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Dr Rohitash Chandra

 Dr. Rohitash Chandra, PhD, MSc, BSc, MIEEE

Dr. Rohitash Chandra is a Lecturer in Computer Science at the School of Computing, Information and Mathematical Sciences of University of the South Pacific. He holds a PhD in Computer Science from Victoria University of Wellington, MSc in Computer Science from the University of Fiji and BSc from the University of the South Pacific.

His research interests in general encircle the methodologies and applications of Artificial Intelligence. More specifically, he is interested in Neural and Evolutionary Computation methods such as Feedforward and Recurrent Networks, Genetic Algorithms, Cooperative Coevolution and Neuro-evolution with applications in Pattern Classification, Time Series Prediction, Control , Robot Kinematics and Environmental Informatics. He is also interested in Medical and Health Informatics, and Computational Biology research with focus on Metabolic Flux Analysis. He is the Founder and Executive Director of Software Foundation Fiji which is a registered non-profit organization that promotes the development of software and technology in Fiji. He has published 26 papers from his research in leading international journals and conference proceedings.

Apart from his interest in science, he is actively involved in literature and has been the editor of the Blue Fog Journal. His interest is also in Philosophy of Religion. He writes poetry and is the author of “A Hot Pot of Roasted Poems” that was released in 2007 in Fiji.  His third poetry collection, ‘‘Being at Home’’ will be released in 2013.

Education

1.    PhD in Computer Science, Victoria University of Wellington, 2012. Thesis title: Problem Decomposition and Adaptation in Cooperative Neuro-evolution.

2.    Master of Science in Computing Science, University for Fiji, 2009. Thesis title: Modelling of Deterministic, Fuzzy and Probabilistic Dynamical Systems.

3.    Bachelor of Science (Computer Science and Engineering Technology), 2006, University of the South Pacific.

Leadership

1.    Founder and Executive Director, Software Foundation Fiji, from 2010 to present.

2.    Founding Editor, Blue Fog Journal: Fiji's Literary Journal, from 2006 to present.

 Journal Reviewer

  1. IEEE Transactions on Evolutionary Computation
  2. IEEE Transactions on System, Man and Cybernetics
  3. IEEE Transactions of Neural Networks and Learning Systems
  4. Robotica
  5. Memetic Computing
  6. Neurocomputing

Membership

  1. Executive Member, Software Foundation of Fiji ,  http://softwarefoundationfiji.org/
  2. Member, International Neural Networks Society, http://www.inns.org/
  3. Member, International Society for Environmental Information Sciences, http://www.iseis.org/
  4. Member, IEEE, http://ieee.org/
  5. IEEE Computational Intelligence Society Member, http://cis.ieee.org/

Research Interests:

Artificial Intelligence and Robotics: Artificial Intelligence aims to develop machines that can learn from experience and make intelligent decisions. Neural networks are artificial Intelligence methods that are loosely modelled after biological neural systems and have a wide range of applications in pattern recognition, time series prediction, regression, clustering and control problems. They can be used to solve problems in several fields that include business, engineering and medicine. Evolutionary computation is an artificial intelligence method that is inspired from the theory of evolution. I have used evolutionary computation methods such as genetic algorithms and cooperative co-evolution as learning methods in neural networks. I am interested in developing efficient and robust learning methods for feed-forward and recurrent neural networks. I am also interested in solving large-scale optimization problems with evolutionary computation methods and further improving the performance of these methods. Robot Kinematics applies geometry to study of movement of parts that forms the structure of robotic systems. I have used evolutionary computation methods for solving the forward kinematics of parallel manipulators and am interested in further improving the efficiency and robustness of the optimization techniques.

Bioinformatics: Bioinformatics involves the use of computer science and mathematics for problems in biology, health and medicine in order to develop better methods for diagnosis and drug discovery through modelling and simulation. I am currently working on the problem of Metabolic Flux Analysis in the field of Systems Biology where Evolutionary Computation methods are used for optimization.

