Dr. Scott Penberthy

Scott is a member of Google Cloud’s CTO office (OCTO), a team of industry ex-CTOs who co-innovate with top customers and product teams. Scott reframes scientific processes as “tensors in, tensors out,” extracts data before and after a complex system, then builds and trains ML models to replicate, improve and optimize our best human efforts. Once the pandemic hit, Scott shifted his focus to healthcare. There he discovered the role of information retrieval and AI in understanding the source code to life, which can bring people together at time of need (and even before!) with much higher precision and lower costs.

Scott has demonstrated efficacy in reverse engineering mainframe systems in healthcare claims processing, searching for exoplanets and minerals on the moon with NASA, and cutting the costs in millions of customer chat & voice interactions. Scott was blessed with the opportunity to build an amazing AI team within the CTO Office, where the team instigated call center AI, document AI, AI notebooks, and many of Google’s largest AI-first cloud deals. Scott holds a PhD in AI with multiple degrees from MIT and the University of Washington.

Previously, Scott landed public cloud at PwC for 200k employees in 2014, moved a video site for 5m users to AWS in 2008, sold a social photo site with 50M users in 2007, built mobile phone “widgets” in 2005, and launched a $13B web middleware and $4B web hosting business in the 90s. Scott enjoyed working directly with the CEO of IBM, Lou Gerstner, during Lou’s turnaround of Big Blue. Years later he had a similar role with Bob Moritz, CEO and Chairman of PwC. Scott is an avid programmer, triathlete, space fan, guitarist, chef and father of two amazing daughters. Occasionally, Scott speaks in public.

Dr. Timothy Haas

Session Title:

How Firms can Apply Data Science to Save Species

Dr. Haas specializes in multivariate statistics, spatial statistics, decision making using probabilistic networks, computer intensive statistical methods, time series, and ecosystem management. Currently, Dr. Haas is developing tools to help manage and conserve wildlife. He recently published the book “Improving Natural Resource Management: Ecological and Political Models” (2011, Wiley).  He has recently co-authored a paper in the IEEE Transactions on Cybernetics that uses an agent-based model to study the poaching-driven extinction risks of the rhinoceros.

Dr. Haas is active in several professional organizations and serves as referee for the Journal of the American Statistical Association, Atmospheric Environment, and Statistics and Probability Letters. He participates regularly in workshops on statistical topics.

Ed Shee

Session Title:

From Model to Micro-service – ML Deployments At Scale

With a background in cloud computing and a passion for machine learning, Ed has combined those skills to become a leader in the field of MLOps (machine learning operations). Organiser of Tech Ethics London and MLOps London, Ed is heavily involved in lots of developer communities and, thankfully, loves both beer and pizza.

Dr. Santona Tuli

Session Title:

Machine Learning Orchestration with Airflow

I love building end-to-end data science pipelines: architecting, testing and productionizing statistical data analyses to inform good decision making. My fortes include strategic data featurization, explainable machine learning and result validation. I enjoy explaining technical concepts clearly to a wide variety of audiences.

Currently, I help make data and machine learning workflow orchestration with Apache Airflow developer friendly and more powerful. At Astronomer, we study the usage and painpoints of Airflow in order to simplify the open source software as well as build additional tooling to enrich enterprise data orchestration and empower data science professionals.

Previously, I built ML pipelines for understanding and answering natural language queries for enterprise clients at scale in the CRM space.

I also led a team of 5 data physicists studying nuclear physics phenomena in ultrarelativistic collisions at the Large Hadron Collider (CERN). We built analysis pipelines for several terabytes of sensor event data as well as the machinery to test these pipelines using Monte Carlo simulations of events. We measured a rare particle family in proton-nucleus collisions for the first time – a 1 in 100, 000 signal – providing new constraints on the theory of the strong force.

Sam Portillo

Session Title:

Principles of Building Greenfield Data Platforms

Peter Aiken

Session Title:

Achieving Data Acumen: Improving Workforce Literacy

Click here to Meet Peter

Abigail Byram

Session Title:

Panel on Data Ethics

Abigail Byram a Data Engineering Consultant with SingleStone Consulting with a background in engineering solutions for data governance platforms in large-scale enterprises. She is also an undergraduate instructor for the VCU Computer Science Foundations program and is currently enrolled in the Online Master’s in Computer Science program at Georgia Tech. She loves puzzles in all shapes and sizes from jigsaws to puzzle-platformer video games to piecing together complicated engineering problems. Data is her passion: it’s all about conforming data methodologies to the context of the data and fitting them together into a cohesive and responsible data solution.

Jigyasa Grover

Session Title:

Sculpting Data for Machine Learning

Jigyasa Grover is a Machine Learning Engineer at Twitter, ML Google Developer Expert and the co-author of the book ‘Sculpting Data for ML’. She has a myriad of experiences from her brief stints at Facebook, Inc., National Research Council of Canada, and Institute of Research & Development France involving Data Science, mathematical modeling, and software engineering. Red Hat ‘Women in Open Source’ Academic Award Winner and Google Summer of Code alumna, Jigyasa is an ardent open-source contributor as well. She served as the Director of Women Who Code and Lead of Women Techmakers for a handful of years to help bridge the gender gap in technology. In her quest to build a powerful community with a strong belief in “we rise by lifting others,” she mentors aspiring developers and Machine Learning enthusiasts in various global programs. Apart from her technological ventures, she enjoys exploring new places, hanging out with friends and family, and has been recently having fun with baking.

