Dr. Leland Beck
My current research is in the area of Computer Science education. I am interested in finding out more about how students learn key concepts in Computer Science, and in exploring new teaching strategies and curricular approaches to enhance that learning. I am presently working on a five-year project entitled “Cooperative Learning Methods for Java-Based CS1 Courses,” sponsored by the National Science Foundation, to develop and evaluate cooperative learning materials for introductory programming courses. This research is being done in collaboration with Dr. Alexander Chizhik of SDSU’s School of Teacher Education. Our preliminary experiments have shown that many students learn significantly more with the cooperative learning approach. We are now working on an extension of this project, which will evaluate the effectiveness of our cooperative learning approach when it is used by different instructors, with different populations of students, and in different educational environments. In the near future, I hope to apply similar cooperative-learning methods to other courses in the Computer Science curriculum.
Dr. Rob Edwards
My group focuses on the interface between Computer Science and Biology, with something of an emphasis on microbial biology. Microbes are the most important living organisms, responsible for both the bad things that we live with such as infection and disease, as well as the good things like bread and wine. Microbes themselves are affected by viruses, and one aspect of my research is to understand the viruses and how they alter the microbes behavior.
We work closely with biologists, and aid them with their data analysis and discovery. Our friends in biology generate large amounts of DNA sequence data (long strings of letters from a four-letter alphabet), and we write software to unravel the functions encoded by these letters.
The Edwards Bioinformatics Lab has a wide range of diverse interests, from android programming (you may have seen our you tube videos) to data mining from pictures and images. Together, we work at the frontier of applying computational science to biological important questions.
Dr. Marie Roch
Professor Roch’s lab uses signal processing and machine learning techniques to examine issues related to free ranging animals through the analysis of their sounds recorded in natural environments. We have developed detection, classification, and data management algorithms, permitting us to determine what animals are present and vocalizing as well as information about their distribution and habitat preferences. These methods are used by The US Navy, The National Oceanic and Atmospheric Administration (NOAA), and others for organizing information about marine mammals and can be used to help make science-based public policy decisions. We collaborate closely with researchers at The Scripps Institution of Oceanography, UCSD (Scripps Whale Acoustics Lab, Behavioral Acoustic Ecology Lab, and the Marine Bioacoustics Lab). Further information on our lab’s projects can be found at: overview and publications.
Professor Roch’s research has been funded by The Office of Naval Research, The National Oceanographic Partnership Program, HPWREN, and The US Navy CNO N45/Living Marine Resources Program.
Dr. Mahmoud Tarokh
My area of interest is intelligent robots and systems with emphasis on mobile robots and articulated rovers. Currently I work on several research projects including rover navigation in rough terrain, path planning, robotic person following, and manipulator kinematics. Rover navigation, which has been supported by NASA, involves kinematics modeling and analysis, control strategies and animation of the rover traversing over rugged terrain. In path planning, I apply genetic algorithms and fuzzy logic to find optimal paths for rovers. Robotic person following employs image processing techniques and fuzzy logic control for a rover to follow a person in previously unknown environments, and has application both in space and on earth. SPAWAR Systems Center has provided support for the person following project. I have also devised two novel techniques for the manipulator inverse kinematics problem, one uses genetic algorithms and the other is based on decomposition, classification and approximation techniques. Another project is development and construction of an autonomous agile rover to traverse distances of up to 20 miles over rough terrain autonomously without human intervention. There are many applications for such a rover, such as scientific investigations (e,g. observation and sample collection), planetary explorations, and information gathering in hostile environments. The construction and instrumentation of the rover is well underway, and many challenging problems in such diverse areas as control, vision, pattern recognition and learning, are currently under investigation. I have been awarded a grant to develop a robotic helicopter for imaging and monitoring pollution and habitat restoration at Tijuana Estuary. You can find more information at my website: Intelligent Machines and Systems Laboratory
Dr. Faramarz Valafar
The main area of my research is biomedical informatics. Our research group is interested in the development of data mining and pattern recognition techniques in all areas of biomedical informatics. In particular, we have projects in genetic basis of disease (e.g. drug resistant tuberculosis and autism) where we apply machine learning techniques to systems biology, functional genomics and proteomics, microarray data analysis and (pair-wise and multiple) sequence alignment in order to understand the genetic mechanism of disease. In these projects we develop and use spatio-temporal data mining and pattern recognition techniques for determination of gene regulatory networks from temporal microarray and whole genome sequencing data. In sequence alignment, we use a variety of local and global sequence alignment techniques for alignment of gene and protein sequences. We use these techniques for phylogeny studies as well as RNA structure determination. My other area of interest is high-performance computing (HPC). Our group is interested in the development and application of HPC algorithms for science and engineering. In this area, we are studying parallelizing compilers, communication pattern optimization in scientific applications, and the development of online high-performance and distributed databases. Examples of such applications include the development of high-performance tools amenable to distributed parallel environments for biomedical informatics and numerical analysis, sensu lato. You can find more information at the website of the Biomedical Informatics Research Center’s (BMIRC) website.
