In The Name of Eternal
Supervisor
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Hossein Karshenas, PhD Assistant Professor of
Artificial Intelligence |
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Fields of Interest · Estimation of Distribution
Algorithms · Data-driven Optimization · Computational Intelligence ·
Data
Analytics and Modeling ·
Probabilistic
Graphical Models ·
Machine
Learning · Multi-Objective Optimization ·
Intelligent Digital Health |
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You can follow me on: |
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Degree |
Time |
Place |
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Bachelor in Computer Engineering |
2002
2006 |
Shahid Beheshti University, Tehran,
Iran |
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Master in Artificial Intelligence
and Robotics |
2006
2009 |
Iran University of Science and
Technology, Tehran, Iran |
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PhD in Artificial Intelligence |
2009
2013 |
Technical University of Madrid,
Madrid, Spain |
·
A. Saihood, H. Karshenas
and A.R. Naghsh-Nilchi, Deep fusion of gray level co-occurrence
matrices for lung nodule classification, PLoS
ONE 17(9), pp. 1 26 (e0274516), 2022.
·
H. Shahmoradi, M. Esmaelian
and H. Karshenas, An EDA-based method for
solving electric vehicle charging scheduling problem under limited power and
maximum imbalance constraints, Computers & Industrial Engineering
172, pp. 108544, 2022.
·
P. Kazemi and H. Karshens,
Fuzzy word sense induction and disambiguation, IEEE Transactions on Fuzzy
Systems 30(9), pp. 3918 3927, 2022.
·
M. Fatehifar and H. Karshenas,
Drug-Drug interaction extraction using a position and similarity fusion-based
attention mechanism, Journal of Biomedical Informatics 115, pp. 103707,
2021.
·
N. Imanpour, A.R. Naghsh-Nilchi,
A.H. Monadjemi, H. Karshenas,
K. Nasrollahi and T.B. Moeslund,
Representative dense feature learning for memory and time-efficient single
image super-resolution, IET signal processing 15(2), pp. 141 152,
2021.
·
E. Hatefi, H. Karshenas
and P. Adibi, Conditional probability distribution
divergence reduction in visual domain adaptation, CSI Journal on Computer
Science and Engineering 17(2), pp. 8 16, 2020.
·
T. Ahmadi, H. Karshenas, B. Babaali and B. Alinejad, Allophone-based acoustic modeling
for Persian phoneme recognition (in Persian), Signal and Data Processing
17 (3), pp. 37 54, 2020.
·
E. Hatefi, H. Karshenas and P. Adibi,
Subspace Learning Augmented with Class Conditional Probability Estimation
Based on SVM Classifier in Domain Adaptation, Computer Society of Irans
25th International Computer Conference, pp. 1 7, 2020.
·
M. Sharifiasn, H. Karshenas and S. Sharifiasn,
Improving Network Intrusion Detection by Identifying Effective Features using
Evolutionary Algorithms based on Support Vector Machine (in Persian), Computational
Intelligence in Electrical Engineering 11 (1), pp. 29 42, 2020.
· N. Saeidi, H. Karshenas and
H. M. Mohammadi, Single Sample Face Recognition
using Multi-Cross Pattern and Learning Discriminative Binary Features, Journal
of Applied Security Research 14(2), pp. 169 190, 2019.
· Z. Hanifelou, P. Adibi, S.A. Monadjemi and H. Karshenas,
KNN-based multi-label twin support vector machine with priority of labels, Neurocomputing
322, pp. 177 186, 2018.
· N. Saeidi, H. Karshenas and
H. M. Mohammadi, Learning multi-objective binary
features for image representation, 7th International Conference
on Computer and Knowledge Engineering (ICCKE 2017), pp. 1-6, 2017.
· A. Nikanjam and H. Karshenas,
Multi-structure problems: Difficult model learning in discrete EDAs, IEEE
Congress on Evolutionary Computation (CEC), pp. 3448-3454, 2016.
· H. Karshenas, C. Bielza and P. Larraρaga, Interval-based ranking in noisy evolutionary
multi-objective optimization, Computational Optimization and Applications
61(2), pp. 517-555, 2015.
·
H. Karshenas, R. Santana, C. Bielza
and P. Larraρaga, Multi-objective estimation of
distribution algorithm based on joint modeling of objectives and variables, IEEE
Transactions on Evolutionary Computation 18(4), pp. 519-542, 2014.
·
P. Larraρaga, H. Karshenas, C. Bielza and R.
Santana, A review on evolutionary algorithms in Bayesian network learning and
inference tasks, Information Sciences 233, pp. 109-125, 2013.
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H. Karshenas, R. Santana, C. Bielza
and P. Larraρaga, Regularized continuous estimation
of distribution algorithms, Applied Soft Computing 13(5), pp.
2412-2432, 2013.
