Who will speak at Data Day Texas + AI

We're just now beginning to announce speakers for the 2024 edition of Data Day Texas + AI. We'll be adding new speakers each week.

Susan Shu Chang (Toronto) @susan_shuc

Susan Shu Chang (Linkedin) is currently Principal Data Scientist at Elastic. Originally trained in Economics, Susan is a 5x PyCon speaker, founder of Indie game studio Quill Game Studios and organizer of the 3700+ member Toronto Women's Data Group. Susan is also author of the upcoming O'Reilly book: Machine Learning Interviews. To learn how she finds time for all this and more, check out her personal site, susanshu.com, for her writings on focus optimization and daily routines.

Mikiko Bazeley (San Francisco) @BazeleyMikiko

Mikiko Bazeley (Linkedin / YouTube / Substack / GitHub) is currently head of MLOps at Featureform, a Virtual Feature Store. She's worked as an engineer, data scientist, and data analyst for companies like Mailchimp (Intuit), Teladoc, Sunrun, Autodesk as well as a handful of early stage startups. Mikiko leverages her knowledge and experiences as a practitioner, mentor, and strategist to contribute MLOps & production ML content through LinkedIn, Youtube, & Substack, as well as partnering with companies in the ML ecosystem like Nvidia. Her main goals are to help: data scientists deploy better models faster; ML platform engineers develop robust & scalable ML systems & stacks without breaking the bank; & bring the delight back into building ML products.

Jessica Talisman (Santa Cruz)

Jessica Talisman is a taxonomist, ontologist, information architect, and professional data wrangler. Over her 25 years of experience in the taxonomy world, Jessica has worked in galleries, libraries, museums, the federal government, e-commerce, and currently is Senior Manager, Taxonomy at System1. Jessica received her Master of Library and Information Science at Emporia State University. Check out Jessica’s recent interviews on the Monday Morning Data Chat and Discovering Data.

Veronika Durgin (Boston)

Veronika Durgin is Vice President of Data at Saks, the premier luxury ecommerce platform. In her role she is responsible for the data strategy at Saks from driving enterprise digital transformation and governing enterprise data, to enabling data efficiency and supporting analytics and reporting of the full customer shopping journey. Prior to joining Saks, she held various data engineering and management roles at tech-enabled sustainable agriculture company, Indigo, and Sonos, Inc. Veronika started her career as a database administrator focusing on performance tuning and optimization. Over the past two decades she has developed skills across database administration, data engineering, platform architecture, data modeling, and analytics and insights. Veronika is a Certified Data Vault Practitioner and a Snowflake Data Superhero. She is passionate about her profession and sharing knowledge with others. Veronika earned a master’s degree in computer software engineering from Brandeis University and a bachelor’s degree in biology from the University of Massachusetts, Boston. She lives in Massachusetts with her husband, 2 boys, and a Rhodesian Ridgeback.

Jesse Anderson (Lisbon) @jessetanderson

One of our perennially requested speakers, Jesse Anderson (Linkedin) is author of the oft-cited APress book Data Teams. As managing director of the Big Data Institute, Jesse works with companies ranging from startups to Fortune 100 companies. As an expert trainer known for his novel teaching practices, Jesse has taught over 30,000 people the skills to become successful data engineers. Jesse is published on O’Reilly and Pragmatic Programmers. He has been covered in prestigious publications such as The Wall Street Journal, CNN, BBC, NPR, Engadget, and Wired. Check out Jesse's new deep dive podcast: Unapologetically Technical, and learn more about Jesse at Jesse-Anderson.com.

Ryan Mitchell (Boston) @Kludgist

An expert in web scraping, web security, and data science, Ryan Mitchell is a frequently requested speaker at data and security conferences. She has also taught and designed courses at Northeastern University and Olin College of Engineering. Ryan holds a master’s degree in software engineering from Harvard University Extension School and is currently a senior software engineer at the Gerson Lehrman Group where she creates data science tools. Ryan is author of the O'Reilly book Web Scraping with Python, soon to be in its third edition, as well as multiple Linkedin courses including: Python Data Structures with Trees and Web Scraping with Python.

Holden Karau ( San Francisco) @holdenkarau

Holden Karau Wikipedia / Linkedin ) is a queer transgender Canadian, Apache Spark committer, Apache Software Foundation member, and an active open source contributor. As a software engineer, she’s worked on a variety of distributed computing, search, and classification problems at Apple, Google, IBM, Alpine, Databricks, Foursquare, and Amazon. She graduated from the University of Waterloo with a bachelor of mathematics in computer science. Outside of software, she enjoys playing with fire, welding, riding scooters, eating poutine, and dancing. Holden is the author of multiple O'Reilly publications, including Learning Spark, High Performance Spark, Kubeflow for Machine Learning, as well as the recent Scaling Spark with Ray and the upcoming Scaling Spark with Dask.

