Ting Hu

Ph.D.
Department of Computer Science
Memorial University
St. John's, NL, A1B 3X5
Canada

Email: tingh A T mun. ca

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Supervisor

Professor Wolfgang Banzhaf

Ph.D. Thesis Topic

Evolvability and Rate of Evolution in Evolutionary Computation

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Research Interests

I obtained my Phd recently from Memorial University. My Phd research focused on the study of evolvability in Evolutioanry Computation systems. Principles and methods from molecular biology and evolutionary biology are investigated and expected to inspire new mechanisms in computational models. The computational models, therefore, can have evolvable genomes with high evolvability, and the computational evolution process is expected to be accelerated.

I am interested in evolution rate measure, molecular signaling, gene expression regulation, neutral network exploration, and epigenetic mechanisms.

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Publications

Journal Article

• T. Hu and W. Banzhaf (2010). Evolvability and Speed of Evolutionary Algorithms in the Light of Recent Developments in Biology.
  In Journal of Artificial Evolution and Applications, article ID:568375, 2010.
  
  
• T. Hu, S. Harding, and W. Banzhaf (2010). Variable Population Size and Evolution Acceleration: A Case Study with A Parallel Evolutionary Algorithm.
  In Genetic Programming and Evolvable Machines, 11(2):205-225, June 2010.
  
  

Conference Article

• T. Hu, Y. P. Chen, and W. Banzhaf (2010). WiMAX Network Planning Using Adaptive-Population-Size Genetic Algorithm.
  In 7th European Event on the Application of Nature-inspired Techniques for Telecommunication Networks and other Parallel and Distributed Systems (EvoCOMNET in EvoStar 10). LNCS vol. 6025.
  
  
• T. Hu and W. Banzhaf (2009). Neutrality and Variability: Two Sides of Evolvability in Linear Genetic Programming.
  In 11th Genetic and Evolutionary Computation Conference (GECCO 09).
  
  
• T. Hu, Y. P. Chen, W. Banzhaf and R. Benkoczi (2009). An Evolutionary Approach to Planning IEEE 802.16 Networks.
  In 11th Genetic and Evolutionary Computation Conference (GECCO 09) as a poster.
  
  
• G. He, Y. Li, Z. Shi, and T. Hu (2009). Intrinsic Evolution of Digital Circuits Using Evolutionary Algorithms. (Best Paper Award Nomination)
  In 2009 World Summit on Genetic and Evolutionary Computation (GEC Summit 09).
  
  
• T. Hu and W. Banzhaf (2009). The Role of Population Size in Rate of Evolution in Genetic Programming. (Best Paper Award Nomination)
  In 12th European Conference on Genetic Programming (EuroGP 09). LNCS vol. 5481.
  
  
• T. Hu, Y. P. Chen and W. Banzhaf (2008). A Genetic Algorithmic Approach to Planning IEEE 802.16 Networks.
  In 18th Annual Newfoundland Electrical and Computer Engineering Conference (NECEC 08).
  
  
• T. Hu and W. Banzhaf (2008). Nonsynonymous to Synonymous Substitution Ratio ka/ks: Measurement for Rate of Evolution in Evolutionary Computation.
  In 10th International Conference on Parallel Problem Solving from Nature (PPSN X). LNCS vol. 5199.
  
  
• T. Hu and W. Banzhaf (2008). Measuring Rate of Evolution in Genetic Programming Using Amino Acid to Synonymous Substitution Ratio ka/ks.
  In 10th Genetic and Evolutionary Computation Conference (GECCO 08) as a poster.
  
  
• B. Zheng and T. Hu (2007). A Novel Multi-objective Evolutionary Algorithm.
  In 7th International conference on Computational Science (ICCS 07). LNCS vol. 4490.
  
  
• B. Zheng, Y. Li, and T. Hu (2006). Vector Prediction Approach to Handle Dynamical Optimization Problems.
  In 6th International Conference on Simulated Evolution and Learning (SEAL 06). LNCS vol. 4247.
  
  
• W. Ding, T. Hu and H. Zhang (2005). Multi-Objective Optimization by a New Dynamical Evolutionary Algorithm Based on the Information Entropy.
  In 2nd International Conference on Neural Networks and Brain (ICNN&B 05).
  
  
• T. Hu, Y. Li and W. Ding (2005). A New Dynamical Evolutionary Algorithm Based on the Principle of Minimal Free Energy.
  In 1st International Symposium on Intelligence Computation and Applications (ISICA 05).
  