·
H. Karshenas, R. Santana, C. Bielza
and P. Larraρaga, Continuous estimation of
distribution algorithms based on factorized Gaussian Markov networks, In Markov
Networks in Evolutionary Computation, volume 14 of Adaptation, Learning,
and Optimization, pp. 157-173, Springer, Berlin, 2012.
·
P. Larraρaga, H. Karshenas, C. Bielza and R.
Santana, A review on probabilistic graphical models in evolutionary
computation, Journal of Heuristics 18(5), pp. 795-819, 2012.
·
H. Karshenas, R. Santana, C. Bielza
and P. Larraρaga, Multi-objective optimization with
joint probabilistic modeling of objectives and variables, In Proceedings of
Evolutionary Multi-Criterion Optimization, volume 6576 of Lecture Notes in
Computer Science, pp. 298-312, Springer, Berlin, 2011.
·
H. Parvin, B. Minaei, H. Karshenas and A. Beigi, A new
N-gram feature extraction-selection method for malicious code, In Proceedings
of Adaptive and Natural Computing Algorithms, volume 6594 of Lecture Notes
in Computer Science, pp. 98-107, Springer, Berlin, 2011.
·
R. Santana, H. Karshenas,
C. Bielza and P. Larraρaga,
Regularized k-order Markov models in EDAs, In Proceedings of 13th Annual
Genetic and Evolutionary Computation Conference (GECCO'11), pp. 593-600,
ACM, 2011.
· H. Karshenas, A. Nikanjam, B.H. Helmi and A.T. Rahmani, Combinatorial effects of local structures and
scoring metrics in Bayesian optimization algorithm, In Proceedings of First
ACM/SIGEVO Summit on Genetic and Evolutionary Computation (GEC 2009), pp.
263-270, ACM, 2009.
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E. Shahrian, H. Karshenas and M. Fathy, A similarity-window based
background estimation approach, In Proceedings of IEEE/ACS International
Conference on Computer Systems and Applications (AICCSA'08), pp. 623-628,
2008.
·
Deep
learning for multi-modal multi-label emotion recognition, Master Thesis
(Student: Sara Azima), 2020 2022.
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Deep
reinforcement learning-based image captioning, Master Thesis (Student: Ali
Abedi), 2020 2022.
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Deep
reinforcement learning for training intelligent agents in natural language
environments, MSc Thesis (Student: Parham Kazemi),
2020 2021.
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Iranian
stock market prediction using social media sentiment analysis, Master Thesis
(Student: Elham Mohammadnejad), 2019 2022.
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Identification
of hot topics and trends in information science and knowledge based on text
mining techniques, MSc Thesis (Student: Elahe Akhavan-Hariri), 2019 2020.
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Video
semantic segmentation with deep neural networks and attention mechanism, MSc
Thesis (Student: Mahdiye Mirmahdi),
2018 2021.
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Many-objective
estimation of distribution algorithms based on decomposition, MSc Thesis
(Student: Farzaneh Hadifar),
2018 2021.
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Task-adaptive
hyper variation operator for metaheuristics, MSc Thesis (Student: Najmeh Pourkhamisi), 2018 2020.
·
Denotative
forecast of energy consumption in road transportation (freight and passenger)
using artificial neural networks: A case study in Iran, MSc Thesis (Student:
Mahmood Monavari), Funded by National Iranian Oil
Products Distribution Company (NIOPDC), 2018 2019.
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Drug-drug
interaction detection from text using deep neural networks, MSc Thesis
(Student: Mohsen Fatehifar), 2017 2020.
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Gait
quality prognosis in children with cerebral palsy using neural networks, MSc
Thesis (Student: Zahra Mousavi), 2017 2019.
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Forecasting
electricity consumption using household profile extraction, MSc Thesis
(Student: Amin Hadi), with the cooperation of Esfahan
Province Electricity Distribution Company (EPEDC), 2017 2019.
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Intrusion
detection system based on estimation of distribution algorithms and support
vector machine classifiers, MSc Thesis (Student: Masoud Sharifian), 2017
2019.
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Sentiment
analysis of news articles for international stock price predictions, MSc Thesis
(Student: Mohammad Ali Golshan), 2016 2019.
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Improving
MBN-EDA with reference point-based selection methods, MSc Thesis (Student: Somayeh Ghadiri), 2016 2018.
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Learning
multi-objective binary features for image representation and recognition, MSc
Thesis (Student: Nemat Saeidi),
2016 2018.
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Modeling
health tourism capital import using data mining methods, MSc Thesis (Student: Farzane Jahani Kaji), with the cooperation of Isfahan Fertility &
Infertility Center, 2016 2017.
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Automatic
broad and narrow transcription of read formal speech in Persian language based
on phone recognition, MSc Thesis (Student: Tahere
Ahmadi), 2015 2018.