Dr. Marko Vuskovic
My research interests are in two areas of robotics and pattern recognition. In robotics I develop real-time control of multifunctional artificial hand (prehensile EMG pattern recognition, synergetic mapping between joint space and object space, human body to machine interface). I am also interested in assistive wheelchair robot control system for quadropledgic patient (voice command-based user interface, robot command/control languages and scripting libraries). In pattern recognition, my research is on adaptive resonant theory-based (ART) neural networks (incremental learning algorithms, stability issues, supervised and non-supervised learning using ART networks, application to glycan-array classification and cancer diagnosis), multi-class support vector machines and their application in bioinformatics and communication networks, and spectral and wavelet-based methods for feature extraction from temporal signals.
Dr. Wei Wang
My research interests include the broad areas of wireless networking, cyber-physical systems, and computer-aided healthcare systems. My current research is focused on optimization and scheduling algorithm design to bridge the gap between emerging applications and energy-constrained internet of things. Applications include intelligent transportation system design using heads-up display and smartphone for driver safety warning, as well as supply chain management for pharmacy anti-counterfeiting. I am also focused on innovative wireless and portable solutions for seizure patient monitoring, and microwave tomography imaging solutions for early stage breast cancer screening. Specific features such as brain wave signals and tumor region of interests are identified, real-time cyber transmissions and cloud-based big data resources are leveraged, and classification and machine learning techniques are utilized to provide decision support information for doctors. I am also interested in educational robotics, developing hands-on laboratory training materials to improve student learning in CS and broad STEM areas.
Dr. Roger Whitney
My general interests are centered on software development. Designing and developing software is an enormous and growing industry. Despite its importance software development has more than its share of problems, disasters and cost overruns. We do not seem to be good at developing software or training people to develop software. I am interested in the use of agile processes and dynamically-typed languages to improve the software development process. Currently I am involved in exploring the use of agile techniques and dynamically type languages in Web development and implementing web portals. The goal is to determine if agile processes and languages are beneficial in these areas. My current project is developing a framework for testing web applications to be used in support of agile development. Given SDSU’s role supplying the region with trained labor, I am also in interested in how to better educate software developers. For more details on my work, visit my home page.
Dr. Tao Xie
My primary research interest lies in the area of high-performance computing, energy-efficient storage systems, parallel/distributed systems, and security-aware scheduling. In particular, I have been investigating efficient scheduling schemes and resource management strategies to support high performance applications running on dedicated and non-dedicated clusters, which consist of off-the-shelf hardware and software components. After joining SDSU, I concentrated on high-performance/highly reliable storage systems and energy-efficient computing. My work on these topics focuses on the following research problems: data placement, data redistribution, data reconstruction, the relationship between energy-saving techniques and disk reliability, and flash-based mobile disk arrays. You can find more information at my Computer Architecture and Systems Lab web site.
Dr. Mary Thomas
My research interests focus on computational science, parallel programming, and advanced computational environments that support high-end scientific applications.
I am investigating parallelization and nesting techniques for 3D staggered grid coastal ocean models, such as the Unified Curvilinear Ocean Atmospheric Model (UCOAM). UCOAM is a non-hydrostatic, large eddie simulation (LES) CFD model capable of running both ocean and atmospheric simulations at very high resolutions (meter-scale). Parallelization approaches include MPI and GPU techniques. For the nested model research, a new model is being developed which nests the UCOAM model within a coarser, global ocean model (kilometer scale).
Computational environments (CE’s) involve the use of emerging technologies and cyberinfrastructure to integrate advanced computational, data, and networking infrastructure. Research projects include development of the Cyberinfrastructure Web Application Framework (CyberWeb). CyberWeb is designed to facilitate development of virtual environments (VOs), Web services, and portals associated with scientific and high-performance computing. CyberWeb utilizes Cyberinfrastructure (
For more information about my research and my courses, go to my web site.
Dr. Jo Ann Lane
Current research interests are in the area of software engineering and systems engineering for software-intensive systems with an emphasis on systems of systems (SoS) and enterprise-wide systems. Currently working on
- Methods to assess system interoperability and to improve software-intensive system interoperability for systems that are part of one or more SoS
- Techniques to detect and manage emergent behaviors of systems that interoperate in one or more SoS
- Engineering tradespace analysis methods to support system and software affordability constraints
- Expediting systems and software engineering and identifying limits of schedule compression
- Balancing lean and agile techniques with technical debt