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Virtual Chapter Event
Wednesday, December 17, 2025, 12:00 AM - 1:00 PM EST
Category: Events

 

 

 

 

Virtual Chapter Webinar Event

Wednesday, December 17, 2025
12:00
 PM ET - 1:00 PM ET

Register Today!

Time-Series Intelligence: Scientific Machine Learning (ML) for Forecasting and Strategy

Key Takeaways: 

  • Precision Forecasting Drives Competitive Advantage: Scientific ML eliminates models and fitting parameters to outperform traditional statistical methods in volatile environments.
    • Takeaway: Businesses can anticipate demand shifts, market cycles, and operational bottlenecks with greater accuracy—turning uncertainty into strategic foresight.
  • Enhances Decision Confidence: Unlike black-box deep learning, Scientific ML emphasizes explainable dynamics rooted in domain knowledge.
    • Takeaway: Executives gain trust in AI-driven forecasts, enabling faster adoption and alignment across finance, operations, and strategy teams.
  • Scalable Inference Enables Real-Time Adaptation: Efficiently updates as new data streams are added.  No models, no parameters, no bias.
    • Takeaway: Businesses can continuously refine forecasts without retraining—ideal for high-frequency decision environments like supply chains or financial markets.

  • Unlocks Innovation: Scientific ML blends insights from thermodynamics, control 
Speaker:
Mark Temple-Raston, PhD, CEO and Founder 

Mark Temple-Raston, PhD, is a visionary leader bridging the gap between advanced mathematics and real-world business transformation. With over 25 years of global expertise spanning Wall Street and cutting-edge technology, he founded Decision Machine in 2015—a pioneering company that revolutionizes market forecasting through scientific machine learning, delivering deductive and exact predictions that drive strategic decision-making.

Mark's distinguished Wall Street career includes a decade at Citigroup, where he spearheaded critical initiatives across Global Functions, Regulatory Risk Management (Basel II), Enterprise Architecture Governance, and the Chief Data Office during the Dodd-Frank era. His leadership spans across diverse industries—from healthcare and logistics to aerospace—where he's consistently delivered enterprise-scale solutions in architecture, data governance, and risk management.

Armed with a doctorate in Applied Mathematics and Theoretical Physics from the University of Cambridge, Mark uniquely combines theoretical rigor with practical business acumen. His approach combines deep foresight with clear communication—building transparent, mathematically precise systems that tackle complex business challenges with clarity and confidence.

Mark's work represents the future of data-driven decision making, where scientific methodology meets strategic business insight to unlock unprecedented market intelligence.                      


Thank you to our Corporate Sponsors