Available
Positions and Collaboration
·
Analysis
and modeling of metaheuristic and evolutionary based search
Please contact me for more information
Current Students
·
MSc
o Mohammad-Amin Dadgar
·
PhD
o Mina Khaksar (Co-supervisor)
o Emad Alanbari
(Co-supervisor)
o Nemat Saeidi (Co-supervisor)
o Hoda Moradian
o Ahmed Ali Seihood
o Hadi Tabeolhojjah (Co-supervisor)
o Fatemeh Zarmehr
(Advisor)
o Elham Hatefi
(Co-supervisor)
Past Students
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MSc
o Sara Azima
o Ali Abedi (Currently PhD student of Electrical
Engineering, University of Windsor)
o Elham Mohammadnejad
(Co-supervisor)
o Parham Kazemi (Currently
PhD student of Bioinformatics, University of British Columbia)
o Elahe Akhavan-Hariri (Currently PhD
student of Information Science and Knowledge Studies, Kharazmi
University) (Advisor)
o Mahdiye Mirmahdi (Advisor)
o Farzaneh Hadifar
o Najmeh Pourkhamisi
o Mahmood Monavari
(Advisor)
o Mohsen Fatehifar
(Currently PhD student of Audiology, University of Manchester)
o Zahra Mousavi Fakhr
o Amin Hadi
o Masoud Sharifian
o Mohammad Ali Golshan
(Advisor)
o Somayeh Ghadiri (Advisor)
o Ali Fattahi (Advisor)
o Nemat Saeidi (Currently PhD student
of Artificial Intelligence, University of Isfahan)
o Farzane Jahani Kaji
(Advisor)
o Tahere Ahmadi (Currently PhD candidate at Linguistics
Department, University of Isfahan) (Co-supervisor)
·
PhD
o Hadi Shahmoradi (Advisor)
o Nasrin Imanpour
(Advisor)
|
Undergraduate |
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Graduate |
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Artificial
Intelligence Principles
of Compiler Design Fundamentals
of Computer Programming Advanced
Computer Programming Professional
English in Computer Science Information
Storage and Retrieval Expert
Systems |
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Evolutionary
Computation Probabilistic
Graphical Models Advanced
Optimization Algorithms Fuzzy
Sets and Systems Corpus
Development, Management and Application Artificial
Intelligence Seminar |
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Journals
o
Computational
Intelligence in Electrical Engineering, University of Isfahan, 2020 2022.
o
Information
Sciences, Elsevier, 2013 2021.
o
IEEE
Transactions on Evolutionary Computation, IEEE Computational Intelligence
Society, 2012 2019.
o
Journal
of Computing and Security, University of Isfahan, 2015 2020.
o
IEEE
Access, IEEE, 2018 2022.
o
IEEE
Transactions on Cybernetics, IEEE Computational Intelligence Society, 2017.
o
Memetic
Computing, Elsevier, 2014.
o Automation in Construction, Elsevier, 2013.
·
Conferences
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Fifth
International Conference on Internet of Things and Its Applications (IOT2021),
19 20 May 2021, Isfahan, Iran, URL: https://iot2021.ui.ac.ir/en/
o
6th
Conference on Signal Processing and Intelligent Systems (ICSPIS2020), 23 24
December 2020, Mashhad, Iran, URL: http://www.icspis.ir/
o
Fifth National Conference
on Computer Games: Challenges and Opportunities (CGCO2020), 19 February 2020,
Isfahan, Iran, URL: http://cgco2020.ui.ac.ir/en/
o
Third International Conference on Internet of Things
and Applications (IOT2019), 17 18 April 2019, Isfahan, Iran, URL: http://iot2019.ui.ac.ir/en/
o
Third National Conference
on Computer Games: Challenges and Opportunities (CGCO2018), 14 February 2018,
Isfahan, Iran, URL: http://cgco2018.ui.ac.ir/en/
o
26th Iranian
Conference on Electrical Engineering (ICEE2018), 8 10 May 2018, Mashhad,
Iran, URL: http://icee2018.sadjad.ac.ir/
o
First International Conference on Internet of Things:
Applications and Infrastructure (IOT2017), 19 20 April 2017, Isfahan, Iran,
URL: http://iot2017.ui.ac.ir:81/en/
o
Second National Conference on Computer Games:
Challenges and Opportunities (CGCO2017), 16 18 February 2017, Isfahan, Iran,
URL: http://cgco2017.ui.ac.ir:81/fa/
o
First National Conference on Computer Games:
Challenges and Opportunities (CGCO2016), 17 19 February 2016, Isfahan, Iran,
URL: http://cgco2016.ui.ac.ir:81/fa/
o
14th International Conference on
Intelligent Data Engineering and Automated Learning (IDEAL 2013), Special
Session on Swarm Intelligence and Data Mining (SIDM 2013), October 20 23,
2013, Hefei, Anhui, China. URL: http://sidm2013.nclab.tw
Last Updated: January 9, 2023