Olac Fuentes - Research Interests

I am interested in Machine Learning and its applications to Computer Vision, Bioinformatics, Scientific Data Analysis, Robotics, and Natural Language Processing.

I lead the Vision and Learning Laboratory (VL2) at UTEP and I am also affiliated with the Laboratory for Industrial Metrology and Automation (LIMA) and with the Interactive Systems Group (ISG).

Publications

Journal Papers

  1. Trilce Estrada, Olac Fuentes and Michela Taufer, A Distributed Evolutionary Method to Design Scheduling Policies for Volunteer Computing, ACM SIGMETRICS PER (Performance Evaluation Review) (to appear).
  2. Luis Malagón-Borja and Olac Fuentes, Object Detection using Image Reconstruction with PCA, Image and Vision Computing, Volume 27(1-2), pp 2-9, January 2009.
  3. Steven Gutstein, Olac Fuentes and Eric Freudenthal, Knowledge Transfer in Deep Convolutional Neural Nets, International Journal on Artificial Intelligence Tools (IJAIT), Volume 17, Number 3, pp. 555-567, June 2008.
  4. Thamar Solorio, Olac Fuentes, Roberto Terlevich and Elena Terlevich, An Active Instance-Based Machine Learning Method for Stellar Population Studies, Monthly Notices of the Royal Astronomical Society, Vol. 363(2), October 2005.
  5. Jorge de la Calleja and Olac Fuentes, Machine Learning and Image Analysis for Morphological Galaxy Classification, Monthly Notices of the Royal Astronomical Society, Vol. 349, pp. 87-93, 2004.
  6. Carmen Martínez and Olac Fuentes, Face Recognition using Unlabeled Data, Computación y Sistemas - Iberoamerican Journal of Computer Science Research, Vol. 7, No.2, pp 123-129, 2003.
  7. Federico Ramírez and Olac Fuentes, A Hybrid Algorithm for Spectral Analysis, Experimental Astronomy, Vol. 14, No. 3, pp. 129-146, 2002.
  8. Sergio Vázquez y Montiel, Juan Jaime Sánchez Escobar, and Olac Fuentes, Obtaining the phase of an interferogram using an evolution strategy, Part I. Applied Optics, Vol. 41, No.17, pp. 3448-3452, June 2002.
  9. Federico Ramírez, Olac Fuentes, and Ravi Gulati, Prediction of Stellar Atmospheric Parameters Using Instance-based Machine Learning and Evolutionary Algorithms, Experimental Astronomy, Vol. 12, No. 3. pp. 163-178, 2001.
  10. Olac Fuentes Automatic Determination of Stellar Atmospheric Parameters Using Neural Networks and Instance-Based Learning. Experimental Astronomy, Vol. 12, No. 1, pp. 21-31, 2001.
  11. Olac Fuentes and Ravi K. Gulati, Predicition of Stellar Atmospheric Parameters from Spectra, Spectral Indices and Spectral Lines Using Machine Learning .Revista Mexicana de Astronomia y Astrofisica, volume 10, March 2001.
  12. Olac Fuentes and Randal C. Nelson, Learning Dextrous Manipulation Strategies for Multifingered Robot Hands Using the Evolution Strategy, .Machine Learning, Vol. 31, 223-237, 1998,
  13. Olac Fuentes and Randal C. Nelson, Learning Dextrous Manipulation Strategies for Multifingered Robot Hands Using the Evolution Strategy, Autonomous Robots, Vol. 5, 395-405, 1998.
  14. Rajesh P. N. Rao and Olac Fuentes, Hierarchical Learning of Navigational Behaviors in an Autonomous Robot using a Predictive Sparse Distributed Memory, Machine Learning, Vol. 31, 87-113, 1998.
  15. Rajesh P. N. Rao and Olac Fuentes, Hierarchical Learning of Navigational Behaviors in an Autonomous Robot using a Predictive Sparse Distributed Memory, Autonomous Robots, Vol. 5, 297-316, 1998.
  16. Olac Fuentes, Rajesh P. N. Rao, and Michael Van Wie, Hierarchical Learning of Reactive Behaviors in an Autonomous Mobile Robot. Computación y Sistemas - Iberoamerican Journal of Computer Science Research, Volume 1, number 2, 1997.
  17. Vladik Kreinovich, Chris Quintana and Olac Fuentes, Genetic Algorithms: What Fitness Scaling is Optimal?. Cybernetics and Systems. March 1993.

