Stanford University
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Achintya K. Bhowmik, PhD
Adjunct Professor, OHNS/Otology & Neurotology Division
BioDr. Achin Bhowmik serves on the faculty of Stanford University as an adjunct professor at the Stanford School of Medicine, where he advises research and lectures in the areas of sensory augmentation, computational perception, cognitive neuroscience, and intelligent systems. He is also an affiliate faculty member of the Stanford Institute for Human-Centered Artificial Intelligence, Wu Tsai Neurosciences Institute and Human Performance Alliance, and a mentor for the Stanford Institutes of Medicine Summer Research Program.
Dr. Bhowmik is the chief technology officer and executive vice president of engineering at Starkey Hearing Technologies, a privately-held medical devices company with over 5,000 employees and operations in over 100 countries worldwide. In this role, he is responsible for the company’s technology strategy, research and development, engineering and program management departments, and leading the drive to transform hearing aids into multifunction wearable health and communication devices with advanced sensors and artificial intelligence.
Previously, Dr. Bhowmik was the vice president and general manager of the Perceptual Computing Group at Intel Corporation, where he was responsible for the R&D, engineering, operations, and businesses in the areas of 3D sensing and interactive computing, computer vision and artificial intelligence, autonomous robots and drones, and immersive virtual and merged reality devices.
Dr. Bhowmik is a member of the Forbes Technology Council, board of trustees for the National Captioning Institute, board of directors for Mojo Vision and OpenCV, board of advisors for the Fung Institute for Engineering Leadership at the University of California, Berkeley, and industry advisory board for the Institute for Engineering in Medicine and Biomedical Engineering at the University of Minnesota. He is also on the board of advisors for several technology startup companies.
He has also held adjunct and guest professor positions at the University of California, Berkeley, Liquid Crystal Institute of the Kent State University, Kyung Hee University, Seoul, and the Indian Institute of Technology, Gandhinagar. He received his Bachelor of Technology from the Indian Institute of Technology, Kanpur, PhD from Auburn University, and attended the Executive Program at Stanford University. He has authored over 200 publications, including two books and over 80 granted patents.
His awards and honors include Fellow of the Institute of Electrical and Electronics Engineers (IEEE), President and Fellow of the Society for Information Display (SID), Fellow of the Asia-Pacific Artificial Intelligence Association (AAIA), Artificial Intelligence Excellence award by the Business Intelligence Group, Gold Globee award for “Most Innovative Person of the Year in Healthcare”, Top 25 Healthcare Technology CTOs by the Healthcare Technology Report, Notable Leaders in Healthcare by Twin Cities Business, Healthcare Heroes award by the Business Journals, Industrial Distinguished Leader award from the Asia-Pacific Signal and Information Processing Association, TIME’s Best Inventions, and the Red Dot Design award.
Dr. Bhowmik and his work have been covered in numerous press articles, including TIME, Fortune, Wired, USA Today, US News & World Reports, Wall Street Journal, CBS News, BBC, Forbes, Bloomberg Businessweek, Scientific American, Popular Mechanics, MIT Technology Review, EE Times, The Verge, etc. -
Rohan Tan Bhowmik
Undergraduate, Electrical Engineering
BioI am an undergraduate student at Stanford University studying Computer Science and Electrical Engineering with an emphasis on artificial intelligence. I am constantly seeking to learn and develop new machine-learning techniques and build applications based on them, especially in the areas of health, environment, and human-computer interaction. I’m especially interested in brain-inspired computing for energy-efficient systems.
As a software engineering intern at AMD AI Group since June 2024, I’ve gained expertise in machine learning compilers and optimized model performance across diverse hardware architectures. I unified AI/ML model implementations for high-performance computing on CPUs, GPUs, and AI accelerators. I also developed masked and causal attention modules on Torch-MLIR and IREE, enabling models like LLaMa and Stable Diffusion on the AMD stack.
My other recent projects include the development of 1) a wildfire prediction method by analyzing trends in environmental, meteorological, and geological data with an aim to mitigate the impact of California’s devastating wildfire seasons, 2) a respiratory disease exacerbation prediction system based on a novel spatio-temporal artificial intelligence algorithm and local environmental sensor network, 3) a machine learning technique for automating patient facial condition assessment and surgery planning, 4) blood alcohol level estimation using infrared imaging and deep neural networks, and 5) a novel image recognition framework utilizing a quantum optical convolutional neural network.
I have published papers based on my research in peer-reviewed journals, including the Journal of Environmental Management, IEEE Access, Electronics, and Facial Plastic Surgery & Aesthetic Medicine. I have won top national awards in the USA Physics, Astronomy & Astrophysics, Junior Math, Computing, and Biology Olympiads and was named Regeneron STS Top 300 Finalist in 2023.
Outside of academics, I play clarinet, tennis, and volunteer with organizations to help sensory-deficient individuals, including the Baker Institute for Children with Hearing Loss, Starkey Hearing Foundation, and VocaliD.
