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Our Approach

We are the Computer Vision and A.I. Venture Team of the Visual Attention Laboratory at the University of Massachusetts Boston.

For the past 15 years, we have developed, applied, and evaluated computer vision and machine learning technology. Our approach has been the study of human cognition and perception to inform the creation of advanced technical systems. We have also worked on some projects for companies (e.g., Mitsubishi), hospitals (e.g., Brigham & Women’s Hospital, Boston), and other academic institutions (e.g., Harvard University). Due to the success of these projects, we recently established the Computer Vision and A.I. Venture Team that is dedicated to commercial and industrial applications.

Our expertise is in computer vision and machine learning, including the latest advances in technologies such as deep neural networks, sensor fusion, and parallel processing for big data analysis. Our advantage over other groups is our knowledge of human cognition and behavior that we have gained in our academic research through psychophysical experimentation such as eye tracking, electroencephalography (EEG), and functional magnetic resonance imaging (fMRI). This experience has enabled us to build systems that adapt to their human users to optimize human-computer interaction, leading to effective products that are easily adopted by its users.

The Computer Vision and A.I. Venture Team provides services such as the following examples:

(1) We help companies in the financial and medical sectors to design, implement, and evaluate modern machine learning technology for a variety of purposes.

(2) We assist enterprises and schools to build their own Artificial Intelligence Labs, including workbenches, GPU systems, software, study materials, and training of students, teachers, and personnel in various areas of machine learning, A.I., and computer vision.

(3) We can analyze a company’s large and complex data sets using current algorithms to provide insights that can inform the company’s future decisions.

Story

Professor Marc Pomplun has conducted research for academic, medical, and industrial purposes since 1993 and founded the Visual Attention Laboratory in the Department of Computer Science at the University of Massachusetts Boston in 2002. His research group, consisting of undergraduate and graduate students, post-doctoral fellows, and visiting scholars has conducted research on human and computer vision, machine learning, and human-computer interaction. In 2016, Zhimin (Daniel) Xia, the CEO of the robotics company Boston PT info LLC, joined the group, and his entrepreneurial insights led to the inception of the Computer Vision and A.I. Venture Team that provides innovative commercial and industrial solutions.

Meet the Team

Dr. Marc Pomplun, Professor of Computer Science

marc

Dr. Pomplun’s reserarch interests are human vision, visual attention and eye movements, computational modeling and data analysis methods.

He has published more than 200 academic papers and worked on numerous industrial projects on machine learning, computer vision, and data analysis.

He regularly teaches courses at UMass Boston on Artificial Intelligence, Software Engineering, Cognitive Science, Theory of Computation, Computer Vision, Neural Networks, and Applied Discrete Mathematics. His textbook titled “Hands-On Computer Vision” will appear in 2017.

Dr. Zhimin (Daniel) Xia

Research interests: AI, robot , Medical Robot
A Multi-functional Intelligent Service Robot
An Intelligent Hotel-service Robot
An Intelligent Restaurant-service Robot
An Intelligent Service Robot
A Super-capacitor with Heat Dissipation
A Super-capacitor Module
A Standing Medical-service Robot
A Medical-service Robot

Akram Bayat, Ph.D. Candidate

Ms. Bayat peruses her PhD degree under supervision of professor Pomplun at University of Massachusetts Boston. She earned both the master of Electrical Engineering and the master of Computer Science.

Bayat’s research interests are video and image processing with deep learning, data mining, machine learning,  and human- smartphone interaction.

She has published several papers on human activity recognition and human identification. She regularly teaches embedded systems lab using Arduino at UMass Boston.

Shaohua Jia, Ph.D. Candidate

Research interests: Eye movements, machine learning, object recognition, computer vision.

He is currently pursuing a PhD degree in Computer Science at University of Massachusetts Boston, under the supervision of Prof. Marc Pomplun. Prior to entering UMass Boston he received his mater and bachelor degrees in Electrical Engineering at UESTC in China and had been working at ZTE in China for ten years.

Do Hyong Koh, Ph.D. Candidate

Research interests: Eye movements, eye tracking methodology, object recognition, dyslexia
Real time eye movement identification protocol
Qualitative and quantitative scoring and evaluation of the eye movement classification algorithms
Instantaneous Saccade Driven Eye Gaze Interaction
Input evaluation of an eye-gaze-guided interface: kalman filter vs. velocity threshold eye movement identification


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