Refereed Conference Papers

  1. Trilce Estrada, Olac Fuentes and Michela Taufer, A Distributed Evolutionary Method to Design Scheduling Policies for Volunteer Computing, Proceedings of Computing Frontiers 2008, Ischia, Italy, May 2008.
  2. Jorge de la Calleja, Olac Fuentes and Jesús González, Selecting minority examples from misclassified data for over-sampling, Proceedings of FLAIRS-08 Conference, Coconut Grove, Florida, May 2008.
  3. Steven Gutstein, Olac Fuentes and Eric Freudenthal, The Utility of Knowledge Transfer for Noisy Data, Proceedings of FLAIRS-08 Conference, Coconut Grove, Florida, May 2008.
  4. Juan Carlos Gómez and Olac Fuentes, Using Evolution Strategies for Automatic Extraction of Parameters for Stellar Population Synthesis of Galaxy Spectra from SDSS, 2007 IEEE Congress on Evolutionary Computation, Singapore, September 2007.
  5. Luis David López and Olac Fuentes, Color-Based Road Sign Detection and Tracking, International Conference on Image Analysis and Recognition (ICIAR), Montreal, CA, August 2007.
  6. Juan Carlos Gómez and Olac Fuentes, A Hybrid Algorithm Based on Evolution Strategies and Instance-Based Learning Applied to Two-dimensional Fitting of Brightness Profiles in Galaxy Images, International Conference on Machine Learning and Data Mining (MLDM 2007), Leipzig, Germany, July 2007.
  7. Jorge de la Calleja and Olac Fuentes, Learning from Imbalanced Datasets using a Distance-based Over-sampling Method, International Conference on Machine Learning and Data Mining (MLDM 2007), Leipzig, Germany, July 2007.
  8. Juan Carlos Gómez and Olac Fuentes, Using Evolution Strategies for Automatic Extraction of Parameters for Stellar Population Synthesis of Galaxy Spectra from SDSS, Genetic and Evolutionary Computation Conference (GECCO 2007), London, England, July 2007 (Poster presentation).
  9. Steven Gutstein, Olac Fuentes and Eric Freudenthal, Knowledge Transfer in Deep Convolutional Neural Nets, Proceedings of FLAIRS-07 Conference, Key West, Florida, May 2007.
  10. Jorge de la Calleja and Olac Fuentes, A Distance-based Over-sampling Method for Dealing with Imbalanced Data Sets, Proceedings of FLAIRS-07 Conference, Key West, Florida, May 2007 (Poster presentation).
  11. Olac Fuentes, David Vera and Thamar Solorio, A Filter-Based Approach to Detect End-of-Utterances from Prosody in Dialog Systems, Proceedings of the The Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT 2007), Rochester, NY, April 2007.
  12. Jorge de la Calleja and Olac Fuentes, Automated Star/Galaxy Discrimination in Multispectral Wide-Field Images, Proceedings of the Second International Conference on Computer Vision Theory and Applications (VISAPP), Barcelona, Spain, March 2007..
  13. Thamar Solorio, Olac Fuentes, Nigel Ward and Yaffa Al Bayyari, Prosodic Feature Generation for Back-channel Prediction, Proceedings of the Ninth International Conference on Spoken Language Processing (Interspeech 2006), Pittsburgh, PA, September 2006.
  14. H. Jair Escalante and Olac Fuentes, Analysis of Galactic Spectra Using Noise-Aware Learning Algorithms, Proceedings of FLAIRS-06 Conference, Melbourne Beach, Florida, May 2006.
  15. Jorge de la Calleja and Olac Fuentes, Automated Classification of Astronomical Objects in Multi-spectral Wide-Field Images, Proceedings of FLAIRS-06 Conference, Melbourne Beach, Florida, May 2006. (Received best poster award).