Environmental, Health and Medical Informatics: Environmental Informatics involves the use of computer science and mathematics to develop intelligent information systems that help in the understanding and management of environmental problems. Data repository of species in the risk of extinction can also be developed and analysed in order to provide intelligent environmental decision support systems. I have done some work in the past that involved intelligent decision support systems based on neural networks. Further work can be done in using this approach for endangered species in Fiji. Information systems in health can help to effectively manage hospital processes and patients. My interest is in examining how health information systems can be developed and deployed to enhance the medical sector in Fiji.

Publications

1.    Google Scholar Profile

2.    DBLP Profile

 Journal Articles 

1.    R. Chandra, M. Frean, M. Zhang, “Crossover-based Local Search in Cooperative Co-evolutionary Feedforward Networks”,  Applied Soft Computing, Elsevier, Vol. 12, Issue 9, September 2012, pp. 2924-2932.

2.    R. Chandra, M. Frean, M. Zhang, “On the Issue of Separability for Cooperative Coevolution of Feedforward Networks'', Neurocomputing, Elsevier, 2012, Vol. 87, June, 2012, pp. 33-40.

3.     R. Chandra, M. Zhang, “Cooperative Coevolution of Elman Recurrent Neural Networks for Chaotic Time Series Prediction”, Neurocomputing, Elsevier, Vol. 86, June, 2012, pp.116-123.

4.    R. Chandra, M. Frean, M. Zhang, “Adapting Modularity During Learning in Cooperative Co-evolutionary Recurrent Neural Networks”, Soft Computing, Springer, Vol. 16, No. 6, 2012, pp. 1009-1020.

5.    R. Chandra M. Frean, M. Zhang and Christian Omlin, “Encoding Subcomponents in Cooperative Coevolutionary   Recurrent Neural Networks '',  Neurocomputing, Elsevier, Vol 74, 2011, pp. 3223-3234.

6.    R. Chandra, L. Rolland, “On Solving the Forward Kinematics of  3RPR Planar Parallel Manipulator using Hybrid Metaheuristics'',   Applied Mathematics and Computation, Elsevier, Vol 217, No. 22,  2011, pp. 8997-9008 .

7.    R. Chandra, R. Knight and C. W. Omlin, “Renosterveld Conservation in South Africa: A Case Study for Handling Uncertainty in Knowledge Based Neural Networks for Environmental Management'',  Journal of Environmental Informatics, Vol 13, No. 1,2009, pp. 56-65.

 

 Chapter in Book Series

1.    R. Chandra,   M. Zhang, L. Peng, “Application of Cooperative Convolution Optimization for 13C Metabolic Flux Analysis: Simulation of Isotopic Labeling Patterns Based on Tandem Mass Spectrometry Measurements '',   SEAL 2012: Proceedings of International Conference on Simulated Evolution, Lecture  Notes in Computer Science, Springer, pp. 178 - 187

2.    R. Chandra, M. Frean, M. Zhang,  “An Encoding Scheme for Cooperative Coevolutionary Neural Networks".  AI 2010: Advances in Artificial Intelligence. Lecture Notes in Artificial Intelligence. Vol. 6464, , Springer., (Proceedings  of the 23rd Australasian Joint Conference on Artificial Intelligence) Adelaide, Australia, 2010. pp. 253-262.

3.    L. Rolland and R. Chandra, “On solving the forward kinematics of the 6-6 General parallel manipulator with an efficient evolutionary algorithm'', In ROMANSY 18 - Robot Design, Dynamics and Control, Series: CISM International  Centre for Mechanical Sciences, Vol. 524 Springer, Berlin, 2010, pp. 117-124..

