Scalar Research is a full-service artificial intelligence & data science consulting firm.
We help companies tackle complex business challenges with data-driven products and solutions leveraging cutting-edge machine learning and advanced analytics.
Tackle your most challenging business problems with state-of-the-art tools that leverage machine learning and data science.
Understand how machine learning and data science can help drive meaningful improvements to your core metrics.
Gain a proprietary edge in your industry by collecting, annotating, and processing massive datasets with our help.
Find actionable insights, automate repetitive tasks, and make your products smarter with custom machine learning solutions.
Integrate powerful models into novel or existing products and tools to enable your team and customers to leverage your data.
Bring machine learning and data science knowledge to your company. Equip your team to leverage data to make meaningful improvements to your core metrics.
Develop your team's capabilities with private, in-person workshops and lectures tailored specifically for your business.
Grow your in-house expertise at scale with educational materials such as video lectures, whitepapers, and more.
Scalar Research is a full-service artificial intelligence and data science consulting firm.
We started Scalar to bridge the gap between groundbreaking machine learning research and complex business challenges. Our team helps companies understand how they can leverage data to drive outsized improvements to their core metrics.
Our consulting practice provides end-to-end services in strategy, R&D, and deployment for data-driven products and solutions. Our team also helps companies develop their in-house capabilities with private workshops, lectures, and educational materials.
Our clients have ranged from large corporations to startups in diverse industries, such as healthcare, chemicals, education, and software.
Gabriel is a machine learning scientist with experience in applying cutting-edge academic research to solve real-world problems.
He began his training as a B.S. & M.S. student in computer science at Stanford University, where he received multiple academic distinctions, including the President's Award for Academic Excellence.
He was one of ten students to graduate with honors in computer science in his undergraduate class at Stanford. His thesis investigated quantum deep learning algorithms using NASA's D-Wave quantum computer, and was selected for a presentation at the AQC 2017 Conference in Tokyo, Japan.
During his master's program, he conducted research at the Stanford Partnership in AI-Assisted Care, a joint lab between the Stanford Computer Science Department (Prof. Fei-Fei Li – Chief Scientist of Cloud AI/ML at Google) and the Stanford School of Medicine (Prof. Arnold Milstein). His research focused on improving clinical care and reducing monitoring costs in hospitals by leveraging machine learning and computer vision, and resulted in a first-author manuscript selected as Top 10 Research Paper at the NIPS Machine Learning for Health 2017 Workshop.
Gabriel also has extensive software engineering experience. At Google and Facebook, he worked on backend infrastructure for enterprise tools responsible for billions of dollars in revenue. He's also created an advertising supply-side platform that handled millions of ad requests per day, built an algorithmic trading platform and quantitative strategies for cryptoasset markets that handled over US$10M in volume, and held positions at startups and investment firms.
Let's find out how your company can leverage data to tackle its most challenging business problems.