Meet the Minds Behind Velonae
Our team combines decades of experience in machine learning, financial markets, and data science to push the boundaries of what's possible in finance
Dr. Sarah Chen
Before joining Velonae in early 2024, Sarah led the quantitative research team at Goldman Sachs, developing proprietary algorithms that generated over 0M in alpha for institutional clients. She holds a PhD in Applied Mathematics from MIT and has been recognized as one of the top 40 under 40 in fintech by Financial Times.
Her research focuses on pattern recognition in complex financial datasets, particularly in identifying hidden correlations that traditional supervised methods miss. She's passionate about making advanced ML techniques accessible to financial professionals who may not have deep technical backgrounds.
Michael Rodriguez
Michael joined us from Netflix, where he built recommendation systems that served 200+ million users daily. His expertise lies in creating robust, scalable infrastructure that can handle the massive data volumes typical in financial markets. He's particularly skilled at optimizing model performance without sacrificing accuracy.
What sets Michael apart is his ability to bridge the gap between research and implementation. He's developed our core processing engine that can analyze millions of transactions in real-time while maintaining 99.9% uptime. His background in distributed systems makes him invaluable for our growing client base.
Dr. James Wilson
James brings a unique perspective, having spent 10 years managing a 0M hedge fund before transitioning to academia at Stanford. His research focuses on how human behavioral patterns create exploitable inefficiencies in markets, and how unsupervised learning can identify these patterns at scale.
His work on clustering techniques for identifying regime changes in financial markets has become foundational to our approach. James is also our key liaison with academic institutions, ensuring our research stays at the forefront of both finance and machine learning developments. He regularly speaks at conferences and has authored two books on quantitative finance.
Our Collective Strength
Together, our team represents over 30 years of combined experience in financial markets, machine learning, and data science. We've learned that the most powerful insights come from combining diverse perspectives and expertise.
Market Intelligence
Deep understanding of financial markets, from traditional equities to emerging digital assets. We've seen multiple market cycles and understand how patterns evolve over time.
Research Excellence
Our research has been published in top-tier journals and implemented at billion-dollar institutions. We believe in rigorous testing and peer review of all our methodologies.
Technical Innovation
We build systems that can process terabytes of market data in real-time while maintaining the flexibility to adapt to changing market conditions and new data sources.
Our Mission
We believe that the most valuable insights in finance are often hidden in plain sight. Traditional supervised learning approaches require you to know what you're looking for, but the markets are constantly evolving in ways that historical patterns can't predict.
That's where unsupervised learning comes in. By letting the data speak for itself, we can discover patterns and relationships that even experienced analysts might miss. Our goal is to democratize access to these advanced techniques, making them practical and actionable for financial professionals at all levels.
We're not just building tools – we're building a new way of thinking about financial data that puts discovery and exploration at the center of decision-making.