The Human-in-the-Loop track at Data Day Texas 2020 will feature international leaders in Human-in-the-Loop Machine Learning, presenting in the industry's first dedicated track.
Human-in-the-Loop Machine Learning tackles one of the most problems in technology today: how do people and machines interact to solve problems together? Probably 90% of Machine Learning applications today are powered by Supervised Machine Learning. This covers a wide range of use cases: an autonomous vehicle can drive you safely down the street because humans have spent thousands of hours telling it when its sensors are seeing a ‘pedestrian’, ‘moving vehicle’, ‘lane marking’, and every other relevant object; your in-home device knows what to do when you say ‘turn up the volume’, because humans have spent thousands of hours telling it how to interpret different commands; and your Machine Translation service can translate between languages because it has been trained on thousands (or maybe millions) of human-translated texts.
Dr. Robert Munro, author of the upcoming Manning publication Human in the Loop Machine Learning, will keynote the track.
Confirmed Human in the Loop sessions include:
Information Extraction with Humans in the Loop: Dr. Anna Lisa Gentile - IBM Research Almaden
Human Centered Machine Learning: Robert Munro - Author / Serial Founder
Cost-Optimized Data Labeling Strategy: Jennifer Prendki - Alectio
Humans, machines and disagreement: Lessons from production at Stitch Fix: Brad Klingenberg - Stitch Fix
Learning sequential tasks from human feedback : Brad Knox - Bosch USA
How to trust your Human-In-The-Loop (HITL) data annotations: Emanuel Ott - iMerit
From Stanford to Startup: making academic human-in-the-loop technology work in the real world : Abraham Starosta / Tanner Gilligan
Human in the Loop Speakers:
Anna Lisa Gentile (San Jose ) @anligentile
Dr. Anna Lisa Gentile (LinkedIn) is a Researcher at IBM Research Almaden. Her research is principally focused on studying methods and techniques for semantic annotating unstructured and semi-structured content. Her main Research Areas are Information Extraction (IE), Natural Language Processing (NLP) and Semantic Web. She obtained her PhD with a thesis on Named Entity Disambiguation at the University of Bari, Italy in 2010. She has published more than 60 peer-reviewed scientific publications including papers at major venues such as LREC, EMNLP, ESWC and ISWC. She has been serving as Organizing Committee member for conferences such as ISWC, ESWC, WWW amongst many others and organized workshop series such as LD4IE on Linked Data for Information Extraction and HumBL on Augmenting Intelligence with Bias-Aware Humans- in-the-Loop.
Dr. Gentile will present the following Human in the Loop session: Information Extraction with Humans in the Loop.
Tanner Gilligan (SF Bay)
Tanner Gilligan has a passion for both AI and software architecture, and combines these skills in order to lead the platform development at Sculpt. Originally, Tanner grew up in Minnesota where he worked full time during high-school, and moved to California for college and better weather. He completed his B.S. and M.S. in Computer Science (AI) at Stanford University in only four years, and graduated with distinction for being at the top of his class. Prior to Sculpt, he gained hands-on AI experience at TrueCar, Oracle, and several clients while working as a ML consultant.
Tanner will co-present the following Human in the Loop session: From Stanford to Startup: making academic human-in-the-loop technology work in the real world.
Brad Klingenberg (San Francisco)
Brad Klingenberg is the Chief Algorithms Officer at Stitch Fix, an online personal styling service that helps people find the clothes they love through personalized shipments of apparel, shoes and accessories. Brad and his team uses statistics, machine learning and human-in-the loop algorithms to optimize the Stitch Fix client experience, the management of inventory and the selection of items for clients. Prior to joining Stitch Fix, Brad received his PhD in Statistics from Stanford University and worked as a data scientist in technology and financial services.
Brad will present the featured Human in the Loop session: Humans, machines and disagreement: Lessons from production at Stitch Fix.
Brad Knox (Austin)
Brad Knox co-leads the Bosch Learning Agents Lab, which is housed at UT Austin and focuses on the development of machine learning algorithms for autonomous driving. Brad was an early pioneer of human-in-the-loop reinforcement learning, the topic of his PhD dissertation at UT. His postdoctoral research at the MIT Media Lab focused on creating interactive characters through machine learning on puppetry-style demonstrations of interaction. Before joining Bosch, Brad founded and sold his startup Bots Alive, working in the toy robotics sector. He has won multiple best paper awards, the 2012 best dissertation award for the UT Austin Department of Computer Science, and was named to IEEE Intelligent Systems' AI 10 to Watch in 2013.
Brad will present the following Human in the Loop session : Learning sequential tasks from human feedback.
Human in the Loop Keynote
Robert Munro (San Francisco ) @WWRob
Robert Munro (LinkedIn) is an expert in combining Human and Machine Intelligence, working with Machine Learning approaches to Text, Speech, Image and Video Processing. Robert has founded several AI companies, building some of the top teams in Artificial Intelligence. He has worked in many diverse environments, from Sierra Leone, Haiti and the Amazon, to London, Sydney and Silicon Valley, in organizations ranging from startups to the United Nations. In addition to publishing more than 50 papers, Robert is the author of the upcoming Manning publication Human in the Loop Machine Learning. He has a PhD from Stanford University.
Rob will present the following Human in the Loop keynote: Human Centered Machine Learning.
Emanuel Ott (Hannover, Germany)
Emanuel Ott leads iMerit’s solutions team. Over the past 6 years, he and iMerit’s US/India-based teams have been fueling the world’s leading augmented reality, natural language processing, and self-driving car companies with human annotated ground truth to power their efforts to “see and understand the world”. Emanuel's ceaseless curiosity for innovative technological solutions to human problems has led him to redefine client annotation requirements, improve their data pipelines, and empower them to leverage and hone the power of HITL workflows involving iMerit's workforce of nearly 3,000 in-house employees.
Emanuel will present the following Human in the Loop session: How to trust your Human-In-The-Loop (HITL) data annotations.
Jennifer Prendki (San Francisco) @jlprendki
Jennifer Prendki is the founder and CEO of Alectio and has spent a large part of her career promoting the importance of creating a better approach to Machine Learning Lifecycle Management. Her current focus is on helping ML teams build better models with less data. Prior to founding Alectio, she was the VP of Machine Learning at Figure Eight, one of the industry leader in data labeling (recently acquired by Appen); she also headed Machine Learning at Atlassian and various Data Science initiatives on the Search team at Walmart Labs. She is also known for her active support of women in STEM and Technology.
Jennifer will present the following Human in the Loop session: Cost-Optimized Data Labeling Strategy.
Abraham Starosta (SF Bay)
Abraham Starosta is passionate about democratizing AI. Prior to Sculpt, He enjoyed researching NLP, multitask learning and weak supervision at Stanford. He has built text intelligence products for financial institutions at Primer AI, and co-founded the technical recruiting agency for startups Human Capital. He finished his B.S and M.S in Computer Science from Stanford specializing in AI and NLP.
Abraham will co-present the following Human in the Loop session: From Stanford to Startup: making academic human-in-the-loop technology work in the real world.
For a list of all Data Day Texas / AI Summit speakers, visit our Speakers page.