  16. José Martínez and Olac Fuentes, Using C4.5 as a variable Selection Criterion in Classification Tasks, IASTED International Conference on Artificial Intelligence and Soft-Computing, Benidorm, Spain, September 2005.
  17. Juan Carlos Gómez, Olac Fuentes and Ivanio Puerari, Two-Dimensional Fitting of Brightness Profiles in Galaxy Images with a Hybrid Algorithm, Proceedings of the Ninth International Conference on Knowledge-Based Intelligent Information & Engineering Systems (KES), Melbourne Australia, September 2005. Lecture Notes in Artificial Intelligence 3682.
  18. Trilce Estrada-Piedra and Olac Fuentes, Identification of Stellar Populations in Galactic Spectra using the Hierarchical Decision Ensemble, Proceedings of the 18th International FLAIRS Conference, Clearwater Beach, Florida, May 2005.
  19. Luis Malagón-Borja and Olac Fuentes, An Object Detection System using Image Reconstruction with PCA, Proceedings of the 2nd Canadian Conference on Computer and Robot Vision, Victoria, B.C., Canada, May 2005.
  20. Geovany A. Ramírez and Olac Fuentes, Face Detection using Combinations of Classifiers, Proceedings of the 2nd Canadian Conference on Computer and Robot Vision, Victoria, B.C., Canada, May 2005.
  21. Olac Fuentes, Thamar Solorio, Roberto Terlevich and Elena Terlevich, Analysis of Galactic Spectra Using Active Instance-Based Learning and Domain Knowledge, Proceedings of IX Iberoamerican Conference on Artificial Intelligence (IBERAMIA), Puebla, Mexico, November 2004. Lecture Notes in Artificial Intelligence 3315.
  22. Antonio Salim, Olac Fuentes and Angélica Muñoz, Development of Local Perception-Based Behaviors for a Robotic Soccer Player, Proceedings of IX Iberoamerican Conference on Artificial Intelligence (IBERAMIA), Puebla, Mexico, November 2004. Lecture Notes in Artificial Intelligence 3315.
  23. Juan Carlos Gómez, Olac Fuentes,  Lia Athannasoula and Albert Bosma, Using Evolution Strategies to Find a Dynamical Model of the M81 Triplet, Proceedings of the Eight International Conference on Knowledge-Based Intelligent Information & Engineering Systems (KES),Wellington, New Zealand, September 2004. Lecture Notes in Artificial Intelligence 3215.
  24. Luis Álvarez, Olac Fuentes, and Roberto Terlevich, Extracting Stellar Population Parameters of Galaxies from Photometric Data Using Evolution Strategies and Locally Weighted Linear Regression. Proceedings of the Eight International Conference on Knowledge-Based Intelligent Information & Engineering Systems (KES), Wellington, New Zealand, September 2004. Lecture Notes in Artificial Intelligence 3215.
  25. Jorge de la Calleja and Olac Fuentes, Automated Classification of Galaxy Images, Proceedings of the Eight International Conference on Knowledge-Based Intelligent Information & Engineering Systems (KES), Wellington, New Zealand, September 2004. Lecture Notes in Artificial Intelligence 3215.
  26. Antonio Salim, Olac Fuentes, and Angélica Muñoz, Development of Local Vision-Based Behaviors for a Robotic Soccer Player, Proceedings Mexican International Conference in Computer Science, Colima, México, Sept. 2004.
  27. Olac Fuentes and Thamar Solorio, An Optimization Algorithm Based on Active and Instance-Based Learning, Proceedings of 2004 Mexican International Conference on Artificial Intelligence (MICAI), Mexico City, Mexico, Lecture Notes in Artificial Intelligence 2972, April 2004.