 Refereed Conference Proceedings 

  1.  R. Chandra, M. Frean, M. Zhang, "Modularity Adaptation in Cooperative Coevolutionary Feedforward Neural Networks" , Proceedings of the IEEE International Joint Conference on Neural Networks,   2011, San Jose, USA, pp. 681-688.
  1. R. Chandra, M. Frean, M. Zhang, " Memetic Cooperative Coevolutionary Recurrent Neural Networks ", Proceedings of the IEEE International Joint Conference on Neural Networks,  2011, San Jose, USA, pp. 673-680.
  1. R. Chandra, M. Frean, L. Rolland, “A Hybrid Meta-Heuristic Paradigm for Solving the Forward Kinematics of 6-6 General Parallel Manipulator,” Proceedings of 8th IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA 2009), Daejeon, Korea, December 2009, pp. 171-176.
  1. R. Chandra, M. Zhang, L. Rolland, “Solving the Forward Kinematics of the 3RPR Planar Parallel Manipulator using a Hybrid Meta-Heuristic Paradigm'', Proceedings of 8th IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA 2009), Daejeon, Korea, December 2009, pp. 177-182. 
  1. L. Rolland, R. Chandra, “Forward Kinematics of the 3RPR planar Parallel Manipulators Using Real Coded Genetic Algorithms'', Proceedings of  24th International Symposium on Computer and Information Sciences (IEEE), North Cyprus, September 2009, pp. 381-386.
  1.  L. Rolland, R. Chandra, “Forward Kinematics of the 6-6 general Parallel Manipulator Using Real Coded Genetic Algorithms'', Proceedings of 2009 IEEE/ASME Conference on Advanced Intelligent Mechatronics, Singapore, pp. 1637-1642
  1. R.   Chandra,   C.   W.   Omlin, “Evolutionary   One-Step   Gradient   Descent   for   Training Recurrent Neural Networks'',   Proceedings of International Conference on Genetic and Evolutionary Methods, Los Vegas, July 2008, pp. 306-311.
  1. R. Chandra, G. Onwubolu, “Neural Networks in Prediction Problems'',    Proceedings of the International Workshop on Inductive Modeling, Prague, September 2007, pp. 46-54.
  1. R. Chandra, K. Chaudhary, A. Kumar, “The Combination and Comparison of Neural Networks   and Decision   Trees   for   Wine   Classification'',      Proceedings   of   the  International Workshop on Inductive Modeling, Prague, September 2007, pp. 10-17.
  1. R. Chandra and C. W. Omlin, “Combining Genetic and Gradient Descent Learning in Recurrent   Neural Networks:   An   Application   to   Speech   Phoneme   Classification``, Proceedings   of   the International   Conference   on   Artificial   Intelligence   and   Pattern   Recognition, Orlando FL, USA, July 2007, pp. 278-285.
  1. R.   Chandra   and   C.   W.   Omlin,   “A   Hybrid   Recurrent   Neural   Networks   Architecture   Inspired by  Hidden  Markov   Models:   Training   and   Extraction   of   Deterministic   Finite  Automaton'', Proceedings of the  International Conference on Artificial Intelligence and  Pattern Recognition, Orlando FL, USA, July 2007, pp. 286-293.
  1. R. Chandra and C. W. Omlin, “Hybrid Recurrent Neural Networks: An Application to    Phoneme Classification'', Proceedings of International   Conference   on   Genetic   and   Evolutionary   Methods, Las Vegas, USA, June 2007, pp. 57-62.
  1. R. Chandra and C. W. Omlin, “Knowledge Discovery using Artificial Neural Networks  for   a Conservation   Biology   Domain'', Proceedings of International   Conference   on   Data   Mining,   Las Vegas, USA, June 2007, pp. 221-227.
  1.  R. Chandra and C. W. Omlin, “Training and Extraction of Fuzzy Finite Automata in  Recurrent   Neural Networks'',   Proceedings   of   the   International   Conference   of   Computational   Intelligence,   San Fransisco,   U.S.A,   Acta   Press,   November   2006,   pp. 274-279.   
  1. R. Chandra and C. W. Omlin, “Evolutionary Training of Hybrid Systems of Recurrent Neural   Networks and   Hidden   Markov   Models'',  Proceedings   of   the WASET  International  Conference on Neural Networks, Barcelona Spain, October 2006, pp. 58-63.
  1. R.   Chandra,   R.   Knight   and   C.   W.   Omlin,   “A   Knowledge based   Neurocomputing Decision Support System for Biodiversity and Conservation Biology'',  Proceedings of the   International   Conference   on   Environmental   Management,   Environmental  Geoinformatics and Modeling, vol. 4,  Hyderabad India, 2005.   

Thesis

  1. R. Chandra, “Problem Decomposition and Adaptation in Cooperative Neuro-evolution'', PhD thesis, Victoria University of Wellington, May, 2012.
  1. R. Chandra, “Modeling of Deterministic, Fuzzy and Probabilistic Dynamical Systems'',  M.S. Thesis, University of Fiji, June, 2008. 


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