Hala Nelson (Alexandria, Virginia)

Hala Nelson (Linkedin) is an Associate Professor of Mathematics at James Madison University. She has a Ph.D. in Mathematics from the Courant Institute of Mathematical Sciences at New York University. Prior to her work at James Madison University, she was a postdoctoral Assistant Professor at the University of Michigan- Ann Arbor. Her research is in the areas of Materials Science, Statistical Mechanics, Inverse Problems, and the Mathematics of Machine Learning and Artificial Intelligence. Her favorite subjects are Optimization, Numerical Algorithms, Mathematics for AI, Mathematical Analysis, Numerical Linear Algebra and Probability Theory. She likes to translate complex ideas into simple and practical terms. To her, most mathematical concepts are painless and relatable, unless the person presenting them either does not understand them very well, or is trying to show off. Other facts: Hala Nelson grew up in Lebanon, during the time of its brutal civil war. She lost her hair at a very young age in a missile explosion. This event and many that followed shaped her interests in human behavior, the nature of intelligence, and AI. Her father taught her Math, at home and in French, until she graduated high school. Her favorite quote from her father about math is, "It is the one clean science''.
Hala is author of the recent O'Reilly book: Essential Math for AI.

Adi Polak (Israel) @AdiPolak

As Vice President of Developer Experience at Treeverse, Adi Polak shapes the future of data & ML technologies for hands-on builders. She also contributes to the lakeFS open-source, a git-like interface for object stores. In her work, she brings her vast industry research and engineering experience to bear in educating and helping teams design, architect, and build cost-effective data systems and machine learning pipelines that emphasize scalability, expertise, and business goals. Adi is a frequent worldwide presenter and the author of the recent O'Reilly book, Machine Learning With Apache Spark. She is continually an invited member of multiple program committees and advisor for conferences like Data & AI Summit, Scale by the Bay, and others. Previously, she was a senior manager for Azure at Microsoft, where she focused on building advanced analytics systems and modern architectures. When Adi isn’t building data pipelines or thinking up new software architecture, you can find her on the local cultural scene or at the beach.

Ole Olesen-Bagneux (Copenhagen)

Ole Olesen-Bagneux holds a PhD in Information Science from the University of Copenhagen, Denmark, where he has also lectured in courses for Knowledge Organization and Information Retrieval. He has worked within the field of Data Management and Governance as a leader, architect, and practitioner for over a decade in the life science sector. Ole is a frequent guest on leading data podcasts, including Monday Morning Data Chat, Discovering Data Podcast, and Catalog and Cocktails. Ole currently works as an Enterprise Architect in GN Store Nord, in Copenhagen, Denmark, and is author of the 2023 O'Reilly book: The Enterprise Data Catalog.

Santona Tuli (Washington DC)

Santona Tuli, PhD started working with data through fundamental physics—analyzing massive event data from particle collisions at CERN. Since then, she has worked as a machine learning engineer in the NLP sector, and on product engineering for the programmatic data workflow orchestration tool Airflow. Currently at Upsolver, she works on a framework for authoring data pipelines declaratively in SQL. Dr. Tuli is passionate about building and empowering others to build end-to-end data and machine learning pipelines scalably.She has also been featured in the 3D IMAX movie Secrets of the Universe, which showcases real scientists pushing the frontiers of knowledge. In her STEM outreach work, she emphasizes representation, equity, advocacy and empowerment.

Joe Reis (Salt Lake city)

Joe Reis (Linkedin), Co-Founder and CEO of Ternary Data, is a “recovering data scientist,” and a business-minded data nerd who’s worked in the data industry for 20 years. His responsibilities have ranged from statistical modeling, forecasting, machine learning, data engineering, data architecture, and everything else in between. Joe is co-host of the popular Monday Morning Data Chat (Spotify / Apple) as well as the newly launched Joe Reis Show (Apple / Spotify). Joe is also co-author of the bestselling O'Reilly book: Fundamentals of Data Engineering. Joe also teaches at the University of Utah as well as runs several meetups, including The Utah Data Engineering Meetup and SLC Python. When he’s not busy running a company, teaching, or creating content, Joe often finds himself DJing/making music, rock climbing, or trail running in the mountains around Salt Lake City, Utah.

Matthew Housley (Salt Lake city)

Co-Founder / CTO of Ternary Data as well as fellow “Recovering Data Scientist,” , Matthew Housley is also a “Reformed Academic,” holding a PhD in Math and dual Masters degrees in both Math and Physics. It was only natural that he began his career in Academia as a Professor of Mathematics, before joining one of the largest e-commerce companies as a data scientist. Matt's STEM background in combination with his knack for teaching makes him a mastermind at overhauling processes, improving teamwork, and incorporating engineering best practices so that real value is delivered to companies. While making the journey from data scientist to data engineer, Matt began to focus more on data & cloud engineering, working extensively with Amazon Web Services, Google Cloud Platform, Containers, Apache Airflow and GPUs, among other technologies. Matt (or should we say, “Dr. Housley”) is an adjunct faculty member in the David Eccles School of Business at The University of Utah. Joe is co-host of the popular Monday Morning Data Chat (Spotify / Apple) and co-author of the bestselling O'Reilly book: Fundamentals of Data Engineering.