  28. Vittorio Zanella and Olac Fuentes, An Approach to Automatic Model-Based Morphing of Face Images in Frontal View, Proceedings of 2004 Mexican International Conference on Artificial Intelligence (MICAI), Mexico City, Mexico, Lecture Notes in Artificial Intelligence 2972, April 2004.
  29. Carmen Martínez and Olac Fuentes, Face Recognition using Unlabeled Data,  Proceedings of CIC-2003, Mexico City, Mexico, Oct. 2003.
  30. Vittorio Zanella and Olac Fuentes, Model-Based Automatic Morphing of Face Images in Frontal View, IASTED International Conference on Visualization, Imaging and Image Processing, Benalmádena, Spain, Sept. 2003. pp. 55-60.
  31. Jorge de la Calleja, Olac Fuentes and Aurelio López-López, Content-Based Retrieval of Astronomical Images, IASTED International Conference on Artificial Intelligence and Applications, Benalmádena, Spain, Sept. 2003.
  32. Olac Fuentes and Thamar Solorio, Interferogram Analysis using Active Instance-Based Learning, IASTED International Conference on Artificial Intelligence and Applications, Benalmádena, Spain, Sept. 2003.
  33. Geovany Ramírez, Vittorio Zanella and Olac Fuentes, Heuristic-Based Face Detection, IASTED International Conference on Computer Graphics and Imaging, Honolulu, Hawaii, July 2003.
  34. Vittorio Zanella-Palacios and Olac Fuentes, Evolution Strategies for Automatic Image Morphing, Proceedings of International Conference on Computational Intelligence for Modelling Control and Automation, Vienna, Austria, Feb. 2003.
  35. Jorge de la Calleja y Olac Fuentes, Image-Based Morphological Classification of Galaxies Using Ensembles of Classifiers, Proceedings of International Computing Congress, Mexico City, Mexico, November 2002.
  36. Thamar Solorio and Olac Fuentes, Improving Classification Accuracy of Large Test Sets Using the Ordered Classification Algorithm, Proceedings of VII I Iberoamerican Conference on Artificial Intelligence (IBERAMIA), Seville, Spain. Lecture Notes in Artificial Intelligence 2527, pp. 70-79. November 2002.
  37. Federico Ramírez and Olac Fuentes, Spectral Analysis Using Evolution Strategies, IASTED International Conference on Artificial Intelligence and Soft Computing, Banff, Alberta, Canada, July 2002.
  38. Thamar Solorio and Olac Fuentes, Taking advantage of unlabeled data with the ordered classification algorithm , IASTED International Conference on Artificial Intelligence and Soft Computing, Banff, Alberta, Canada, July 2002.
  39. Federico Ramírez and Olac Fuentes, Prediction of Stellar Atmospheric Parameters Using Instance-based Machine Learning and Evolutionary Algorithms. Proceedings of the IASTED International Conference on Artificial Intelligence and Applications (AIA2001), Marbella, Spain, Sept. 2001.
  40. Thamar Solorio and Olac Fuentes, Improving Classifier Accuracy using Unlabeled Data. Proceedings of the IASTED International Conference on Artificial Intelligence and Applications (AIA2001), Marbella, Spain, Sept. 2001.
  41. Olac Fuentes, Neural Networks and Instance-Based Learning for the Prediction of Stellar Atmospheric Parameters . Proceedings of the IASTED International Conference on Artificial Intelligence and Soft Computing (ASC2001), Cancun, Q.R., May 2001.
