Bio

Koul (coincidentally pronounced 'Cool') brings over 16 years of production-oriented Applied Research/Data Science experience on PetaByte scale datasets, with features shipped to about a billion people. More famously, he's known as the founder of Seeing AI - the most used assistive technology by the blind community, after the iPhone. He has been pushing ideas to reality using computer vision and deep learning techniques for Augmented Reality, Robotics, Speech, Productivity as well as building tools for communities with visual, hearing and mobility impairments. A regular at hackathons, he has won close to four dozen awards, including top-3 finishes for four years consecutively in the planet's largest private hackathon with 18,000 participants. Some of his recent work, which IEEE has called ‘life-changing’, has been honored by CES, FCC, Cannes Lions, TIME magazine, SXSW, American Council of the Blind, showcased at events by UN, White House, House of Lords, World Economic Forum, on Netflix, National Geographic, and applauded by world leaders including Justin Trudeau and Theresa May. NASA FDL AI Mentor, CES Innovation Award Judge, Edison Awards Judge Selected talks: * TEDxSeattle'18 (https://youtu.be/ttyXf_9ptBs) * UN, NASA SETI Institute, Google Talk, NeurIPS'18 (NIPS), CVPR'20 * Keynote speaker: SMX Munich'14 (Germany), ACB'18, Global Data Science Conference'17 * O’Reilly Artificial Intelligence Conference (NY'16, SF '17, SF'18, SF'19) * Host of Re:Work Deep Learning Summit ('19, '20) Recently announced: * Seeing AI app: https://youtu.be/R2mC-NUAmMk * Dictate - Hands-free typing in Microsoft Office: http://dictate.ms * Netflix's Bill Nye Saves The World, @22 minutes: https://www.netflix.com/watch/80117907 * Recipient of IET Career Achievement Medal In his free time, Koul enjoys writing about himself in third person. Contact him at akoulcs-careers at yahoo dot com Specialties: Artificial Intelligence, Deep Learning, Computer Vision, Big Data Analysis, Machine Learning on Large Datasets, Natural Language Processing (NLP), Information Retrieval, Search Engines, Predictive Analytics, Scalability