COMPUTER SCIENCE FACULTY AND STAFF DIRECTORY
My primary interests are in cybersecurity, blockchain, IoT and smart cities, and parallel and distributed systems. I have worked on projects that produced innovative techniques to evaluate security for blockchain systems and IoT and smart cities applications.
My research interests broadly cover machine learning and artificial intelligence applications. I work with several data modalities including computer vision, audio/text, and human-centric data such as fMRI, eye-gaze, and physiology. I have researched applications for student learners, teachers in classrooms, generalized AI, athlete injury prevention, and sentiment analysis.
I am a graduate of the UWC of Hong Kong and NYU. In 2014 I was honored by the National Science Foundation at the White House as one of the “100 SuperStar Computer Science instructors” in the United States. I spent 2017 on a fellowship studying high performing low-income schools across the US.
My research is in computer vision and machine learning, and specifically, developing techniques for visually recognizing people, their gestures, and their actions, and for applying these recognition techniques to complex systems of interacting people and machines. I also hold an appointment in the Molecular, Cellular and Integrated Neuroscience (MCIN) program.
My area of specialty is systems security and advanced networking. My current research is in blockchain and applying AI anomaly detection to network security. I am also the President of Invykta LLC, a cyber-security consulting company. I was previously President and CEO of Secure64 Software Corporation and spent 24 years in R&D and Marketing at Hewlett Packard.
My research interests are in the areas of modeling and testing software in the object-oriented, aspect-oriented, and component-based paradigms. I serve on the editorial boards of prominent technical publications, co-chair major conferences in the field, and am a member of the ACM and Senior Member of the IEEE.
My research lies at the intersection of Computational Linguistics/Natural Language Processing, Artificial Intelligence, Machine Learning, and Embodied Cognition. I use simulation and multimodal methods to research human language understanding, communication, and reasoning in a computational context.
My research interests cover several key areas in reliable and secure computing. I work on topics that include vulnerability discovery, security risks and economics, software reliability, test effectiveness, impact of testing on reliability, fault modeling, and fault tolerance.
I teach undergraduate courses in the Department of Computer Science and joined the faculty after 37 years in industry, primarily at HP in software R&D. My experience includes projects in languages, software engineering, networking, network management, user experience, and databases. I received my M.S. in computer science from CSU in 2013.
My research is on efficient algorithms for combinatorial problems. I am especially interested in recursive decompositions of arbitrary graphs and digraphs, algorithms for classes of graphs that are subclasses of the class of perfect graphs, and classes of graphs that have geometric representations.
My main research area focuses on improving user interaction by eliciting (hand and full-body) gesture sets by user elicitation, developing interactive gesture-recognition algorithms, multimodal user interaction for virtual and augmented reality, and how to increase interest in computer science for non-CS, entry-level college students.
My research interests are in the area of Big Data for the sciences, with an emphasis on issues related to predictive analytics, storage, retrievals, and metadata management. The research crosscuts data science and data engineering especially in the context of voluminous, high-velocity data. Software produced by my group has been deployed in agricultural sciences, environmental monitoring, epidemiology, and meteorology.
My research interests are broadly in cloud computing, big data, and analytics with a focus on using machine learning, probabilistic, and statistical techniques to address scaling, autonomy, and tractability issues. These efforts target processing, routing, storing, and mining data streams generated by networked sensors, observational equipment, and programs.
My research focuses on data networking. Any problem that involves moving bits, bytes, packets, chunks, files, or another abstraction between two machines is of interest to me. Much of my recent work has been in wireless networks. As department chair, I am working to improve the diversity of our student body and to expand our industry partnerships.
My research broadly focuses on software algorithms, hardware architectures, and hardware-software co-design for energy-efficient, fault-resilient, real-time, and secure computing. These efforts target multiscale computing platforms, including embedded and Internet of Things (IoT) systems, cyber-physical systems, mobile devices, and datacenters.