  42. Olac Fuentes and Randal C. Nelson, Learning Dextrous Manipulation Skills Using the Evolution Strategy. Proceedings of the 1997 IEEE International Conference on Robotics and Automation, Albuquerque, New Mexico, April 1997.
  43. Martin Jägersand, Olac Fuentes and Randal C. Nelson, Experimental Evaluation of Uncalibrated Visual Servoing for Precision Manipulation. Proceedings of the 1997 IEEE International Conference on Robotics and Automation, Albuquerque, New Mexico, April 1997.
  44. Olac Fuentes and Randal C. Nelson, Learning Dextrous Manipulation Skills Using Multisensory Information. Proceedings of the 1996 IEEE/SICE/RSJ/ International Conference on Multisensor Fusion and Integration for Intelligent Systems, Washington, D.C., December 1996.
  45. Olac Fuentes and Randal C. Nelson, Experiments on Dextrous Manipulation without Prior Object Models. Proceedings of the 1996 IEEE International Symposium on Intelligent Control, Dearborn, Michigan, September 1996.
  46. Rajesh P. N. Rao and Olac Fuentes, Learning Navigational Behaviors using a Predictive Sparse Distributed Memory. From Animals to Animats: Proceedings of the Fourth International Conference on Simulation of Adaptive Behavior, Cape Cod, Massachusetts, September 1996.
  47. Martin Jägersand, Olac Fuentes and Randal C. Nelson, Acquiring Visual-Motor Models for Precision Manipulation with Robot Hands. Proceedings of the Fourth European Conference on Computer Vision, Lecture Notes in Computer Science 1065, April 1996.
  48. Olac Fuentes and Randal C. Nelson, The Virtual Tool Approach to Dextrous Telemanipulation. Proceedings of the 1996 IEEE International Conference on Robotics and Automation, Minneapolis, Minnesota, April 1996.
  49. Olac Fuentes, Rajesh P. N. Rao, and Michael Van Wie, Hierarchical Learning of Reactive Behaviors in an Autonomous Mobile Robot. Proceedings of the 1995 IEEE International Conference on Systems, Man and Cybernetics, Vancouver, B. C., Canada, October, 1995.
  50. Rajesh P. N. Rao and Olac Fuentes, Perceptual Homing by an Autonomous Mobile Robot using Sparse Self-Organizing Sensory-Motor Maps. Proceedings of the World Congress on Neural Networks '95, Washington, D.C., July, 1995.
  51. O. Sirisaengtaksin, L. O. Fuentes, and V. Kreinovich, Non-traditional Neural Networks that solve one more intractable problem: propositional satisfiability, Proceedings of the First International Conference on Neural, Parallel, and Scientific Computations, Atlanta, GA, May 1995. 
  52. Vladik Kreinovich, Robert Lea, Olac Fuentes, and Anatole Lockshin, Fuzzy Control is Often Better Than Manual Control of the Very Experts Whose Knowledge It Uses: an Explanation. Proceedings of the 1992 IEEE International Conference on Tools with Artificial Intelligence. Arlington, Virginia, November 1992.
  53. V. Kreinovich, C. Quintana, R. Lea, O. Fuentes, S. Kumar, I. Borisheva and L. Reznik, What Non-linearity to Choose? Mathematical Foundations of Fuzzy Control. Proceedings of the 1992 International Fuzzy Systems and Intelligent Control Conference. Louisville, KY, March 1992. pp. 349-412.
  54. Olac Fuentes and Vladik Kreinovich, Simulation of Chemical Kinetics: a Promising Approach to Inference Engines.  Proceedings of the First World Congress on Expert Systems, Orlando, Florida, December 1991.

