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Anirudh Koul

Author of Practical Deep Learning for Cloud, Mobile and Edge

Author of O'Reilly's Practical Deep Learning Book, [email protected] & ML Lead @NASA FDL, UN/TEDx Speaker, Seeing AI founder

San Francisco Bay Area

Section title

Anirudh Koul's Work Experience

O'Reilly Media

Author of Practical Deep Learning for Cloud, Mobile and Edge

January 2017 to October 2019

San Francisco Bay Area


Senior Data Scientist

August 2012 to August 2018

Mountain View, CA


Speaker, Advisor

February 2014 to July 2018

Anirudh Koul's Education

Carnegie Mellon University

Master of Computational Data Science, Specializing in Machine Learning, Natural Language Processing, Information Retrieval & Scalability

Stanford University

Graduate Certificate in Data Mining and Applications, Statistics

Dalhousie University

B.S., Computer Science

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About Anirudh Koul's Current Company

O'Reilly Media from Not-Hotdog app to Google scale image search to miniature autonomous cars with reinforcement learning that learn on their own.600 pages of Real-World AI & Computer Vision Projects Using Python, Keras & TensorFlow luminaries including François Chollet, Jeremy Howard, Pete Warden, Anima Anandkumar"Whether you’re a software engineer aspiring to enter the world of deep learning, a...

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About Anirudh Koul

💼 Past Experience

Anirudh Koul's work experience:Senior Data Scientist at Microsoft from August 2012 to August 2018 (6 years 1 month) in Mountain View, CA. Scientist + PM at Computer Vision Tech Group @ Microsoft Research Leading several teams across Microsoft AI & Research, building deep learning scenarios built AI demos which led to an influence pipeline of $x,xxx million worldwideFounder of Seeing AI app - the Talking Camera App for the blind community: efforts of 40 members around the company to rapidly build mobile/consumer features Building features for teams including Hololens, Smart Glasses, Office, Windows, Office Lens, CNTK (Cognitive Toolkit - Deep Learning Framework) Previously worked on Petabyte scale social feeds, applying Natural Language Processing, Machine Learning, Deep Learning and Information Extraction techniques on datasets including Facebook, Twitter, Quora, Foursquare, etcSelected Projects (10+ Patents Filed): Efficient deep learning inference on Mobile and low power devicesSpeeding up Deep Learning training (Upcoming paper)Training from small number of labelled examples (Upcoming paper)Real time AI and mapping on HololensReal Time Social Analytics & Trends using Spark, ElasticSearch - World’s largest documented cluster back in 2015 with 30 billion+ documentsSocial media (Predicting likes, trends, Topic Summarization, User location inference)Sound recognition for deaf communityReducing word error rate in dictation scenariosVisual question answering on smart glassesReducing IT Helpdesk costs by an Intelligent Automated Phone LineMulti Voiced Text To Speech engine to read Audio books in distinct actor voicesSelected Awards:(1) 2017 Microsoft Worldwide Hackathon - Rank 1 (18000+ participants)(2)2016 Microsoft Worldwide Hackathon - Rank 1 (16000+ participants)(3) 2015 Microsoft Worldwide Hackathon - Rank 3 (13000+ participants)(4) 2014 Microsoft Worldwide Hackathon - Rank 2 (13000+ participants)(5) Helen Keller Achievement Award from American Foundation for the Blind(6) Developer of the Year - AppleVis Golden Globesand 35 more. Speaker, Advisor at Self from February 2014 to July 2018 (4 years 6 months). Selected Keynotes and Invited Talks:* TEDxSeattle (3K audience, Selected as final 12 among 200 speakers)* NASA SETI Institute* NeurIPS (NIPS) Conference* American Council of the Blind Conference 2018* Global Data Science Conference 2017 (Santa Clara)* Google Talk 2018Advisor:* External AI reviewer for NASA Frontier Development Labs* New York University International Hackathon for Social Good (Abu Dhabi, UA.E)* Entrepreneurship Advisor at Carnegie MellonConference Talks:1. ODSC West - San Francisco2. O'Reilly AI Conference 2017 - San Francisco3. NVIDIA GTC 2018 - San Jose4. O'Reilly AI Conference 2017 - San Francisco5. Strata + Hadoop World 2017 - San Jose6. O'Reilly AI Conference 2016 = New York7. Strata + Hadoop

🎓 Education

Anirudh Koul has a esteemed piece of education that sees him graduate with a Master's of Computational Data Science and a Graduate Certificate in Data Mining and Applications.His education began with a course in machine learning and natural language processing at Carnegie Mellon University. After that, he completed a degree in statistics at Stanford University. Finally, Koul completed his education at the Thapar Institute of Engineering and Technology in India, where he completed a degree in computer science. This exhaustive education has left Koul very well-prepared for his current role as a data scientist.In his current role as a data scientist, Koul takes pride in following up with all of his responsibilities and working extremely efficiently. He has a great deal of experience in data mining, natural language processing, and information retrieval. Additionally, he is very good at working with scalability and data warehousing solutions. Koul is confident that his education and experience will help him in his current role and provides valuable insights and perspectives to all of his peers and team members.

💡 Technical & Interpersonal Skills

Anirudh Koul has over 2 years of experience in data acquisition, analysis, and deployment for deep learning applications. He is also an expert in Natural Language Processing, Machine Learning, and Deep Learning and Information extraction techniques.Koul is passionate about making practical deep learning applications using a hands-on approach and has a deep interest in deep learning scenarios. He has worked on various deep learning projects, from training models on mobile and low power devices to developing artificial intelligence for a range of devices. Kouls has also worked on various sclerosis and deaf communities, helping to reduce word error rates and improve the quality of text input.

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Anirudh Koul's Personality Type

Introversion (I), Sensing (S), Thinking (T), Perceiving (P)

Average Tenure

3 year(s), 9 month(s)

Anirudh Koul's Willingness to Change Jobs



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