Research Bio

My research interests stem from a deep curiosity to understand how people interact with computing technology, and what could be next. In human-centered computing, natural user interaction (NUI) is the study and development of “advanced” interface technology that uses touch, voice, vision, and motion for interaction. Understanding the types of input people will make, as well as how they want the system to respond, is the core of this approach.

Tailoring NUIs to work for specific user groups or populations, including children or users with disabilities, is a focus area for our lab. We have shown that kids (counter to common “digital native” narratives) miss more taps onscreen, execute gestures differently, and make those gestures more inconsistently, as compared to adults. We also established that kids are more comfortable using exploration and “trial and error” to learn how to use novel touchscreen interfaces, like our PufferSphere, than adults are.

Our more recent projects are exploring human-AI interaction for these users and contexts, and increasing tech literacy in a world ripe with potential misuses. I couldn’t do this work without my great network of collaborators and talented students. For more on my research projects and my research students, check out my lab’s website: the Intelligent Natural Interaction Technology (INIT) Lab.

Previously, I was a Research Assistant Professor in the Department of Information Systems at the University of Maryland-Baltimore County (UMBC) in Baltimore, MD. I received my Ph.D. degree from the Human Computer Interaction Institute (HCII) in the School of Computer Science (SCS) at Carnegie Mellon University in Pittsburgh, Pennsylvania. My thesis work focused on the area of handwriting-based interfaces for intelligent tutoring systems for algebra equation-solving and was advised by Jie Yang and Ken Koedinger. In addition to an M.S. in HCI from Carnegie Mellon, I have a B.S. and an M.S. in computer science with concentrations in artificial intelligence, human-computer interaction, and software engineering from Drexel University in Philadelphia, Pennsylvania. For my M.S. thesis I used genetic programming to evolve board evaluation functions for computer agent players of the strategy game Acquire. Earlier research involved creating a computer-aided conceptual design tool for engineers called CUP.

My industry work experience includes positions at the User-Centered Interfaces Group at Lockheed Martin Advanced Technology Laboratories (LM ATL), where I worked on advanced user interface technologies such as spoken-language understanding, handwriting recognition, and gesture recognition from 2008 to 2010; and at the Fuji-Xerox Palo Alto Laboratory (FXPAL) [now defunct], where I worked on the Collaborative Exploratory Search project in 2007.

Formal Bio: Lisa Anthony is an associate professor with tenure in the Department of Computer & Information Science & Engineering (CISE) at the University of Florida in Gainesville, FL. She holds a BS and MS in Computer Science (Drexel University, 2002) and a PhD in Human-Computer Interaction (Carnegie Mellon University, 2008). After earning her PhD, Lisa worked in both industry and academic research, including two years in a DARPA- and ONR-funded R&D lab and two years at the University of Maryland Baltimore County focusing on multimodal interaction. Her lab has made its primary impact in understanding how to develop advanced interaction interfaces and algorithms for children in a variety of contexts, including education, healthcare and serious games. Dr. Anthony has received industry and government funding, including the NSF CAREER award, and is known for her work on multistroke gesture recognition, particularly the $N and $P gesture recognizers, and gesture applications for children. Her research has earned multiple best paper awards, including two “Ten Year Impact” awards (ACM ITS/ISS 2021, ACM ICMI 2022). Currently, Dr. Anthony is focusing on efforts to create a symmetrical mentoring program within UF and beyond.