Who will speak at Data Day Texas 2022

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We continue to confirm speakers for Data Day Texas 2022. If you are doing something cool with data and want to share it at Data Day Texas, we are still accepting proposals.

Heather Hedden (Boston) @hhedden

Heather Hedden (LinkedIn) has been a taxonomist for over 26 years in various organizations and as an independent consultant. She is currently a data and knowledge engineer on the professional services team of Semantic Web Company, vendor of PoolParty software. Previously worked as a taxonomist at Cengage Learning, Gale, Viziant, First Wind, and Project Performance Corporation. Heather has designed and developed, taxonomies, ontologies, and metadata schema for internal and externally published content. She gives workshops on taxonomy creation at conferences, as corporate training, and through an independently offered online course. Heather is author of The Accidental Taxonomist.
Heather will host the following two sessions:
Introduction to Taxonomies for Data Scientists (workshop)
The Future of Taxonomies - Linking data to knowledge (presentation).

Paul Azunre (Austin) @pazunre

Paul Azunre (LinkedIn) holds a Ph.D. in Computer Science from MIT and has served as a Principal Investigator on several DARPA research programs. He has helped develop scientific software in key roles at established organizations such as Oracle and Dun & Bradstreet, as well as a variety of startups. He founded Algorine Inc., a Research Lab dedicated to advancing AI/ML and identifying scenarios where they can have a significant social impact. Paul also co-founded Ghana NLP, an open-source initiative focused on using NLP and Transfer Learning with Ghanaian and other low-resource languages. He frequently contributes to major peer-reviewed international research journals and serves as a program committee member at top conferences in the field.
In his spare time, under the alias Dr. Pushkin, Paul is part of the underground hip-hop, R&B and Afrobeats/Afropop/Afrohiphop group - Isolirium (Spotify / Soundcloud).
Paul is also author of the recently published Transfer Learning for Natural Language Processing from Manning.
Paul will present the following session: Business Transformers - Leveraging Transfer Learning for B2B Insights.

Paige Roberts (Austin) @RobertsPaige

With two decades in the data management industry, Paige Roberts (Linkedin), has worked as an engineer, a trainer, a marketer, a product manager, and a consultant. Now, as Open Source Relations Manager at Vertica, she promotes understanding MPP data processing, open source, and how the analytics revolution is changing the world. Paige is contributor to the upcoming O'Reilly publication 97 Things Every Engineer Should know.
Paige is a total geek who is into role-playing games, LARP’ing in the SCA, Doctor Who, superheroes, space exploration, comics, Tolkien, etc. Paige writes and publishes fantasy and science fiction stories under her maiden name Paige E. Ewing. She won the Kennedy Space Center’s global Space Apps Challenge three years ago for coming up with an idea for growing food on Mars, And she's a pretty mean shot with a recurve, crossbow, or long bow.
Paige will host the following MLOps session: Shortcut MLOps with In-Database Machine Learning.

Satoru Hayasaka (Austin) @sathayas42

Dr. Satoru Hayasaka was trained in statistical analysis of various types of biomedical data. Since his doctoral training, he has taught several courses on data analysis geared toward non-experts and beginners. In recent years, he taught introductory machine learning courses to graduate students from different disciplines. Recently he joined KNIME as part of the evangelism team, and he continues teaching machine learning and data mining using KNIME Analytics Platform.
Boris will present the following hands-on workshop: Introduction to Codeless Deep Learning.

Elliott Cordo (New Jersey)

Elliott Cordo is an expert in data engineering, data warehousing, information management, and technology innovation with a passion for helping transform data into powerful information. He has more than a decade of experience implementing cutting-edge, data-driven applications. He has a passion for helping organizations understand the true potential in their data by working as a leader, architect, and hands-on contributor. Elliott has built nearly a dozen cloud-native data platforms on AWS, ranging from data warehouses and data lakes, to real-time activation platforms in companies ranging from small startups to large enterprises. In his current role as Head of Data at Capsule, Elliott is focused on building a cloud-native data and machine learning platform powering the pharmacy.
Elliott will present the following session: Building a Modern Data Platform Using Advanced Redshift Topologies.

Borislav Iordanov (Montreal) @bolerio

Borislav Iordanov developed one of the first open-source graph databases in the early NoSQL days, HyperGraphDB, but really his main focus and interests have always been around knowledge representation and software development. He built an OWL based, model-driven, low code enterprise application in the late 00s which earned some awards and accolades for innovation in government. Then after several graph related startups or consulting gigs, he has recently jointly Semantic Arts, a wonderful group of people with whom he shares the conviction that a data centric architecture will solve a lot of your problems.
Boris will present the following session: What's up with upper ontologies?.

