Federal University of Technology - Paraná

 

Bioinformatics and Computational Intelligence Laboratory

 (LABIC)


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Current Research Projects

  • Deep Learning & Machine Learning:
    • Issues on data augmentation for deep learning architectures
    • Transfer learning issues
    • Image segmentation/clustering issues with application to crops, vehicles, and people
  • Computer Vision:
    • Soft biometrics for people recognition in surveillance videos
    • Anomaly detection in videos
    • Enriched semantic description of video contents in natural language
    • Image-based classification of skin cancer
    • Real-time car identification (make, model, color, licence) in multiple video streams
  • Bionformatics:
    • Computer simulation of protein folding and aggregation with GPU-based parallel Molecular Dynamics
    • Deep learning methods for the study of the aggregation of amyloidogenic proteins
  • Evolutionary Computation:
    • Genetic Programming for car image segmentation
  • Data Mining & Big Data:
    • Human behavior analysis from large-scale wi-fi data
    • Real-time sentiment analysis in massive distance learning data
    • Real-time re-identification of people in multiple video streams

 

Past Research Projects

  • Deep Learning & Machine Learning:
    • Deep learning methods for the protein secondary structure prediction problem
  • Computer Vision:
    • Methods for face recognition and face identification
    • Unsupervised learning for automatic image classification
  • Bionformatics:
    • Algorithms for the Protein Folding Problem
    • Deep learning methods for the protein secondary structure prediction problem
    • Evolutionary computation for the inference of gene regulatory networks
    • Cellular automata applications in bioinformatics
    • Computational tools for analysis of genomic sequences
    • Analysis of cancer-related mutations in genomic databases
    • Multiple sequence alignment in a parallel virtual machine
    • Biomolecular sequence alignment using computational intelligence techniques
    • Data-mining in biological datasets
    • Application of stochastic formal languages in bioinformatics
    • Hardware-based (FPGA) algorithms for multiple sequence alignment, protein folding and genomic analysis
  • Evolutionary Computation:
    • Evolutionary computation for the inference of gene regulatory networks
    • Gene expression programming applied to symbolic regression and data classification.
    • Operations research techniques for optimized power substations location
    • Logistic optimization of maintenance teams for power distribution networks
    • Genetic programming for data mining of medical datasets
    • Electronic circuits synthesis using genetic programming
    • Genetic algorithms for mobile robot path optimization
  • Data Mining & Big Data:
    • Mining evidences of cartels in public bids
    • Telematic services from the Origin-Destination matrix obtained with open data of the Curitiba´s public transportation network
    • Community detection in multilevel complex networks
    • Human behavior analysis from large-scale wi-fi data
  • Medical  & Health Informatics:
    • Intelligent tutor for learning mechanical ventilators manoeuvres
    • A multimedia system for training in kinesiology
    • Ontologies and artificial intelligence techniques for evaluation of patients with neurological diseases
    • Data mining in medical databases
    • A multimidia system for teaching support on the neurological evaluation of the newborn
    • Computer system for control and follow-up of clinical research protocols in oncology
    • A computational tool for distance learning using handheld computers – application in telemedicine
  • Reconfigurable Computation:
    • Gene detection with high-performance reconfigurable hardware
    • Cellular automata evolution in FPGA
    • FPGA-based hardware accelerator for bioinformatics problems

     

     

Last update:  10/30/19