Vlad is the CTO and Chief Scientist at FiscalNote, where he is responsible for setting the technology vision and execution strategy for the global R&D organization. At FiscalNote he leads teams supporting a growing suite of products and enabling future capabilities by focusing on using machine learning and natural language processing (NLP) to create practical applications for analyzing, modeling, and extracting knowledge from the growing amount of mostly unstructured data related to government, policy and law. As the 10th employee, he developed the first version of the company’s patented technology to help organizations understand and act on policy changes, led major technical partnerships and data augmentation and integration initiatives, and as part of the executive team helped secure over $250 million in funding from Series A on and grow the business from pre-revenue to over $100M ARR, 3,000 customers, and public offering on NYSE.

Previously, he worked as a researcher in a number of academic and industry settings, completing his Ph.D. in CS, as an NSF and NDSEG Fellow, at the University of Maryland and his B.S. in CS and Philosophy at Columbia University. He has over 15 years of experience developing, leading, and advising technology teams building state-of-the-art machine learning and NLP systems. His work has led to over 10 patents, he has published more than 20 peer-reviewed articles in and serves on the program committees for top-tier conferences, such as ACL, NAACL, and EMNLP, and has been covered by media such as Wired, Vice News, and Washington Post.

Vlad is also the founder of Machine Opinings, a technology consultancy, and advisor to high-growth SaaS and consumer startups such as Enquire.ai, TealBook, Buy Nothing, HeadsUp and Summit Consulting, and an angel investor in over a half dozen others.

Full CV and publication list.