Michael Uschold (Seattle, WA ) @UscholdM

Michael Uschold, Senior Ontology Consultant at Semantic Arts, has over twenty-five years’ experience in developing and transitioning semantic technology from academia to industry. He pioneered the field of ontology engineering, co-authoring the first paper and giving the first tutorial on the topic in 1995 in the UK.
As a senior ontology consultant at Semantic Arts since October 2010, Michael trains and guides clients to better understand and leverage semantic technology using knowledge graphs. He has built commercial enterprise ontologies in digital asset management, finance, healthcare, legal research, consumer products, electrical devices, manufacturing and corporation registration. More recently he has focused on semantic application development using SPARQL for application code and R2RML for converting relational data into a knowledge graph.
During 2008-2009, Uschold worked at Reinvent on a team that developed a semantic advertising platform that substantially increased revenue. As a research scientist at Boeing from 1997-2008 he defined, led and participated in numerous projects applying semantic technology to enterprise challenges. He is a frequent invited speaker and panelist at national and international events, and serves on the editorial board of the Applied Ontology Journal. He received his Ph.D. in AI from Edinburgh University in 1991 and an MSc. from Rutgers University in Computer Science in 1982.
Michael will present the following 90 minute workshop: Ontology for Data Scientists.

Bob Van Luijt (Amsterdam) @bobvanluijt

Bob van Luijt (LinkedIn / Wikipedia) is a technology entrepreneur, technologist, and new media artist from the Netherlands. Starting his first software business at the age of 15, Bob is co-creator of the open source vector search engine Weaviate as well as co-founder of SeMI Technologies, the company that helps drive its development, Bob's work bridges across art and technology. During his late teens and early twenties, Bob studied music in The Netherlands (ArtEZ) and received a Fulbright scholarship to study at Berklee college of music in Boston. After his studies, he grew his software consultancy business focussing on software enabled business models and products working for a number of enterprise clients in Europe while creating multiple software-art installations which were exhibited at a variety of tech-art and design festivals in Europe and the US. Bob has spoken at over 100 events on the topics of software, business models and creativity in Europe and the US.
Bob will be speaking on vector search.

Kirk Marple (Seattle) @kirkmarple

Kirk Marple is a customer-focused technology leader with extensive expertise with cloud-based microservices, scalable multimedia data ingestion, knowledge graphs (entity extraction/enrichment), machine learning and computer vision integration, and CPU/GPU-based file and data processing workflows.
Kirk will present the following session: Unstructured Data Management: It's not just for your documents.

Arthur Keen (La Luz) @arthurakeen

Arthur Keen has a Ph.D. in Industrial Engineering and Computer Science from Texas A&M university. He has over 20 years experience developing solutions and products in graph analytics, AI, and semantics. He has worked in diverse domains including intelligence, cyber, financial services, logistics, retail, and energy. He has led 3 products from concept to general availability, is listed as inventor on 7 graph-related patents, and is a frequent speaker at conferences.
Arthur will present the following Graph Day session: Knowledge Graph Machine Learning.

Leo Meyerovich (San Francisco) @lmeyerov

Leo Meyerovich is the founder & CEO of Graphistry, the first GPU-accelerated visual graph intelligence platform. Federal, enterprise, science, and tech teams use Graphistry on problems like threat hunting, anti-fraud, user analytics, supply chains, and genomics. Leo's past research at UC Berkeley (PhD) and Brown (ScB) in high performance computing, security, and programming language design received the SIGPLAN 10 Year Test of Time award, multiple best paper awards, and is published in CACM, Security & Privacy, WWW, and others. Several of the ideas are now found in popular browsers, web frameworks, and cloud infrastructure providers. More recently, he helped start the GPU dataframe ecosystem, the initial Apache Arrow implementation, and the medical anti-misinformation open AI effort Project Domino.
Leo will present the following session: What is Graph Intelligence?.

