Leading research through innovation
Our faculty are pursuing a diverse collection of research opportunities whose goals are the advancement of the computer science field of study, IT industry collaboration including technology transfer, and the pursuit of important societal problems faced by our many public and private sector partners. Our approach has also grown from traditional computer science themes such as algorithmic analysis and computer language development to one which embraces the integration of computing in fields like computational sciences, bioinformatics, disaster management, Geographical Information Systems, as well as cutting edge technology topics like cloud computing, social networks, cyber security, and highly reliable systems. Our research community firmly believes in a multi-disciplinary approach to solve both theoretical and applied computing problems.
Our School has reached a high sustained level of research and scholarly activity and is now taking the next step towards prominence by competing for and winning very prestigious national and international awards, and in recruiting outstanding faculty.
TerraFly is a technology and tools for visualization and querying of geospatial data. The visualization component of the system provides users with the experience of virtual “flight” over maps comprised of aerial and satellite imagery overlaid with geo-referenced data. The data drilling and querying component of the system allows the users to easily explore geospatial data, to create geospatial queries, and get instant answers supported by high-performance multidimensional search mechanisms. TerraFly’s server farm ingests, geo-locates, cleanses, mosaics, and cross-references 40TB of basemap data and user-specific data streams. TerraFly’s Application Programming Interface allows rapid deployment of interactive Web applications and has been used to produce systems for disaster mitigation, ecology, real estate, tourism, and municipalities. TerraFly’s Web-based client interface is accessible from anywhere via any standard Web browser, with no client software to install.
The Integrated Computer Augmented Virtual Environment (I-CAVE), an instructional and research visualization facility located in the ECS building of FIU’s Modesto Maidique Campus. This facility can be used for both undergraduate and graduate instruction in a variety of fields across the natural and social sciences, humanities, and professional programs. I-CAVE provides new opportunities for students and faculty for research, creative projects, learning exploration and data visualization. The benefit for users is tremendous as this virtual environment provides for 2-D and 3-D visualizations of scalable data, a completely immersive experience of a virtual space, and the capacity to explore new ideas, places or objects in a dynamic and interactive visual environment.
Research Experiences for Teachers (RET)
Cyber-enabled technologies provide opportunities for teachers of science, math, and technology to work with faculty at Florida International University. Through a six (6) week program, teachers participate in technical and educational research as part of a research community.
Trajectory Privacy Preservation in Mobile Sensor Networks
(Advisors: Dr. Pissinou, Dr.Kim)
Mobile sensor networks are finding rapidly growing applications in a wide range of data collection applications, such as natural disaster forecasting, health condition monitoring, military reconnaissance, and traffic monitoring. Meanwhile, privacy is becoming an indispensable concern of these applications. This project targets an important but mostly untouched privacy issue: trajectory privacy preservation in mobile sensor networks. Mobile sensors, carried by users or vehicles, communicate with peer nodes and the base station through wireless media continuously. Therefore, trajectory information not only indicates the movement patterns of the sensors but also reveals personal preferences and habits of users. Trajectory privacy invasion could lead to several types of risks for users, including personal safety, consuming profiling, and interference attacks.
Natural Language Processing and Computational Linguistics
(Advisors: Mark A. Finlayson)
Prof. Mark Finlayson’s work intersects artificial intelligence, computational linguistics, cognitive science, and the digital humanities. His research focuses on the science of narrative (as a language object), including understanding the relationship between narrative, cognition, and culture, developing new computational methods and techniques for investigating questions related to language and narrative, and endowing machines with the ability to understand and use narratives for a variety of applications. Prof. Finlayson seeks highly motivated REUs and RETs to address important problems in this area, including building automatic natural language processing tools for extracting syntax and semantics; building user-facing tools for language corpus annotation, and collecting richly annotated corpora of stories.
