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STAC Summit, 28 October 2025, New York

STAC Summits

STAC Summits bring together CTOs and other industry leaders responsible for solution architecture, infrastructure engineering, application development, machine learning/deep learning engineering, data engineering, and operational intelligence to discuss important technical challenges in trading and investment.

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WHEN
Tuesday, October 28, 2025
STAC Exchange (Exhibits) opens at 8:30am EDT
Conference starts at 9:00am EDT
Networking lunch at ~12:00pm EDT
Conference concludes at ~5:00pm EDT
Reception immediately following
WHERE
New York Marriott Marquis
1535 Broadway
New York
Astor Ballroom
7th Floor

Topics tend to cluster in four areas:

  • Quant technology. Architectures for big data and big compute workloads such as model training, strategy research & backtesting, tick analytics, alt data processing, market and credit risk, portfolio optimization, fraud detection, and compliance.
  • Low-latency infrastructure. Architectures for fast decision making and trade execution, primarily in automated trading. Networks, FPGA, servers, software, and other technologies for market data, trading and matching algorithms, execution, and trade-time risk.
  • Command and control. Monitoring of trade flows, time synchronization, and orchestration and management of on-prem and cloud-based infrastructure.
  • AI/ML. Architectures and infrastructure for models and data exploration, training, and inference with deep neural networks (especially LLMs) and statistical machine learning on-prem and in the cloud.
While applied AI may be part of quant technology and low-latency topics, there will be a separate, dedicated AI Track at the NYC STAC Summit that focuses on the AI infrastructure needs of finance, from banking and insurance to trading and investment —from the model to the metal™.

We're currently putting together the agenda for this event.
To see agendas from past STAC Summits and AI STAC events, click here.

 

About STAC Events & Meetings

STAC events bring together CTOs and other industry leaders responsible for solution architecture, infrastructure engineering, application development, machine learning/deep learning engineering, data engineering, and operational intelligence to discuss important technical challenges in finance.