Our Story
We're passionate about AI research that enhances the everyday experience for the millions of users interacting with our technology. We focus on implementing the latest architectures and algorithms and creating cutting-edge solutions in areas like speech recognition, text-to-speech, and speaker verification.
Our Philosophy
We work at the intersection of ML Research and ML Engineering. To a great extent, it is hard to decouple these two disciplines. ML, at its heart, is an empirical discipline. The theoretical foundations of ML are sound in certain areas and evolving in other areas as we continue to push the envelope. The projects we work on involve natural language processing, computational linguistics, large language models (LLMs), networking, security, knowledge acquisition, insight generation, and related areas.
We firmly believe in the “Farm to Table” approach to ML: where possible, we curate our own data to train our own models, and productize them through our unique ML operations (MLOps) approach for better customer experience. As part of this process, we gather new insights which we publish at peer-reviewed conferences and disseminate as technical talks.
Our Team
Machine Learning Ops
Systems for Machine Learning
Speech Recognition
Machine Learning
Natural Language Processing
Security in Multimedia Comms Networks/Protocols
Software Engineering
Inner Source
Natural Language Processing
Computational Psycholinguistics
Generative AI
Speech Processing
Machine Learning Ops
Container-Based Virtualization Technologies
Container Orchestration Systems
Natural Language Processing
Spoken Language Understanding
Text-to-Speech
Robotics
Speech-to-Text
Computer Vision
Text-to-Speech
Robotics
Speech-to-Text
Computer Vision
Our Team
With diverse experience in the ML industry and research, Joseph is passionate about building robust systems inspired by new technological discoveries. He holds an M.S./B.S. in Computer Science from University of Massachusetts Amherst and was a UMass Amherst Bay State Fellow.
Vijay has authored and co-authored over 75 papers, 5 books, 19 Internet Engineering Task Force (IETF) RFCs, and been granted 9 patents by the US Patent Office, many of which are also international patents. In addition to his duties at Vail Systems, he is a Research Associate Professor of Computer Science at Illinos Tech. He holds a Ph.D., Computer Science from Illinois Institute of Technology, and M.Sc. and B.Sc. in Computer Science from Bradley University.
Jordan’s work leverages her background in Computational Psycholinguistics (MA, Northwestern University) to conduct research and develop models that enable Vail technology to better process and produce human language. She possesses a strong understanding of machine learning and artificial intelligence, especially as it is informed by linguistic analysis.
B.S. in Applied Mathematics, B.S. in Statistics, M.S. in Machine Learning and Data Science
Rick has been with Vail Systems for over 20 years and holds a Bachelor’s Degree in Mathematics and Computer Science from University of Illinois, Chicago.
Dan's interests largely lie in spoken language understanding and have included work on speaker recognition, spoof detection and speech generation. He holds a PhD in Physics from Iowa State University, bringing a unique perspective and analytical toolkit to problem solving.
Join the Fun
(no, seriously, we have a blast)