Alexander Morrise (Albany, California)

Alexander Morrise, PhD (Head of Data Science, Graphistry), is a leader in machine learning at the interface of artificial intelligence, natural language processing, and graph neural networks. Alex heads the development of Graphistry[AI], a popular open source graph autoML GPU toolkit that helps convert any data source like CSVs, Databricks, SQL, logs, and graph databases into powerful graph AI visualizations and models. His team works with clients ranging from cybersecurity, fraud, & misinformation to patient & user journeys to the world's largest supply chains. At past startups, he’s built AI systems in fields ranging from news, music, and entertainment (recommender systems) to chip design, process management and quantified self systems for both private and federal customers. Projects include developing AI-powered products for Beats Music (acquired by Apple), Quid (acquired by NetBase), Boomtrain (acquired by ZetaGlobal), Idle Games (acquired by GSN), architecting a privacy-preserving AI that extracts contexts and helps team work at tehama.io, and co-founding Stayopen.com, a modern hotel experience for adventurers seeking community. Before AI startups, Dr. Morrise was a Assistant Professor of Theoretical Physics at USC, Spain, working on topics in Quantum Gravity, Early Universe Cosmology, Particle Phenomenology and String Theory.

Genevera Allen ( Houston ) @genevera_allen

Genevera Allen (LinkedIn / Google Scholar) is an Associate Professor of Electrical and Computer Engineering, Statistics and Computer Science at Rice University and an investigator at the Jan and Dan Duncan Neurological Research Institute at Texas Children's Hospital and Baylor College of Medicine. She is also the Founder and Faculty Director of the Rice Center for Transforming Data to Knowledge, informally called the Rice D2K Lab.
Dr. Allen's research focuses on developing statistical machine learning tools to help scientists make reproducible data-driven discoveries. Her work lies in the areas of interpretable machine learning, optimization, data integration, modern multivariate analysis, and graphical models with applications in neuroscience and bioinformatics. Dr. Allen is the recipient of several honors including a National Science Foundation Career award, the George R. Brown School of Engineering's Research and Teaching Excellence Award at Rice University, and in 2014, she was named to the "Forbes '30 under 30': Science and Healthcare" list. Dr. Allen received her PhD in statistics from Stanford University (2010), under the mentorship of Prof. Robert Tibshirani, and her bachelors, also in statistics, from Rice University (2006).

Jans Aasman (SF Bay)

Jans Aasman (Wikipedia / LinkedIn) is a Ph.D. psychologist and expert in Cognitive Science - as well as CEO of Franz Inc., an early innovator in Artificial Intelligence and provider of the graph database, AllegroGraph. As both a scientist and CEO, Dr. Aasman continues to break ground in the areas of Artificial Intelligence and Knowledge Graphs as he works hand-in- hand with numerous Fortune 500 organizations as well as US and Foreign governments. Jans recently authored an IEEE article on “Enterprise Knowledge Graphs”.
Dr. Aasman spent a large part of his professional life in telecommunications research, specializing in applied Artificial Intelligence projects and intelligent user interfaces. He gathered patents in the areas of speech technology, multimodal user interaction, recommendation engines while developing precursor technology for tablets and personal assistants. He was also a professor in the Industrial Design department of the Technical University of Delft. Dr. Aasman is a noted conference speaker at such events as Smart Data, NoSQL Now, International Semantic Web Conference, GeoWeb, AAAI, Enterprise Data World, Text Analytics, and TTI Vanguard to name a few.
Jans will be presenting the following Graph Day session: What Happens Next? Event Predictions with Machine Learning and Graph Neural Networks

Dave Bechberger ( Anchorage ) @bechbd

Dave Bechberger is a Sr. Graph Architect on the AWS Neptune service team. A long time graph and distributed data practitioner, Dave has spent over 20 years in full stack software development and specializes in building data architectures in complex data domains such as bioinformatics, oil and gas, supply chain management, etc. Dave has previously spoken at a variety of national and international technical conferences including NDC Oslo, NDC London, as well as previous GraphDay conferences in Texas, San Francisco and Seattle. He is a co-author of Graph Databases in Action by Manning Publications.
Dave will present the following Graph Day session: A gentle introduction to using graph neural networks on knowledge graphs.

Yue Cathy Chang ( Sunnyvale ) @yuec

Yue Cathy Chang is an executive recognized for thought leadership and execution in digital transformation. She is passionate about addressing business challenges and often finds herself and her team "parachuting" into situations to tackle challenging and meaningful data needs. Cathy has led teams and functions at blue-chip enterprises as well as startups, across financial services and high-tech industries, working with leaders of centralized and distributed data teams, all betting the next product differentiation on data. She is currently an AVP in banking and financial services at an American multinational technology corporation.
Cathy holds MS and BS degrees in electrical and computer engineering from Carnegie Mellon University, MBA and MS degrees from MIT, and two granted US patents. She's a co-author, with Jike Chong, of the Manning publication How to Lead in Data Science.
Cathy will co-present the following Data Science session:
For the overwhelmed data professionals: What to do when there is so much to do?

