Artificial Intelligence (AI) seeks to understand the fundamental nature of intelligence and how to make computers exhibit intelligent behavior. Machine Learning addresses the problem of how to automatically learn concepts and behaviors from data. With seven faculty in AI and machine learning, UCF CS is highly active in these areas. Major research strengths include complex systems, data mining, diagnostics, evolutionary computation, intelligent simulation, knowledge representation, learning from observation of human performance, multi-agent systems, natural language processing, neural networks, neuroevolution, robotics, and social informatics.
The Evolutionary Complexity (EPlex) Research Group at the University of Central Florida abstracts the essential properties of natural evolution that made it possible to discover astronomically complex structures such as the human brain into computer algorithms for artificial intelligence and machine learning. If such properties can be abstracted effectively, then they can be leveraged to automate the discovery of large-scale neural networks (which is called neuroevolution), robot morphologies, building and vehicle architectures, art, and music. Lab director Kenneth Stanley is an inventor of the NEAT (NeuroEvolution of Augmenting Topologies) algorithm, and numerous subsequent high-impact technologies have been invented at EPlex: CPPNs (compositional pattern producing networks), HyperNEAT (Hypercube-based NEAT), novelty search, ES-HyperNEAT (evolvable structure HyperNEAT), adaptive HyperNEAT, Picbreeder, Galactic Arms Race, MaestroGenesis, Petalz, and many others.
Evolutionary Complexity Research Group
The Evolutionary Computation Lab at the University of Central Florida conducts research in the areas of Evolutionary Computation and Natural Computation. Evolutionary algorithms, including genetic algorithms, evolutionary programming, and evolutionary strategies, are search and learning tools which are based on principles from genetics and evolutionary biology and have been successfully applied to a wide range of problems. Natural computation focuses on computational mechanisms based on natural phenomena as well as complex adaptive systems that involve multiple interacting entities. The research in our lab includes both theoretical studies on how these algorithms work and real world applications.
Evolutionary Computation Lab
The Intelligent Agents Lab is dedicated to investigating social models within RAP systems (Robots, Agents, and People), with a particular emphasis on studying the behavior of people within games and simulation environments where people and agents can interact on an "equal footing". In these social-computational systems where autonomous agents must interact with larger groups of people, it is insufficient to model and infer the activity of one person; we must be able to understand larger social structures such as teams, groups, and crowds. To study these problems, IAL lab members conduct basic research on agent-based modeling, machine learning, and search; we aim to improve on the state of the art methods used in:
• agents for games and simulations
• human motion analysis and path prediction
• social simulations of groups and teams
• human-robot interaction
Intelligent Agents Lab
The MAPLE Lab mission is to enable machines to perceive and understand the real world, so they can intelligently and robustly perform in chanllenging tasks and scenarios.
• Machine Perception: data acquisition and processing
• Machine Learning: knowledge modeling and aggregation
The Natural Language Processing Group at the University of Central Florida focuses on innovative natural language technologies that improve human language understanding and processing. NLP enables computers to derive meaning from human language and generate natural language from a logical form.
Specifically, we conduct research in the areas of text summarization, language generation, social media analytics, natural language semantics, and machine Learning for NLP. Much of the technologies involve probabilistic models, machine learning, and deep learning as applied to large-scale text data.
Natural Language Processing Group
Ph.D., University of Paris, 1977
University of Nottingham, 2010
Ph.D., Computer science; Pennsylvania State University, 1982
Power electronics, solar energy conversion circuits and systems, dc-to-dc conversion, dynamic and control of power converters, power factor correction.
Ph.D., Electrical Engineering, University of Illinois at Chicago, 1990
Distributed systems, network agents, ubiquitous computing, and knowledge representation
Ph.D., Purdue University, 2000
Cognitive radio networks, dynamic spectrum access, economic issues in networks, applied game and auction theories, ad hoc and sensor networks, resource management and QoS provisioning, mobile video delivery, subjective video quality assessment (QoE).
Ph.D., University of Texas at Arlington, 2002
Ph.D., Texas A&M, 2009
Computer Architechture, Intelligent Systems, Evolvable Hardwaredemara@ece.ucf.edu
Parallel computation, combinatorial computing, graph theory, network optimization algorithms, parallel algorithms/parallel data structures
Ph.D., Northwestern University, 1965
Computational complexity design and analysis of algorithms, graph email@example.com
Expertise in Java programming and Cisco enterprise networking equipment.