Rishabh Misra

Session Title:

Sculpting Data for Machine Learning

Rishabh Misra is an ML Engineer at Twitter, Inc, and co-author of the book “Sculpting Data for ML”. He combines his past engineering experiences in designing large-scale systems, working at Amazon and Arcesium (a D.E. Shaw company), and research experiences in Applied Machine Learning, with publications at top venues, to develop distributed Machine Learning relevance systems as part of the Content Quality team. In his downtime, he enjoys watching sci-fi shows, gaming, and spending time with his family.

Raghavan Srinivas

Session Title:

The Pre-cloud to Multi-Cloud journey with Cassandra on Kubernetes

Raghavan “Rags” Srinivas (@ragss) works as a lead container Developer Advocate at Datastax with a mission to help developers build scalable and secure container based systems. His areas of focus are containers, Open Source and DevSecOps. His general interests are in distributed systems, with a specialization in Cloud Computing and security. He worked on Kubernetes, Azure, Cloud Foundry during its early stages and helped customers with implementations. He writes for InfoQ, has spoken on a variety of technical topics at conferences around the world, written for developer portals, organized Hands-on Labs and taught graduate and online classes in the evening.

Rags brings with him over 30 years of hands-on software development and over 20 years of solutions architecture and technology evangelism experience. He has evangelized and influenced the architecture of a number of emerging technology areas. He is also a repeat JavaOne rock star speaker award winner.

Rags holds a Masters degree in Computer Science from the Center of Advanced Computer
Studies at the University of Louisiana at Lafayette. He likes to hike (has hiked the Everest Base Camp), run and generally be outdoors, but most of all, loves to eat. He umpires baseball and generally enjoys watching just about every professional sport.

Read more at: https://that.us/members/ragsns/ on THAT.

Kevin Jones

Session Title:

Not-so-good-vibrations: Electric Grid Oscillations and Unearned Data Wisdom

Kevin Jones received his Ph.D. from Virginia Polytechnic Institute & State University as a Harry Lynde Bradley Fellow in 2013 where he studied synchrophasor technology, wide area measurement systems, and linear state estimation. Kevin developed the open source Linear State Estimator, now commercialized by several industry vendors, used for improving resiliency of real-time transmission control centers. While at Dominion, Kevin developed the Analysis On Demand (ANODE) platform, increasing the analytic throughput of the outage planning team by more than 1000x. He championed much of Dominion’s synchrophasor data program over the last decade and now oversees an organization of approximately 30 engineers who focus on physics-based modeling and simulation, data-driven operations support, and engineering analysis of time-series sensor data from the electric transmission grid.

Marcus Thornton

Session Title:

Live Podcast on Data Privacy and Governance

Marcus Thornton serves as the Deputy Chief Data Officer (CDO) and Interim CDO for the Commonwealth. He is from Danville, Virginia and has worked in software engineering for the last 20 years. Before becoming the Deputy CDO, he worked for a data company that specializes in the collection of retail pricing data across all of North America. As the Deputy CDO, he serves as the Chief Operating Officer to the Chief Data Officer and the CDO’s technical adviser. He creates new partnerships between the Office of Data Governance and Analytics and Commonwealth agencies and shows them how sharing data across the Commonwealth can be leveraged to make more-informed decisions and increase their own efficiencies.

Souj Narasimhacharya

Session Title:

Live Podcast on Data Privacy and Governance

Jodi Kuhn

Session Title:

Panel on Data Ethics

Jodi is an Epidemiologist with over 15 years of experience working for the Commonwealth and loves building nimble teams to solve complex problems. She is the Director of the Office of Data Quality and Visualization in the Virginia Department of Behavioral Health and Developmental Services where she has brought together a team of scientists to provide analytic consultation to program areas across the agency. She views her current role as the ultimate integration of epidemiology and behavioral health, two subject areas close to her heart.

Jodi remains connected to her roots in research as a member of the VCU Institutional Review Board (IRB), conducting full-board reviews of biomedical and socio-behavioral studies. In her spare time she enjoys spending time with family and friends rating parallel parking from her Carytown porch.

Zachary Knitter

Session Title:

Panel on Data Ethics

Zac is a Data Engineer with wide-ranging experience in Web development, programming, and social science research. He is currently a Data Engineer in the Office of Data Quality and Visualization in the Virginia Department of Behavioral Health and Developmental Services where he specializes in automating complex business processes and streamlining them across the enterprise.

Zac holds a B.A. in Political and Social Thought from the University of Virginia and an M.A. in the Social Sciences from the University of Chicago. He brings an interdisciplinary approach to the collection and analysis of data at every opportunity.