Bill Inmon (Castle Rock, Colorado)

Bill Inmon (Wikipedia / LinkedIn) is an American computer scientist, recognized by many as the father of the data warehouse. Inmon wrote the first book, held the first conference, wrote the first column in a magazine and was the first to offer classes in data warehousing. Inmon created the accepted definition of what a data warehouse is - a subject oriented, nonvolatile, integrated, time variant collection of data in support of management's decisions. Bill is among the most prolific and well-known authors in the big data analysis, data warehousing and business intelligence arena. In addition to authoring more than 50 books and 650 articles, Bill has been a monthly columnist with the Business Intelligence Network, EIM Institute and Data Management Review. In 2007, Bill was named by Computerworld as one of the “Ten IT People Who Mattered in the Last 40 Years” of the computer profession.

Juan Sequeda (Austin) @juansequeda

Dr. Juan Sequeda is the Principal Scientist at data.world. He joined through the acquisition of Capsenta, a company he founded as a spin-off from his PhD research in Computer Science from The University of Texas at Austin. His goal is to reliably create knowledge from inscrutable data. His research and industry work has been on designing and building Knowledge Graph for enterprise data and metadata management.
Juan has researched and developed technology on semantic data virtualization, graph data modeling, schema mapping and data integration methodologies. He pioneered technology to construct knowledge graphs from relational databases, resulting in W3C standards, research awards, patents, software and his startup Capsenta acquired by data.world in 2019. Juan strives to build bridges between academia and industry as past co-chair of the LDBC Property Graph Schema Working Group, member of the LDCB Graph Query Languages task force, standards editor at the World Wide Web Consortium (W3C) and organizing committees of scientific conferences, including being the general chair of The Web Conference 2023. Juan is the co-author of the book Designing and Building Enterprise Knowledge Graphs and the co-host of Catalog and Cocktails, an honest, no-bs, non-salesy data podcast.

Chris Tabb (London)

Chris Tabb, co-founder of LEIT DATA started his career in the Business Intelligence/Analytics domain 30 years ago. Beginning at Cognos in the 90’s working in the back office before becoming an expert in all their products, and leaving to become an independent BI consultant in 1998. Chris has followed the evolution of the analytics industry, working hands-on with all the technologies in the ecosystems: – Databases, ETL/ELT, BI/OLAP /Visualisation Tools, Big Data Technologies, Infrastructure On premises / Cloud across many vendors, some old some new. Recently with a focus on the Modern Data Stack Evolution Chris has started many movements with a focus on Business Value using a number of hashtags to raise awareness #bringbackdatamodelling / #bringbackdatamodeling #bringbackdocumention under the umbrella of the #meandatastreets that is focused on simplification of the Data Platform architecture and to focus on Business Value.

Andy Petrella (Liège, Belgium) @noootsab

Andy Petrella is an entrepreneur with a Mathematics and Distributed Data background.Andy is an early evangelist of Apache Spark and the Spark Notebook creator in the data community. He is also author of the O'Reilly book: “What is Data Observability”, “What is Data Governance”, and trainer “Distributed Data Science”, “Data Lineage Essentials”, “Machine Learning Model Monitoring”.Andy is also the founder and CEO of Kensu, a data observability solution implementing the Data Observability Driven Development (DODD) method.

Ryan Dolley (Detroit)

Ryan Dolley is a data consultant specializing in BI and analytics, author of the Super Data Blog, and one half of the Super Data Brothers. Check out his discussion on the evolution of BI and moving beyond dashboards on a recent episode of the Joe Reis Show.

David Hughes (Seattle)

David Hughes is the Principal Graph Consultant for Graphable. He has 10 years of experience designing and building graph solutions which surface meaningful insights. His background includes clinical practice, medical research, software development, and cloud architecture. David has worked in healthcare and biotech within the intensive care, interventional radiology, oncology, cardiology, and proteomics domains. He enjoys endurance running, hiking, and spending time with his family in the outdoors when he is not enabling clients to have data epiphanies from their complex data.

Sean Robinson (Charlotte)

Sean Robinson is a versatile data scientist with several years of experience optimizing data processes and building intelligent data systems. Specifically, he specializes in the use of graph data science and Neo4j to abstract complex systems within a domain into a highly dimensional, interconnected knowledge graphs to uncover novel insights which would otherwise remain dormant in other data structures. Sean currently serves both as Lead Data Scientist at Graphable as well as creating and instructing new network science courses at the University of North Carolina at Charlotte’s Data Science graduate program where he instructs the next generation of data scientists on how to integrate graph data science into their toolkit.