Granica
Neeraja Abhyankar is a Software Engineer specializing in Machine Learning at Granica since January 2024. Previously, Neeraja worked at Dexterity, Inc. from October 2020 to December 2023 as a Robotics Engineer, focusing on perception, state estimation, machine learning, and computer vision algorithms for the company's AI platform. Before that, Neeraja served as a Graduate Research Assistant at the University of Washington within the Machine Learning, Optimization, and Data Interpretation lab from September 2016 to August 2020, researching submodular optimization and algorithmic fairness in machine learning. Additional experience includes a Software Engineering Internship at Facebook and research internships at the Indian Institute of Science and The Institute of Mathematical Sciences, Chennai. Neeraja holds a Master of Science in Electrical and Computer Engineering from the University of Washington and a Bachelor of Technology in Engineering Physics from the Indian Institute of Technology, Madras.
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Granica
Granica is an AI research and systems company helping enterprises leverage AI efficiently and safely. Our mission is to make AI 10,000x better. We believe data is the first-mile problem to solve in this mission. Our first system is a novel training data platform for enterprise AI that unlocks efficiency and privacy through our flagship services tailored for Generative and Traditional AI: Granica Crunch is a family of advanced data compression/reduction models which enable AI/ML teams to add and use more data to improve their ML accuracy and performance while controlling their infrastructure costs. Crunch delivers deep cost efficiencies for data at any scale, at rest and in use. Granica Screen is an advanced data privacy-enhancing service that unlocks even more data for AI/ML teams to safely improve model performance. It guarantees state-of-the-art privacy at scale, enabling Private LLMs and Privacy-preserving AI. Granica Chronicle is a deep data visibility service for disparate AI data stores. Enabling unification, collaboration and insights into data usage for AI and ML. Our research is deeply rooted in information science, machine intelligence, computer vision, natural language, and distributed systems, with a special emphasis on elevating the efficiency and safety of AI systems through fundamental and innovative research. We're backed by remarkable institutional investors in AI, Data, and Cloud; and several industry luminaries in business and technology.