Jike Chong (Sunnyvale) @jikechong

Jike Chong is an executive who nurtures teams and crafts cultures to produce billion-dollar business impacts. He built and grew multiple high-performing data functions in public and private companies and nurtured dozens of ambitious individual contributor data scientists into leaders; some have gone on to lead teams of more than 70 data scientists. Jike was part of the executive team that took Yiren Digital Ltd public on NYSE. He also expanded and led the data team as the chief data scientist at Acorns, designed and executed a project predicting venture investment risks at Silver Lake, and led the Hiring Marketplace Data Science team at LinkedIn, serving a business line with $4B a year in revenue.
Jike received his bachelor’s and master’s degrees in electrical and computer engineering from Carnegie Mellon University and a PhD in electrical engineering and computer science from the University of California, Berkeley. He's a co-author, with Yue Cathy Chang of the Manning publication How to Lead in Data Science.
Jike will co-present the following Data Science session:
For the overwhelmed data professionals: What to do when there is so much to do?

Shirshanka Das (Santa Clara) @shirshanka

Shirshanka Das (LinkedIn) is co-founder and CEO of Acryl Data, the company which is commercializing the open source DataHub project, a real-time metadata platform used by LinkedIn, Expedia, Saxo Bank, Klarna, Viasat, and many others. Prior to founding Acryl, he was the overall architect for Big Data at LinkedIn from 2010 to 2020, and responsible for creating the metadata and data management strategy at the company. As part of this, he founded the DataHub project and shaped its evolution to a metadata platform that powers DataOps, MLOps, productivity, and governance use cases at LinkedIn. He is also a PMC and committer on the Apache Gobblin project which manages 100PB+ of data assets at rest at LinkedIn, and is deployed in production at other large companies like Verizon, PayPal etc. Prior to LinkedIn, Shirshanka worked on high-performance serving systems at Yahoo and PayPal. Shirshanka has a Ph.D. in Computer Science from UCLA.
Shirshanka will present the following session: What is a metadata platform and why do you need it?

Max De Marzi (Chicago) @maxdemarzi

Marx De Marzi (Linkedin) is addicted to graphs. You may consider him a graph database enthusiast. He spent 8 years at Neo4j and recently made the swith to AWS Neptune. He is a blogger and an open source contributor, both activities which stem from passion: teaching people about graphs. He is always open to talk graphs, always learning, and nothing thrills him more than finding easy graph solutions to hard relational problems. He has been helping people get to the "graph epiphany" for over a decade. He is an avid graph database modeler, leveraging his knowledge of mechanical sympathy and experience to deliver dozens of graph uses cases over the years.
Max will present the following Graph Day session: Outrageous ideas for Graph Databases

Dr. Ying Ding (Austin)

Dr. Ying Ding is the Bill & Lewis Suit Professor of Information Technology at the University of Texas School of Information. Before that, she was a professor and director of graduate studies for data science program at School of Informatics, Computing, and Engineering at Indiana University. She has led the effort to develop the online data science graduate program for Indiana University. She also worked as a senior researcher at Department of Computer Science, University of Innsburck (Austria) and Free University of Amsterdam (the Netherlands). She has been involved in various NIH, NSF and European-Union funded projects. She has published 240+ papers in journals, conferences, and workshops, and served as the program committee member for 200+ international conferences. She is the co-editor of book series called Semantic Web Synthesis by Morgan & Claypool publisher, the co-editor-in-chief for Data Intelligence published by MIT Press and Chinese Academy of Sciences, and serves as the editorial board member for several top journals in Information Science and Semantic Web. She is the co-founder of Data2Discovery company advancing cutting edge AI technologies in drug discovery and healthcare. Her current research interests include data-driven science of science, AI in healthcare, Semantic Web, knowledge graph, data science, scholarly communication, and the application of Web technologies.
Ying will present the following Graph Day session: Fighting COVID-19 using Knowledge Graphs

Amy Hodler (Kettle Falls, Washington) @amyhodler

Most recently, Amy Hodler was the AI and Graph Analytics Program Manager at Neo4j, where she promoted the use of graph analytics to reveal structures within real-world networks and predict dynamic behavior. Prior to that, she was Sr. Market Manager, Analytics and Machine Learning at Cray. Amy is the co-author of the O’Reilly book, Graph Algorithms: Practical Examples in Apache Spark and Neo4j, co-author of Knowledge Graphs: Data in Context for Responsive Businesses, and a contributor to the upcoming book, AI on Trial.

