinary expertise. In this talk, we will take Driver Monitoring Systems as an example and illustrate the challenges arising from the variability of the automotive environment, limitations on sensing and compute, and complexities of biosignal interactions with mental and physiological states. We will look at how to formulate a system-level solution leveraging expertise involving neuroscience for understanding mental states, physics for designing sensors, and deep learning for extracting subtle signals from massive amounts of data.

Amod Jai Ganesh Anandkumar

Qualifications: PhD

Title: Director of Research

Affiliation: Harman International, Bangalore

LinkedIn: https://www.linkedin.com/in/ajga2

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About the speaker