First Signal ☕📊 — Quantitative AI Research

Join us at The Rooftop at Club Quarters World Trade Center, a stunning venue in the heart of the Financial District, for an evening of conversation with the researchers, engineers, data scientists, and students in NYC who are working at the intersection of AI, machine learning, and quantitative finance.

No slides. No presentations. No pitches. Just drinks, honest conversation, and meeting the people in this city who care about the same hard problems you do — reinforcement learning in stochastic environments, deep learning for time series, NLP on financial text, backtesting methodology, and everything else at the cutting edge of quantitative AI research

The quantitative AI research community in New York is massive but fragmented. The academics are in their departments. The industry researchers are behind NDAs. The ML engineers are heads-down building. The independent tinkerers are working alone at 2 AM. Rarely do these people end up in the same room.

Come with whatever you're working on, whatever you're stuck on, or whatever paper you read this week that made you rethink something. Bring your questions, your half-baked ideas, and your honest takes on what's actually interesting versus what's just hype.

The Rooftop at Club Quarters World Trade Center has a beautiful lounge and bar with the kind of atmosphere where these conversations happen naturally — sophisticated without being stuffy, relaxed enough to actually talk.

Who should come:

Data scientists, ML engineers, quantitative researchers, financial engineers, PhD students, academics, independent researchers, and anyone in NYC who is serious about AI applied to quantitative problems. All experience levels welcome. Whether you're publishing papers on temporal fusion transformers or just starting to learn PyTorch — you belong here.

What we talk about:

Reinforcement learning architectures for sequential decision-making. LLMs applied to earnings calls, SEC filings, and unstructured financial text. Deep learning for time series — transformers, CNN-BiLSTM, neural forecasting. Factor modeling, signal research, and feature engineering for noisy data. Backtesting methodology and all the ways to fool yourself. Market microstructure and order book modeling. Alternative data as a research subject. Infrastructure — Python, PyTorch, Spark, and the engineering that makes research reproducible. And whatever else comes up when you put a room full of quantitative minds together with drinks in their hands.

🍸 Drinks and food available for individual purchase at the bar and restaurant ⏰ Arrive when you can — the earlier you come, the more people you'll meet