Where I express personal thoughts in words
Gleb Mezhanskiy is the CEO & Co-founder of Datafold - a data observability platform that helps companies unlock growth through more effective and reliable use of their analytical data. As a founding member of Data teams at Autodesk and Lyft and the Head of Product at Phantom Auto, Gleb has built some of the world's largest and most sophisticated data platforms and has developed tooling to improve productivity and data quality in organizations with hundreds of data users.
Saishruthi Swaminathan is an Advisory Data Scientist at IBM's AI Strategy and Innovation division. Previously, she was a technical lead and data scientist in the IBM Center for Open-Source Data and AI Technologies team, whose main focus is to democratize data and AI through open source technologies. She has a Master’s in Electrical Engineering that specializes in Data Science and a Bachelor's degree in Electronics and Instrumentation. Her passion is to dive deep into the ocean of data, extract insights, and use AI for social good.
Previously, she worked as a Software Developer on a mission to spread the knowledge and experience she acquired in her learning process. She also leads an initiative to bring education to rural children and organizes meetups that focus on women's empowerment.
Mohamed Elgendy is a seasoned AI expert, who has previously built and managed AI organizations at Amazon, Rakuten, Twilio, and Synapse. In particular, he founded and managed Amazon's computer vision think tank. He is the author of the "Deep Learning for Vision Systems" book published by Manning in November 2020. Mohamed regularly speaks at many AI conferences like Amazon's DevCon, O'Reilly's AI, and Google's I/O.
Dr. Jennifer Prendki is the founder and CEO of Alectio, the first startup fully focused on DataPrepOps. She and her team are on a fundamental mission to help ML teams build models with less data. Before Alectio, Jennifer was the Vice President of ML at Figure Eight. She also built an entire ML function from scratch at Atlassian and led multiple Data Science projects on the Search team at Walmart Labs. She is recognized as one of the top industry experts on Active Learning and ML lifecycle management. She is an accomplished speaker who enjoys addressing both technical and non-technical audiences.
Sarah Catanzaro is a Partner at Amplify Partners, where she focuses on investing in and advising high potential startups in machine intelligence, data management, and distributed systems. Her investments at Amplify include startups like RunwayML, Maze Design, OctoML, and Metaphor Data, among others. Sarah also has several years of experience defining data strategy and leading data science teams at startups and in the defense/intelligence sector, including roles at Mattermark, Palantir, Cyveillance, and the Center for Advanced Defense Studies.
Aparna Dhinakaran is the Chief Product Officer at Arize AI, a startup focused on ML Observability. She was previously an ML engineer at Uber, Apple, and TubeMogul (acquired by Adobe). During her time at Uber, she built several core ML Infrastructure platforms, including Michelangelo. She has a bachelor’s from Berkeley's Electrical Engineering and Computer Science program, where she published research with Berkeley's AI Research group. She is on a leave of absence from the Computer Vision Ph.D. program at Cornell University.
Emeli Dral is a Co-founder and CTO at Evidently AI, a startup developing tools to analyze and monitor the performance of machine learning models. Earlier, she co-founded an industrial AI startup and served as the Chief Data Scientist at Yandex Data Factory. She led over 50 applied ML projects for various industries - from banking to manufacturing. Emeli is also a data science lecturer at St. Petersburg State Management School and Harbour.Space University. She is a co-author of the Machine Learning and Data Analysis curriculum at Coursera with over 100,000 students. She also co-founded Data Mining in Action, the largest open data science course in Russia.
David Sweet was a quantitative trader at GETCO, where he used experimental methods to tune trading strategies, and a machine learning engineer at Instagram, where he experimented on a large-scale recommender system. He is currently writing a book called "Tuning Up," an extension of lectures given at NYU Stern on tuning high-frequency trading systems. Before working in the industry, he received a Ph.D. in Physics and published research in Physical Review Letters and Nature. The latter publication – an experiment demonstrating chaos in geometrical optics -- has become a source of inspiration for computer graphics artists, undergraduate Physics instructors, and an exhibit called TetraSphere at the Museum of Mathematics in New York City.
Fabiana Clemente is a Data Scientist with a background that ranges from Business Intelligence to Big Data Development and IoT architecture. Throughout her professional career, she has been leading state-of-the-art projects in global companies and startups. She has an academic background in Applied Maths, and MSc in Data Management combined with nano degrees in Deep Learning and Secure and Private AI.
As YData’s Co-Founder, she combines Data Privacy with Deep Learning as her main field of work and research, with the mission to unlock data with privacy by design. She also aims to inspire more women to follow her steps and join the tech community.