  

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Presentations

Invited Talk

• T. Hu (2009). Exploration of Neutrality and Variability in Evolutionary Computation.
  Hitchcock Medical Center, Dartmouth College, Hanover, NH, USA, September 10, 2009
  
  
• T. Hu (2009). A Measurement for Rate of Evolution and Its Applications in EC.
  State Key Laboratory of Software Engineering, Wuhan University, Wuhan, China, May 15, 2009
  
  
• T. Hu (2009). A Measurement for Rate of Evolution and Its Applications in EC.
  Honda Research Institute (HRI)-Europe, Offenbach, Germany, April 20, 2009
  
  

Conference Talk

• T. Hu (2009). Neutrality and Variability: Two Sides of Evolvability in Linear Genetic Programming.
  GECCO 09, Montreal, Canada, July 10, 2009
  
  
• T. Hu (2009). The Role of Population Size in Rate of Evolution in Genetic Programming.
  EuroGP 09, Tuebingen, Germany, April 15, 2009
  
  
• T. Hu (2008). A Genetic Algorithmic Approach to Planning IEEE 802.16 Networks.
  NECEC 08, St. John's, Canada, November 6, 2008
  
  
• T. Hu (2005). A New Dynamical Evolutionary Algorithm Based on the Principle of Minimal Free Energy.
  ISICA 05, Wuhan, China, April 21, 2005
  
  

Conference Poster

• T. Hu (2009). An Evolutionary Approach to Planning IEEE 802.16 Networks.
  GECCO 09, Montreal, Canada, July 9, 2009
  
  
• T. Hu (2008). Nonsynonymous to Synonymous Substitution Ratio ka/ks: Measurement for Rate of Evolution in Evolutionary Computation.
  PPSN X, Dortmund, Germany, September 15, 2008
  
  
• T. Hu (2008). Measuring Rate of Evolution in Genetic Programming Using Amino Acid to Synonymous Substitution Ratio ka/ks.
  GECCO 08, Atlanta, USA, July 15, 2008
  
  

Department Seminar

• T. Hu (2009). The Role of Population Size in Rate of EC Evolution.
  The 6th Graduate Student Research Forum, Department of Computer Science, Memorial University, St. John's, Canada, March 10, 2009
  
  
• T. Hu (2008). Evolvability and Acceleration in Evolutionary Computation.
  Phd Oral Comprehensive Exam (Phd Thesis Proposal), Department of Computer Science, Memorial University, St. John's, Canada, April 16, 2008
  
  
• T. Hu (2008). Measuring Rate of Evolution in Genetic Programming Using Amino Acid to Synonymous Substitution Ratio ka/ks.
  The 5th Graduate Student Research Forum, Department of Computer Science, Memorial University, St. John's, Canada, March 10, 2008
  
  
• T. Hu (2007). Evolvability and Speed of Evolution in Evolutionary Computation.
  The 4th Graduate Student Research Forum, Department of Computer Science, Memorial University, St. John's, Canada, March 19, 2007
  
  
• T. Hu (2006). A New Dynamical Evolutionary Algorithm Based on the Principle of Minimal Free Energy.
  The 3rd Graduate Student Research Forum, Department of Computer Science, Memorial University, St. John's, Canada, March 7, 2006
  
  

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Professional Services

• Program Committee Member. The Genetic and Evolutionary Computation Conference (GECCO 10).
  
  
• Program Committee Member. The Genetic and Evolutionary Computation Conference (GECCO 09).
  
  
• Session Chair. The European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics (EvoBio in EvoStar 09).
  
  
• Reviewer. The Journal of Neurocomputing, Springer, 2009.
  
  
• Reviewer. The International Conference on Intelligent Computing (ICIC 08).
  
  
• Reviewer. The Journal of Genetic Programming and Evolvable Machines, Springer, 2008.
  
  

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Education

• Ph.D., Department of Computer Science, Memorial University, St. John's, Canada
  September 2005 -- May 2010
  
  
• Master of Science, Department of Computer Science, Wuhan University, Wuhan, China
  September 2003 -- July 2005
  
  
• Bachelor of Science, Department of Mathematics and Statistics, Wuhan University, Wuhan, China
  September 1999 -- July 2003
  
  

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Links

• PPSN X Conference Gallary
  
  
• ECJ (A Java-based EC research system)
  
  
• Gnuplot Documentation
  
  
• GP Bibliography (Maintained by Dr. William B. Langdon)
  
  
• JAVA Documentation
  
  

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Beautiful Newfoundland!

(Nikon F60)

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Last updated: June 10, 2010