Background Info
ESTABLISHED IN 1986, THE SOFT COMPUTING RESEARCH GROUP (SCRG) FOCUSES ON RESEARCH AND EDUCATION IN MACHINE LEARNING AND SOFT COMPUTING. IN MACHINE LEARNING, WE STUDY AND DEVELOP ALGORITHMS THAT CAN LEARN FROM AND MAKE PREDICTIONS ON DATA TO MAKE DATA-DRIVEN PREDICTIONS OR DECISIONS. IN SOFT COMPUTING, WE DEAL WITH IMPRECISION, UNCERTAINTY, PARTIAL TRUTH, AND APPROXIMATION IN DATA TO ACHIEVE PRACTICAL, ROBUST AND LOW-COST SOLUTION TO PROBLEMS. OUR EXPERTISE INCLUDES BUT ARE NOT LIMITED TO NEURAL NETWORKS, SUPPORT VECTOR MACHINES, FUZZY LOGIC, BIO-INSPIRED AND EVOLUTIONARY COMPUTATION (GENETIC ALGORITHMS, DIFFERENTIAL EVOLUTION, PARTICLE SWARM OPTIMIZATION, ANT COLONY OPTIMIZATION, CUCKOO SEARCH, FIREFLY ALGORITHMS), AND PROBABILITY-BASED METHODS (BAYESIAN NETWORKS).