Thorsten Liebig (Ulm, Baden-Württemberg, Germany) @tliebig

Thorsten Liebig is co-founder and managing director of derivo GmbH. In this role he supports companies and organizations to reveal and exploit the knowledge in their data sources by means of semantic technologies. His scientific background is in ontologies and reasoning methods. As part of his responsibilities at derivo, Thorsten has contributed to Knowledge Graph projects at Festo, Siemens or Springer Nature. His key expertise is in KG modeling, rule-based reasoning and graph visualization.He is part of team behind SemSpect a graph exploration and querying tool for RDF & Neo4j and writes articles for the official Neo4j Blog. Thorsten was responsible co-author of OWLlink, an official W3C member submission and is co-organizing the Scalable Semantic Web Systems workshop series.

Joey Jablonski ( Austin ) @jrjablo

Joey Jablonski (LinkedIn) is VP of Product at Manifold, where he builds trusted relationships with our customers, allowing us to more fully understand their needs and how we can help. Joey partners with customers to ensure that a product mind-set is part of all engagements—allowing for delivery of value quickly in any project, and building over time to drive adoption of new data-centric capabilities in an organization. He has extensive experience delivering innovative solutions to customers.
Prior to Manifold, Joey was VP of Core Data at Northwestern Mutual, where he delivered high quality and compliant data products to facilitate decision, automation, and new product launches. While there, he built the first data product management team to enable better engineering prioritization, more effective product value definition, and technology simplification. Prior to Northwestern Mutual, Joey was VP of Data Engineering and Analytics at iHeartMedia. There, he led a team delivering data science, data engineering, broadcast engineering, and attribution capabilities to the largest audio media company in the world.

Corey Lanum (Boston) @corey_lanum

Corey Lanum (LinkedIn), has a distinguished background in graph visualization. Over the last 15 years he has managed technical and business relationships with dozens of the largest defense and intelligence agencies in North America, in addition to working with many security and anti-fraud organizations in private industry. Prior to joining Cambridge Intelligence as their US Manager, Corey was helping the customers of i2 (now IBM) and SS8 to solve their most complex graph data challenges.
Corey is the author of Visualizing Graph Data from Manning Publications.
Cory will present the following Graph Day session: Visual timeline analytics: applying concepts from graph theory to timeline and time series data

Milecia McGregor (Tulsa) @flippedcoding

Milecia McGregor is a senior software engineer that's worked with JavaScript, Angular, React, Node, PHP, Python, .NET, SQL, AWS, Heroku, Azure, and many other tools to build web apps. She also has a master's degree in mechanical and aerospace engineering and has published research in machine learning and robotics. She started Flipped Coding in 2017 to help people learn web development with real-world projects and she publishes articles covering all aspects of software on several publications, including freeCodeCamp. She also travels around the world speaking at tech conferences about various software engineering topics ranging from machine learning, PWAs, and managing a career in tech.
Milecia will host the following MLOps session: Using Reproducible Experiments To Create Better Models.

Ryan Mitchell (Boston) @Kludgist

An expert in web scraping, web security, and data science, Ryan Mitchell has hosted workshops and spoken at many events, including Data Day and DEF CON. She teaches web programming and data science and has 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 the author of Web Scraping with Python (O’Reilly) and Instant Web Scraping with Java (Packt Publishing), as well as two Linkedin courses: Python Data Structures with Trees and Web Scraping with Python.
Ryan will be presenting the following session: What is Truth? - Strategies for managing semantic triples in large complex systems

Jonathan Mugan (Austin) @jmugan

Jonathan Mugan (Linkedin) is a researcher specializing in artificial intelligence, machine learning, and natural language processing. His current research focuses in the area of deep learning for natural language generation and understanding. Dr. Mugan received his Ph.D. in Computer Science from the University of Texas at Austin. His thesis was centered in developmental robotics, which is an area of research that seeks to understand how robots can learn about the world in the same way that human children do. Dr. Mugan also held a post-doctoral position at Carnegie Mellon University, where he worked at the intersection of machine learning and human-computer interaction. One of the most requested speakers at the Data Day Texas conferences, he recently also spoke on the topic of NLP at the O’Reilly AI conference, and is the creator of the O’Reilly video course Natural Language Text Processing with Python. Dr. Mugan is also the author of The Curiosity Cycle: Preparing Your Child for the Ongoing Technological Explosion.
Jonathan will be presenting the following session: A Path to Strong AI

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 be speaking as part of the MLOps track.