Research Labs and Groups
Principal Investigator and Director: Dr. Naphtali Rishe
The CREST center focuses on the following research areas: High-confidence reactive software systems, multidimensional-multimodal data modeling and query research, assistive technology research based on the design and development of real-time assistive systems, and advanced information processing with neuroscience applications. This multidisciplinary research and educational center serves as a resource for the education of underrepresented minority students as well as a driving force to increase diversity in graduate education, especially at the Ph.D. level in computer science and engineering.
Director: Dr. Shu-Ching Cheng
Another of our research efforts is the Distributed Multimedia Information System Laboratory (DMIS). Its mission is to conduct leading-edge research in multimedia database systems, data mining, networking and wireless, GIS and Intelligent Transportation Systems. Other research areas of this effort include Multimedia Communications and Networking, Digital Library, 3D Animation, Distributed Computing and WWW.
Director: Dr. S. S. Iyengar
Dr. Ram Iyengar leads the Discovery lab and a team of CIS researchers who are currently performing advanced research in areas of intelligent systems, advanced security systems, autonomous mobile robots, and sensor networks, and smart grids. The Discovery Lab provides an infrastructure to promote collaborative research among universities and research organizations across the nation. In addition to addressing a comprehensive set of fundamental research topics, the Lab is pursuing commercialization, distinguishing itself from traditional research labs through its focus on translating research discoveries into technology transfer outcomes. At the same time, the laboratory provides students with the hands-on experiences they need to solve real-world challenges, develops student-led research opportunities, fosters students’ entrepreneurial skills, and trains a new generation of IT professionals who reflect the diversity of South Florida.
Director: Dr. Shu-Ching Chen & Prof. Shahin Vassigh
Integrated Computer Augmented Virtual Environment (I-CAVE) is an instructional and research visualization facility located on FIU’s Modesto Maidique Campus. This facility can be used for both undergraduate and graduate instruction in a variety of fields across the natural and social sciences, humanities, and professional programs.
The I-CAVE provides new opportunities for students and faculty for research, creative projects, learning exploration and data visualization. The benefit for users is tremendous as this virtual environment provides for 2-D and 3-D visualizations of scalable data, a completely immersive experience of a virtual space, and the capacity to explore new ideas, places or objects in a dynamic and interactive visual environment.
Principal Investigator and Director: Dr. Naphtali Rishe
One of our research efforts is the High-Performance Database Research Center (HPDRC). HPDRC conducts research on such theoretical and applied issues as Internet-distributed heterogeneous databases, database design methodologies, database design tools, information analysis, multi-media databases, database languages, data compression, spatial databases, and data visualization. The Center also designs specific database systems for highly complex applications.
Director: Ruogu Fang
Smart Medical Informatics Learning and Evaluation (SMILE) Group focuses on big medical data research, using scientific approaches to bridge data and medicine. Our effort spans from brain dynamics, medical image analysis, risk factor analysis, and computational neuron morphology.
Director: Rathindra (Babu) DasGupta, Alex Schwarzkopf, Rita Virginia Rodriguez
The National Science Foundation’s (NSF) FIU-FAU-Dubna Industry/University Cooperative Research Center for Advanced Knowledge Enablement (CAKE) was established to develop long-term partnerships among industry, academe, and government. The Center is supported primarily by industry center members, with NSF taking a supporting role in its development, evolution, and core funding. The Center’s mission is to conduct industry-relevant studies and deployments in the representation, management, storage, analysis, search and social aspects of large and complex data sets, with particular applications in geospatial location-based data, disaster mitigation, healthcare, transportation, and town planning.
Director: Niki Pissinou, Ph.D. and S. S. Iyengar, Ph.D.
Funded by by the State of Florida, industry and federal government, the Telecommunications and Information Technology Institute (IT2) is a unique hub for research, technology transfer and education at the graduate and undergraduate levels. With a sustainable growth model as the basis for its development, IT2’s portfolio now boasts cutting-edge research, active alliances with industry and unique academic programs. It is now a leading resource for education, training, research and technology development in the United States of America and abroad.