Ed.S., Nova Southeastern University, 1998
University of Central Florida (2013)
Ultra-low Power Brain-inspired (Neuromorphic), Non-Boolean and Boolean Computing Using Emerging Nanoscale Devices, Device/ Circuit/ Architecture Co-design for Ultra-low Power, High Performance System
Purdue University (2015)
Computer vision, computer graphics visualization, signal image processing, bayesian estimation & decision theory, multimedia communications stochastic processes optimization theory
Ph.D., INRIA, France, 1996
Ph.D. Texas A&M University College Station, 2005
Areas of Specialty:
Big Data, Data Analytics, Deep Learning, Artificial Intelligence, Innovation, Simulation, and Agent-Based Models, Complex Systems, Computational Economics, Evolutionary Computation, and Computational Social Sciences.
Computer vision, machine learning, domain adaptation, transfer learning, object and human activity recognition
Ph.D., University of Southern California, 2015
Artificial intelligence, Machine Learning, knowledge-based systems, automated diagnostics, intelligent simulations, validation and verification of knowledge based systems
Ph.D., University of Pittsburgh, 1979
MS, University of Wisconsin
Distributed systems, computer networks, security protocols, modeling and simulation, and computer graphics
Ph.D., University of Texas, 1970
Computer architecture, parallel computer architecture, active memory and I/O systems, scalable cache coherence protocols, system-area networks, multiprocessor simulation methodology, and hardware/software co-design.
Ph.D., Stanford University, 1998
University of Central Florida
Data mining, especially frequent pattern mining across massive biological networks; integrative approaches to identifying phenotype specific pathways; DNA motif discovery and regulatory network interface; gene/protein function prediction; integration of e
Ph.D., University of Southern California, 2006
Multimedia databases, multimedia information systems, multimedia communications, Internet computing, wireless networks, parallel and distributed systems
Ph.D., University of Illinois at Urbana Champaign, 1987
Mixed and virtual reality models of parallel and distributed computation theory of computation
Ph.D., Pennsylvania State University, 1970
Ph.D., Carnegie Mellon University, 2010
Ph.D., Brown University, 2005
Programming and specification language design and semantics, formal methods (program specification and verification), aspect-oriented languages, object-oriented languages, distributed languages, type theory, programming methodology, software engineering,
Ph.D., Massachusetts Institute of Technology, 1988
Capella University (2014)
Temporal databases, operating systems architecture
Ph.D., University of Central Florida, 1994
Computational vision, active vision and mobile robotics, visual modeling for graphics
Ph.D., University of Toronto, 1993
Parallel and distributed systems, computational sciences, quantum information processing
Ph.D., Polytechnic Institute Bucharest, 1976
Ph.D. University of Minnesota Twin Cities, 2012
Computer Architecture support for irregular problems, Parallel processing, Quantum Computing
Ph.D., Central University of Venezuela, 2004
Ed.D., Arizona State University, 2007
University of Nevada, Reno, 1998
Database systems, object oriented systems
Ph.D., Ohio State University, 1984
Realistic image synthesis and display, and visualization
Ph.D., Birla Institute of Science and Technology, 1993
University of Illinois, Urbana-Champaign (2013)
Computer vision, gesture recognition, lipreading shape from shading, visual surveillance, visual motion, motion based recognition, optical flow
Ph.D. Computer Engineering, Wayne State University, 1986
Ph.D., University of Pennsylvania, 2002
The evolution of increasingly complex neural networks
Ph.D., University of Texas at Austin, 2004
multi-agent systems, machine learning, robotics
Ph.D., Carnegie Mellon University, 2007
Louisiana State University, 2014
Wireless ad hoc, sensor and vehicular networks, value of information and privacy in Internet of Things (IoT), big data in STEM education
Ph.D., University of Texas at Arlington, 2002
Computer Architecture, OS and High Performancejuwang@ece.ucf.edu
Research interests primarily focus on methods of natural computation, theory of coadaptive and coevolutionary computation, and application of coadaptive methods for multiagent learning.
George Mason University (2004)
Ph.D., University of Karlsruhe, 2003
Genetic algorithms, evolutionary computation visualization, machine learning
Ph.D., University of Michigan, 1995
Wireless circuit design for reliability, RF energy harvesting for biomedical applications, sensor interface circuits for internet of things, and secure integrated circuits using CMOS or emerging firstname.lastname@example.org
Computer Communication Networks, Wireless Systems, Optical Wireless, Spectrum Sharing, Network Economics and Architectures, and Network Managementmurat.email@example.com
Computational biology and bioinformatics
Ph.D., University of California, San Diego, 2007
Ph.D., University of Minnesota Twin Cities, 2015