Research Areas of Focus
Director of Student Animation Center
His research areas include Bioinformatics and Family History. He is currently working with professors from Computer Science and Biology on DNA analysis algorithms and applications. His specific research area is Phylogenetic Analysis (determining evolutionary histories through the examination of DNA) which requires extensive network and computational resources. Current research into mapping algorithms for short reads has been applied to the problem of diagnosing Alzheimer’s disease from DNA samples. Dr Clement is also involved in Family History research and has been part of the team developing the Relative Finder and Descendancy Explorer applications that use data from familysearch.org to increase user interest in their ancestors.
Our research focuses on developing machines and algorithms that learn from and collaborate with people to solve challenging problems. To do this, we seek to develop novel algorithms and systems related to the areas of human-machine interaction, artificial intelligence, machine learning, multi-agent systems, and robotics. Recent and ongoing projects include creating artificial intelligence that forges cooperative relationships with people in the face conflict, learning how to get machines to voice and understand narratives in long-term human-machine interactions, and figuring out how to coach people to overcome conflict in their relationships.
Dr. Deccio’s research interests are in network measurement and anti-abuse for improved stability and security of the Internet. He directs the Internet Measurement and Anti-Abuse Laboratory (IMAAL) at BYU. Much of his work focuses on aspects of the Domain Name System (DNS), which provides the critical service of translating domain names to resources, such as numerical IP addresses. Current research projects in the IMAAL include: an analysis of anti-spam mechanisms for email, measuring their complexity and adoption trends over time; measuring the deployment of anti-DDoS mechanisms in DNS servers; investigating behaviors of DNS servers that are potentially privacy-revealing; and measuring DNS resolver behavior and placement, in proximity to authoritative DNS servers of popular DNS domains.
His research interests include Real-time 3D Computer Graphics, Object- oriented graphics, Vector Field tools for Computer Animation, and the Creation and Navigation of Virtual Environments.
Dr. Farrell’s research focuses on the emerging field of fine-grained visual categorization (FGVC), where, instead of recognizing objects at a coarse level (e.g. bird or car), his research tackles the difficult task of training a computer to find the highly-localized and often subtle characteristics (differences in shape, coloration, etc.) that allow precise identification at the level of fine-grained or “subordinate-level” categories (e.g. genus/species, make/model/year). Overcoming this key challenge bridges the divide between objects in the visual world around us and the vast wealth of digital information about them.
Professor Goodrich recently simulated robotic swarms of two different sizes to assess their effect on steering effectiveness and energy expenditure, by placing leaders in different positions of the swarm. In addition to robotic swarms, he has also researched GUIs for selecting trade offs in multi-objective optimization problems. He evaluated GUIs that allow a human to express intent by expressing desirable trade offs.
Center for Animation
Professor Jones works at the intersection of emerging technologies and user experience. Together with students, he investigates new user experiences made possible by emerging technology. His lab is currently investigating the use of interactive computing in hiking and prototyping with 3D printers, circuits and software.
Professor Martinez does research over a broad range of Machine Learning areas. Recent work includes improved learning mechanisms for deep neural networks, document recognition and classification, unsupervised clustering of documents, novel approaches for learning with multiple related outputs, automatic composition of music to bring about desired physiological responses, and understanding of what makes certain tasks more difficult in machine learning. His lab has published over 200 refereed journal and conference papers in the areas of machine learning and neural networks.
His research hopes to address test and verification in software engineering by pursuing automatic techniques for program verification for concurrent and sequential systems. He has particular interest in ways to explore relevant schedules for concurrent systems and ways to automatically derive test sets for sequential systems.
Dr. Morse’s primary area of research is computer vision, with cross-overs into image processing, computer graphics, robotics, machine learning, and high-performance computing.
The Advanced Information Retrieval Applications (AIRL) Research group at BYU is actively pursuing various research projects in recommending items for children using the collaborative-filtering approaches and developing interactive game systems designed for children/adults with Autistic Spectrum Disorder (ASD).
The Internet Security Research Lab (ISRL) designs and evaluates security tools that are easy to use. Current projects are in the areas of secure email, secure chat, two-factor authentication, key management, certificate revocation, TLS security, and blockchain technology. Students conduct research that ranges from designing and building new security systems to conducting qualitative and quantitative usability studies. Dr. Seamons is especially interested in working with undergraduates that want to obtain a research experience that launches them into a top-20 PhD program.
The Applied Machine Learning (AML) lab studies topic modeling and human computer interaction. Recently, we’ve been working on a semi-supervised machine learning model that allows users to give feedback as the machine picks topics for the documents. Algorithms such as this allow people to interact with and gain information from large quantities of text documents.
Our research is in the area of Software Engineering, with a particular focus on engineering and supporting distributed, high-throughput, low latency systems. We are interested in techniques and approaches to improve the tolerance systems have to failures in dependent systems. When there are failures, we are also interested in tool support to help engineers more quickly determine the cause of the failure and mitigate the issue. In our lab we use a wide range of methodological tools from qualitative human centered research to prototype development and experimentation.
The Computational Science Laboratory investigates new algorithms for solving problems in computational biology, computational chemistry and computational physics. Emphasis is placed on finding efficient algorithms that can be run on parallel computers.
His main areas of interest include neural networks, machine learning, artificial intelligence, evolutionary computation and computational creativity.
Dr. Warnick’s research concerns the analysis and design of processes for making decisions from data. The work focuses on fundamental relationships between information, uncertainty, and complexity as seen from the perspectives of a wide variety of applications. Key issues for this science of information and decisions include approximation, learning, control, verification, and optimization.
In the Perception, Control and Cognition Laboratory, our goal is to build agents that perform at human levels in complex tasks. We do this by combining Bayesian models with deep reinforcement learning. Current projects include control algorithms for a simulated android, high-level linguistic planning, theory of mind for autonomous agents, improved depth estimation for augmented reality, and automated affordance extraction via word vectors. We’re also working on a suite of advanced simulators that stress high level cognitive functions.
Software design techniques, software development and reusability, software engineering, object-oriented analysis and design, conceptual modeling, system specification languages, software development tools.
Dr. Zappala works on security and usability. His lab collaborates closely with Dr. Seamons’ lab on numerous systems and usable security projects. Recent research projects include measuring the prevalence of proxies that intercept TLS connections, developing operating system services for authenticating and securing Internet connections, improving authentication in secure messaging applications like Signal, and improving the usability of secure email systems. Dr. Zappala has research funding from both the National Science Foundation and the Department of Homeland Security.