Workshop and Other Conference Papers

  1. Geovany A. Ramírez and Olac Fuentes, Multi-pose Face Detection with Asymmetric Haar Features, 2008 IEEE Workshop on Applications of Computer Vision (WACV), Copper Mountain, Colorado, January 2008.
  2. Juan Carlos Gómez and Olac Fuentes, Extracting Parameters for Stellar Populations Synthesis from SDSS Galaxy Spectra using Evolution Strategies, The Virtual Observatory in Action: New Science, New Technology, and Next Generation Facilities, 26th meeting of the IAU, Special Session 3, Prague, Czech Republic, August, 2006.
  3. Juan Carlos Gómez and Olac Fuentes, Using a Novel Hybrid Algorithm for Two-Dimensional Model of Brightness Profiles in Elliptical and Spiral Galaxy Images , Astronomical Data Analysis Software and Systems XV, San Lorenzo de El Escorial, Spain, 2006.
  4. H. Jair Escalante and Olac Fuentes, Noise Elimination with a Re-Sampling Algorithm, Proceedings of First Iberoamerican Workshop on Machine Learning for Scientific Data Analysis, November 2004, pp.307-316, Puebla, Mexico.
  5. Trilce Estrada-Piedra and Olac Fuentes, Identification of Stellar Populations in Galactic Spectra Using the Hierarchical Decision Ensemble, Proceedings of First Iberoamerican Workshop on Machine Learning for Scientific Data Analysis, November 2004, pp. 371-378, Puebla, Mexico.
  6. Elena Terlevich, Roberto Terlevich, Juan Pablo Torres-Papaqui, Trilce Estrada-Piedra, Olac Fuentes, Thamar Solorio and Sandor Bressan, Computer Science approach to the stellar fabric of violent starforming regions in AGN. The Interplay among Black Holes, Stars and ISM in Galactic Nuclei, Proceedings of IAU Symposium, No. 222. Edited by T. Storchi-Bergmann, L.C. Ho, and Henrique R. Schmitt. Cambridge, UK: Cambridge University Press, p.545-548, 2004.
  7. Thamar Solorio, Olac Fuentes, Roberto Terlevich, Elena Terlevich and Alessandro Bressan, Automated determination of stellar population parameters in galaxies using active instance-based learning, Astronomical Data Analysis Software and Systems XIII, Strasbourg, France, Oct. 2003.
  8. Juan Carlos Gómez, E. Athannasoula  and Olac Fuentes, Determination of initial conditions of M81 triplet using Evolution Strategies, Astronomical Data Analysis Software and Systems XIII, Strasbourg, France, Oct. 2003.
  9. Trilce Estrada-Piedra, Juan P. Torres-Papaqui, Roberto Terlevich, Olac Fuentes and Elena Terlevich, Age determination for the nuclear stellar population of Active Galactic Nuclei (AGN) using Locally Weighted Regression (LWR), Astronomical Data Analysis Software and Systems XIII, Strasbourg, France, Oct. 2003.
  10. Olac Fuentes, Finding Errors in Astronomical Catalogs Using Machine Learning, Astronomical Data Analysis Software and Systems IX, Victoria B.C., Canada, Oct. 2001.
  11. Juan Carlos Gómez, Olac Fuentes, and Ivanio Puerari, Determination of orbital parameters of interacting galaxies using Evolution Strategies, Astronomical Data Analysis Software and Systems IX, Victoria B.C., Canada, Oct. 2001.
  12. Thamar Solorio and Olac Fuentes, Using unlabeled data to improve the automated prediction of stellar atmospheric parameters, Astronomical Data Analysis Software and Systems IX, Victoria B.C., Canada, Oct. 2001.
  13. S. Vázquez-Montiel, O. Fuentes, and J. Sánchez-Escobar, Obtaining the phase of a noisy synthetic interferogram using an evolution strategy. Proceedings of OPTILAS 2001, Buenos Aires, Argentina, July 2001.
  14. Olac Fuentes and Ravi K. Gulati, Prediction of Stellar Atmospheric Parameters using Neural Networks and Instance-based Learning. Advances on Artificial Perception and Robotics Workshop. Guanajuato, Mexico, October 2000.
  15. Olac Fuentes and Ravi K. Gulati, Prediction of Stellar Atmospheric Parameters from Spectra, Spectral Indices and Spectral Lines using Machine Learning. Proceedings of the Seventh Texas-Mexico Conference on Astrophysics, Austin, TX., April 2000.
  16. Olac Fuentes and Ravi K. Gulati, Instance-Based Machine Learning Methods for the Prediction of Stellar Atmospheric Parameters. Astronomical Data Analysis Software & Systems IX, Waikoloa, Hawaii, October 1999.
  17. Olac Fuentes and Vladik Kreinovich, Towards Intelligent Virtual Environment for Teaching Telemanipulation Operators: Virtual Tool Approach and its Interval-Based Justification, Proceedings of the Second International Workshop on Intelligent Virtual Environments, Xalapa, Ver. Mexico, Sept. 1998.
  18. Randal C. Nelson, Martin Jägersand and Olac Fuentes , Virtual Tools: A Framework for Simplifying Sensory-Motor Control in Complex Robotic Systems, Proceedings of the '95 Vision for Robots Workshop, Pittsburgh, PA. August 1995.

