February Event: Powering the Transition: Data Science for Smarter Energy
Join us for a double-feature on the data science powering humanity’s transition to smarter, cleaner energy
Please join Charlottesville Data Science on the evening of Tuesday, February 24 for a double-feature on the data science powering humanity’s transition to smarter, cleaner energy. Manaar Salama, a Data Operations Analyst at RECmint, will explore how machine learning is improving solar forecasting — helping maintain grid stability and ensuring the economic viability of renewable energy. Next, Charlie Henderson, founder and CEO of Stacker Group, will dive into real-time decisioning architecture, showing how closed-loop systems can sense, decide, and act at millisecond speed. Together, these talks illuminate how data science is reshaping energy systems from the rooftop to the grid.
We’ll be gathering in person at Vault Virginia on the Downtown Mall. Thanks again to the team at Vault for hosting us!
Talk 1: Solar Forecasting: Driving the Shift from Gas to Grid
The transition to a less gas-driven, more-electrified future is a critical step in addressing climate change, but it relies heavily on our ability to predict the unpredictable. As solar energy becomes a key variable of this shift, the vast amounts of data generated by residential systems present a unique opportunity. Accurate forecasting is becoming a necessity for maintaining grid stability and ensuring the economic viability of renewable energy for homeowners.
In this talk, Manaar Salama will explore the intersection of data science and solar energy, focusing on the growing landscape of the Mid-Atlantic. She will discuss the challenges of modeling energy production data and how machine learning is being used to solve problems — such as ensuring accurate estimations so that homeowners’ SREC (Solar Renewable Energy Certificate) payments are processed without delay. By the end of this presentation, attendees will understand the key role of predictive modeling in the green energy transition and how ML can remove financial friction for everyday users.
This talk is relevant for data analysts, scientists, or professionals in the energy industry, as well as anyone interested in how data science can drive real progress toward sustainability.
Talk 2: Next Best Action: Architecting the Future of Model-driven, Real-time Decisioning
The energy sector requires real-time decision-making. “NBA” (Next Best Action) is an architectural pattern that brings more data into the context of every decision, while enabling continuous learning. Charlie Henderson, founder and CEO of Stacker Group, will break down how real-time decisioning combines millisecond-speed execution, continuous data integration, and live decision context to move beyond batch-based decisioning. You’ll see how closed-loop systems that sense, decide, act, and learn make it possible to deliver fast, in-app AI decisions, with fewer trade-offs.
About the Speakers
Manaar Salama is a Data Operations Analyst at RECmint, a Charlottesville-based SREC aggregator. She specializes in analyzing residential energy production trends and optimizing the data pipelines that connect homeowners to renewable energy incentives. A graduate of UC Berkeley with a degree in Data Science, Manaar is dedicated to advancing data-driven solutions that support the transition to a sustainable future.
Charlie Henderson is the founder and CEO of Stacker Group and Stacker AI Lab, where he helps Fortune 1000 enterprises overcome technical barriers to fully leveraging their data and ML models. His work focuses on architecting high-performance parallel processing solutions, transforming legacy systems into modern reactive architectures, and enabling real-time decision-making at scale. Stacker Group serves leading enterprises in finance and clean energy.
More upcoming events around Charlottesville
Tuesday, February 10: Cville AI Explorers hosts their February event, Transformers Explained. Nish Tahir, a Principal Applied AI Research Engineer at Telus Digital, will explore the underlying machine learning architecture that powers most modern AI systems.
Sunday, February 22: The Call for Proposals for the Applied Machine Learning Conference closes at 11:59pm. We are seeking proposals for 30-minute talks and 90-minute tutorials that share knowledge, insights, and practical experience in data science, AI, machine learning, and related fields. For more details and to submit a proposal, please see the Call for Proposals page on the conference website.
Friday-Saturday, April 17-18: The Applied Machine Learning Conference returns to Charlottesville. A two-day event by and for practitioners, the AMLC is the signature annual event for the data science, AI, and machine learning community in Charlottesville and the surrounding region. The Call for Proposals is now open, and ticket sales will begin soon. Sponsorship opportunities are also available.
P.S. Know friends or colleagues who might enjoy our Charlottesville Data Science events? Forward this message to them! You’d be surprised how many people study or work in data science, AI, or machine learning in the Charlottesville area and aren’t aware that there’s a robust community and monthly event series in town.
Sorry, I'm going to have to miss this one. I spent a number of years in energy trading where information and timing were always critical to the traders, so I understand how valuable these discussions are. Unfortunately, I have a conflict but hope to make the next meeting.