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.
Sean will be presenting the following Graph Day session: History of Network Science - A Look at How Networks Have Connected Us

Dr. Bivin Sadler (Dallas)

Originally from Dallas Texas, Dr. Bivin Sadler finished a BS in mathematics magna cum laude from Texas Tech University before beginning his professional career in Scottsdale, Arizona, at Motorola. He worked as a statistician and software engineer for 2.5 years, working primarily on a companywide tool to predict when software projects could be released with optimal statistical properties (Six Sigma). Upon completion of the project, he moved to San Diego, and while playing professional beach volleyball for two years, finished a master’s degree in applied math at San Diego State University. He then moved back to Dallas to earn a PhD in statistics from SMU and finished his degree in 2014 after winning the Walsh Award for the top score on the qualifying exam taken after the third year of coursework.
Dr. Sadler was hired as part of the faculty at SMU after graduation and began a dual appointment teaching both undergraduate and graduate classes in the statistics department and online with the recently formed Master of Science in Data Science (MSDS) program. Academically, he has presented his work in item response theory at various conferences and is currently working on several domestic and international consulting projects. He became a full-time member of the MSDS faculty in August 2018 and, in addition to consulting projects and teaching, actively contributes towards developing new courses and enhancing existing ones at the SMU MSDS program.

Jörg Schad (Berlin / San Francisco) @joerg_schad

Jörg Schad (Linkedin / GitHub) is CTO at ArangoDB where he splits his time between Berlin and San Francisco. Prior to ArangoDB, he was Technical Community Lead and Distributed Systems Engineer at Mesosphere, and Big Data Engineer at SAP. Jörg received his Ph.D. at Universität des Saarlandes for research around distributed databases and data analytics.
Jörg will host the following session: Graph Powered Machine Learning for Python Developers

Joshua Shinavier (San Francisco) @joshsh

As a co-founder of what is now Apache TinkerPop, Joshua Shinavier contributed to the first common APIs for graph databases, the original TinkerPop query language which influenced Gremlin, and the first tools which aligned the property graph and RDF data models, starting with neo4j-rdf-sail in 2008. As a Research Scientist at Uber, he led development of the Dragon data integration platform. Joshua is host of The Graph Show, and co-organizer of the Bay Area Category Theory meetup. Joshua holds a PhD in computer science from RPI's Tetherless World Constellation, where he focused on combining knowledge graphs with augmented reality.
Josh will host the following session: Transpilers gone wild: announcing Hydra.

Ryan Wisnesky (Cambridge, Massachusetts )

Ryan Wisnesky (LinkedIn) obtained B.S. and M.S. degrees in mathematics and computer science from Stanford University and a Ph.D. in computer science from Harvard University, where he studied the design and implementation of provably correct software systems. Previously, he was a postdoctoral associate in the MIT department of mathematics, where he developed the categorical query language CQL. He currently leads open-source and commercial development of CQL as CTO of Conexus AI. He maintains an active collaboration with the information-integration department of IBM Research, where he contributed to the Clio, Orchid, and HIL projects.

Michael Zelenetz (Long Island)

Michael Zelenetz is a software engineer at Peak6 Investments. Prior to Peak6 he led data science teams in two hospitals. He is interested in building data-enabled products. He holds a masters from Harvard University and BA from Yeshiva University.
Michael will host the following BI / Data Science session: This Dashboard Should Have Been a Meeting.

Sachin Sharma (Kaiserslautern)

Sachin Sharma is a Machine Learning Research Engineer at ArangoDB whose aim is to build Intelligent products using thorough research and engineering in the area of Graph Machine Learning. He completed his Masters’s degree in Computer Science with a specialization in Intelligent Systems. He is an AI Enthusiast who has conducted research in the areas of Computer Vision, NLP, and Graph Neural Networks at DFKI (German Research Centre for AI) during his academic career. Sachin also worked on building Machine Learning pipelines at Define Media Gmbh where he worked as a Machine Learning Engineer and Scientist.
Sachin will host the following hands-on 90 minute worksop: Thinking outside of the Euclidean Space: An Introduction study to Graph Machine Learning and its Applications with Hands-on-Experience.