Papers in Spanish

  1. Alberto Téllez Valero, Manuel Montes y Gómez, Olac Fuentes y Luis Villaseñor Pineda, Clasificación Automática de Textos de Desastres Naturales en México, Décimo Congreso Internacional de Investigación en Ciencias Computacionales, Oaxtepec, México, Oct. 2003.
  2. Federico Ramírez y Olac Fuentes, Optimización de las Funciones de Membresía de un Control Lógico Difuso de Iluminación Mediante Algoritmos Genéticos. 11 Congreso Internacional de Ingeniería Electrónica, Comunicaciones y Computadoras (CONIELECOMP). Universidad de las Américas, Cholula, Puebla, Febrero 2001.
  3. Federico Ramírez, Olac Fuentes and Ravi K. Gulati, Prediccion de Parametros de Atmosferas Estelares Mediante Algoritmos Geneticos y Aprendizaje Basado en Ejemplos. Conferencia Internacional Mexicana de Inteligencia Artificial. Acapulco, Gro., Mexico, April 2000.
  4. Armando Carrillo and Olac Fuentes, Clasificacion de Textos en Español Utilizando el Clasificador Simple de Bayes y Reglas Gramaticales. Conferencia Internacional Mexicana de Inteligencia Artificial. Acapulco, Gro., Mexico, April 2000.
  5. Federico Ramírez, Olac Fuentes and Ravi K. Gulati, Algoritmos Geneticos para el Analisis Automatico de Informacion Astronomica. Memorias del Congreso Internacional de Computación CIC 99, pp. 68-77. Mexico D.F., November 1999.
  6. Guillermo Sánchez, Manuel Lazo y Olac Fuentes, Algoritmo Genético para Calcular Testores Típicos de Costo Mínimo. Memorias del Cuarto Simposio Iberoamericano de Reconocimiento de Patrones, La Habana, Cuba, March 1999.

Technical Reports

  1. Olac Fuentes and Randal C. Nelson, Learning Dextrous Manipulation Skills for Multifingered Robot Hands, Technical Report 613, Computer Science Department, University of Rochester, May 1996; revised October 1996.
  2. Olac Fuentes and Randal C. Nelson, Experiments on Dextrous Manipulation without Prior Object Models., Technical Report 606, Computer Science Department, University of Rochester, February 1996.
  3. O. Fuentes, J. Karlsson, W. Meira Jr., R. Rao, T. Riopka, J. Rosca, R. Sarukkai, M. vanWie, M. Zaki, T. Becker, R. Frank, B. Miller, C. Brown, Mobile Robotics 1994 , Technical Report 588, Computer Science Department, University of Rochester, June 1995.
  4. Randal C. Nelson, Martin Jägersand and Olac Fuentes, Virtual Tools: A Framework for Simplifying Sensory-Motor Control in Complex Robotic Systems. Technical Report 576, Computer Science Department, University of Rochester, March 1995.
  5. Olac Fuentes and Randal C. Nelson, Morphing Hands and Virtual Tools (or What Good is an Extra Degree of Freedom?), Technical Report 551, Computer Science Department, University of Rochester, December 1994.
  6. Olac Fuentes, Hilcea F. Marengoni and Randal C. Nelson, Vision-Based Planning and Execution of Precision Grasps. Technical Report 546, Computer Science Department, University of Rochester, December 1994.