To fulfill the Institute’s vision of developing next-generation technologies, the efforts of the research groups are segmented into a few, somewhat complementary thrusts that naturally coincide with industrial needs. The fundamental science and technologies are distinctively unique; hence, different approaches are required within each group. IT2’s researchers have lead research efforts and development projects targeted at solving complex problems conducive to early identification of high impact solutions in a wide range of areas including security, privacy, wireless ad-hoc and sensor networks.
Director: Giri Narasimhan
The mission of this research group is to work on problems from the fields of Bioinformatics and Biotechnology. The group’s research projects includes Pattern Discovery in sequences and structures, micro-array data analysis, primer design, probe design, phylogenetic analysis, image processing, image analysis, and more. The group builds on tools and techniques from Algorithms, Data Mining, Computational Statistics, Neural Networks, and Image Processing.
Affective Social Computing Lab (ASCL)
Director: Christine L. Lisetti, Ph.D.
We are interested in research on affect, emotion, and personality at the intersection of research in Artificial Intelligence, Human-Computer Interaction, and Robotics. Emotional systems in humans influence important cognitive processes such as salience determination, focus and attention, priority determination, interruption in an emergency situation, memorization and recall, goal generation, goal attribution, categorization, and preference. All these processes are important for intelligent systems with limited resources evolving in an unpredictable environment, including artificial ones (W. Clancey; N. Frijda; M. Minsky, D. Norman, A. Ortony, R. Picard, D. Rumelhart, H. Simon; A. Sloman; R. Zajonc).
Systems Research Laboratory (SyLab)
Director: Raju Rangaswami
Our goal at the Systems Research Laboratory (SyLab) is to conduct research in the area of Operating Systems. While we are interested in all problems related to Systems, lately, we have been developing new capabilities for storage systems and virtualized data centers. Some of the capabilities that we have developed recently address energy, performance, and self-management for storage systems and resource isolation and performance guarantees within virtualized systems.
Knowledge Discovery Research Group (KDRG)
Director: Tao Li, Ph.D.
Our research explores two related topics on learning from data—how to efficiently discover useful patterns and how to effectively retrieve information. The interests lie broadly in data mining and machine learning studying both the algorithmic and application issues. The algorithmic aspects involve developing new scalable, efficient and interactive algorithms that can handle very large databases. The underlying techniques studied include clustering, classification, semi-supervised learning, similarity and temporal pattern discovery. The application issues focus on actual implementation and usage of the algorithms on a variety of real applications with different characteristics including bioinformatics, text mining, music information retrieval and event mining for computer system management.
Cognition, Narrative, and Culture Laboratory (Cognac Lab)
Director: Mark A. Finlayson, Ph.D.,
How does culture shape our understanding of the world? What makes stories so powerful? How can computation shed light on these questions? Culture surrounds us and affects our behavior and thoughts in ways large and small. Narratives are everywhere, and we know of no culture or society that does not use it as a fundamental form of communication for activities as diverse as explanation, education, and entertainment. The Cognac lab investigates these and related questions from a computational and cognitive point of view, and the unifying interest of researchers in the lab is the computational modeling of culture, narrative, language, and their interaction with cognition. For the purpose of scope we construe culture in a broad sense, as any set of shared knowledge structures that mold the behavior of a group of people. Researchers in the lab conduct inter-disciplinary research spanning artificial intelligence, computational linguistics, cognitive science, and the digital humanities, and use techniques drawn from machine learning, natural language processing, linguistic annotation, knowledge representation, computational inference to tackle key questions in this space, including: How is shared knowledge—commonsense and cultural—represented in language and narrative? How do people and how can machines extract this shared knowledge from data? And how do we apply these insights to achieve advances in machine intelligence, educational practice, health and medicine, social science theory, and the humanities? For recent work, current and former students, and more details generally, visit the lab homepage at http://cognac.cs.fiu.edu.