Student Supervision

Ph.D. Theses

  1. Juan Carlos Gómez-Carranza, Inverse Active machine Learning in Optimization Processes with Application in Astronomy, Ph.D. in Computer Science, INAOE, February 2007.
  2. Vittorio Zanella-Palacios, Automated Morphing of Face Images, Ph.D. in Computer Science, INAOE, January 2005.
  3. José Federico Ramírez-Cruz, Instance and Feature Selection for Instance-Based machine Learning Using Evolutionary Algorithms, Ph.D. in Computer Science, INAOE, October 2003.
  4. Juan Jaime Sánchez-Escobar, Obtención de la Fase de un Interferograma Empleando Estrategias Evolutivas, Ph.D. in Optics, INAOE, November 2002. (Co-supervised with Sergio Vázquez).

M.S. Theses

  1. Geovany Ramírez, Detección de Rostros con Aprendizaje Autmático, M.S in Computer Science, INAOE, March 2006.
  2. Hugo Jair Escalante, Noise-aware Machine Learning Algorithms, M.S in Computer Science, INAOE, February 2006.
  3. Topilzin Flores Lucero, Stereo Vison Using Evolutionary Algorithms, M.S in Computer Science, INAOE, February 2005.
  4. José Luis Saul Malagón Borja, Pedestrian Detection using Image Reconstruction with PCA, M.S in Computer Science, INAOE, February 2005.
  5. Luis Álvarez Ochoa, Extraccióon de Parámetros de Poblaciones Estelares de Galaxias a Partir de Datos Fotométricos Usando Estrategias Evolutivas, M.S in Computer Science, INAOE, October 2004 (co-supervised with Roberto Terlevich).
  6. Trilce Procyón Estrada Piedra, Identificación Automática de Poblaciones Estelares a Partir de Espectros Galácticos, M.S in Computer Science, INAOE, October 2004.
  7. Antonio Salim Maza, Development of Local Vision-based Behaviors for a Robotic Soccer Player, M.S in Computer Science, INAOE, September 2004 (co-supervised with Angélica Muñoz).
  8. José Edgar Lara Ramírez, Robot Navigation and Map Construction Using Machine Learning and Probabilistic Models, M.S in Computer Science, INAOE, February 2004.
  9. Carmen Carlota Martínez Gil, Face Recognition using Template-based Methods and Unlabeled Data, M.S in Computer Science, INAOE, January 2004.
  10. Jorge de la Calleja Mora, Classification of Galaxy Images using Machine Learning and Image Analysis, M.S in Computer Science, INAOE, September 2003.
  11. María Teresa Orozco-Aguilera, Creación de Atributos Relevantes para la Predicción de Parámetros de Atmósferas Estelares, M.S. in Astrophysics, INAOE, December 2002.
  12. Oscar Manuel Martínez-Lazalde, Razonamiento con conocimiento incompleto y su aplicación al juego del Dominó, M.S in Computer Science, INAOE, December 2002.
  13. Thamar Ivette Solorio Martínez, Using Unlabeled Data to Improve Classifier Accuracy, M.S in Computer Science, INAOE, August 2002.
  14. Juan Carlos Gómez-Carranza, Determinación de Parámetros Orbitales de Galaxias Interactuantes Utilizando Estrategias Evolutivas, M.S. in Astrophysics, INAOE, February 2002. (Co-supervised with Ivanio Puerari).
  15. Darío César Peregrina-Albores, Seguimiento de Objetos por Medio de Visión Activa, M.S in Computer Science, INAOE, May 2002. (Co-supervised with Leopoldo Altamirano and Miguel Arias).

B.S. Theses

  1. Jorge de la Calleja Mora, B.S in Computer Science, Clasificación Morfológica de Galaxias usando Aprendizaje Automático, Benemérita Universidad Autónoma de Puebla, August 2002.
  2. Carmen Carlota Martínez Gil, Comparación de Clasificadores Aplicando la Técnica de Eigenfaces y Realizando Ensambles para la Clasificación de Caras, B.S in Computer Science, Benemérita Universidad Autónoma de Puebla, July 2002.
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