Dr. G M Atiqur Rahaman
Professor



    Contact:

    01715712877

    Address:

    Computer Science and Engineering Discipline, Khulna University, Khulna-9208, Bangladesh.


I am a computer scientist and engineer, currently employed as a Professor in Computer Science and Engineering Discipline of the renowned Khulna University of Bangladesh. I have institutional training and expertise in Spectral Imaging and machine-learning-based image analysis. I was a postdoctoral fellow in the Machine Perception and Interaction (MPI) lab, in the Center for Applied Autonomous Sensor Systems (AASS) of Örebro University, Sweden. I have worked with Örebro University Hospital, Örebro Municipality, and the Swedish Institute for Forest Research. I have designed and implemented various deep-learning methods for solving challenging industrial problems. The contributions have been published in a high-quality journal and European conference. 

I achieved Ph.D. degree in Computer Science from the School of Computing at the highly-ranked University of Eastern Finland (UEF) attached to the Computational Spectral Imaging Research Group. The research focus was on developing a machine learning approach to analyze multispectral images. I have also completed a Licentiate of Technology degree in Engineering Physics from Mid Sweden University with an EU Marie Curie Fellowship under the project CP7.0 led by NTNU. During this study, I developed innovative methods to analyze halftone microscale images and proposed an extension of a classical color reproduction model useful for the Printing and Graphics Arts Industry. The application area was in the cultural heritage and spectral printing industry.

I completed the EU Erasmus Mundus double Master degree (CIMET) jointly awarded ( due to extraordinary results) by the University of Granada Spain, University Jean-Monnet France, Norwegian University of Science and Technology (NTNU), and UEF. The main fields of study were Spectral Imaging, Signal, and Vision. In my M.Sc. thesis, I proposed novel techniques to analyze multispectral retinal images to detect and classify various diabetic retinopathies. During 04 years of study of B.Sc. Engineering in Computer Science and Engineering discipline, I worked for one year on a bachelor thesis in MRI medical image analysis. An algorithm was proposed to render voxel-based surface to reconstruct the scanned brain image.

My overall research area and interests are in developing machine/deep learning-based computational techniques for various applications in the intersection fields of spectral imaging, color science, computer vision, pattern recognition and modeling. My current research focuses on developing Machine Learning/Neural Network/Deep Learning based methods for image analysis in different medical applications. Throughout my academic and research career, I have worked with high-quality international researchers both in academia and industries around the world. Over the last 20 years, not only I have been involved in pursuing post-graduate studies in Europe but also involved in teaching, researching and supervising students of Computer Science at the university level. So far I have supervised as the main supervisor or evaluated as an expert member a number of thesis and projects in computer science at undergraduate and graduate levels. Currently, I am supervising Ph.D., M.Sc. and B.Sc. thesis students working on machine learning/deep learning-based method development to analyze images  in different applications.

I have scientific publications and documented knowledge in the fields computer vision, deep learning, multispectral imaging and image analysis. I have notable experience in teaching at the university level. Solid and relevant multi-disciplinary education, training, skills, and work experiences in high-quality international research and academic environments have made me a strong candidate for an academic administration or research position.

I am proficient in both independent work and collaborative teamwork, with a commitment to excellence, strong ethics, and respect for diverse viewpoints. I am eager to contribute innovative ideas, solve real-world problems, and disseminate knowledge within the academic community. My multidisciplinary education, diverse skills, and extensive teaching and research experience equip me to develop a high-quality international academic and research environment.

My diverse educational background, extensive research skills, and substantial teaching experience equip me for leadership in the academic arena. I am committed to creating a high-quality academic and research environment and aspire to contribute to building a knowledge-based society in Bangladesh, enhancing the quality of life through education and innovation.

 


Postdoctoral Fellow, Machine Perception and Interaction Lab, Orebro University, Sweden       2021-2023
Research Area: Artificial Intelligence, Machine Learning, Deep learning

Ph.D. in Computer Science, University of Eastern Finland, Finland                                            2017

Dissertation: Use of Reflectance Measurements to Study Turbid Media by Imaging

Licentiate of Technology in Engineering Physics, Mid Sweden University, Sweden                2014

Dissertation: Image Analysis Approach for modelling Color in Printing

M.Sc. in Computer Science (Univ. of Eastern Finland + Univ. Jean-Monnet, France)                  2011

M.Sc. in Optics, Image and Vision, (Univ. of Granada, Spain + Univ. Jean-Monnet France)      2010

Thesis: Retinal Spectral Image Analysis for Diabetic Retinopathy

Obtained Grade: B (80%-89%) marks

B.Sc. Engg. in Computer Science and Engg., Khulna University, Bangladesh                           2003

Thesis: Iso-surface Construction Technique of Volumetric Data for Medical Imaging

Obtained CGPA: 3.81/4.0 (Distinction, 2nd position in merit list) 

Higher Secondary Certificate (HSC) Exam., Notre Dame College, Dhaka, Bangladesh             1998

Obtained marks: 89.4% 

Secondary School Certificate (SSC) Exam., Khulna Zilla School, Khulna, Bangladesh              1996

Obtained marks: 85.3% 


Artificial Intelligence

Deep Learning

Machine Learning

Computer Vision

Color Science

Spectral/Colour Imaging

Current Research Project/Collaboration

SL Title Research Role Awarded Date Completion Date Funding Agency
No Research Project Available


Position
Name of the Institution
Duration
Postdoctoral FellowMachine Perception and Interaction (MPI) lab, Centre for Applied Autonomous Sensor Systems (AASS), Örebro University, Sweden     
2021- 2023
 ProfessorComputer Science and Engineering (CSE) Discipline, Khulna University, Bangladesh 
2017- to date  
Associate Professor 
CSE Discipline, Khulna University, Bangladesh 2011- 2017
Assistant Professor
CSE Discipline, Khulna University, Bangladesh 
2007- 2011
Lecturer
CSE Discipline, Khulna University, Bangladesh                                            
2006-2007
Lecturer
CSE Faculty, Patuakhali Science and Technology University, Bangladesh             
2004- 2006
Part-time teacher
Khulna Agricultural University, Dhaka International University, Northern University of Business and Technology, Asian University, ICMAB, College Teachers Training Institute, etc.                        
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EU Marie Curie Fellowship for PhD (2012-2015)

EU Erasmus Mundus Scholarship for double M.Sc. degree (2009-2011)

Bangladesh ICT Division Fellowship (2016)

Khulna University Merit Scholarship

H.S.C. and S.S.C. Education Board Merit Scholarships

Supervision

SL Title Degree Role Start Date End Date
No Supervision Available

No Data Available

coming soon...

Publications (All are Peer Reviewed Articles)

Journals/Book Chapters

1.        G. M. Atiqur Rahaman, M. Längkvist and A. Loutfi (2024). Deep Learning Based Automated Estimation of Urban Green Space Index from Satellite Image: A Case Study, Urban Forestry & Urban Greening, Volume 97,128373, doi: 10.1016/j.ufug.2024.128373. (IF 6.0)

2.        Azoad ahnaf SM, Saha S, Frost S, Rahaman G.M.A. Understanding and interpreting CNN’s decision in optical coherence tomography-based AMD detection. European Journal of Ophthalmology. 2023;0(0). doi:10.1177/11206721231199126 (IF 1.6)

3.        S. Saha, Rahaman G.M.A., T. Islam, M. Akter, S. Frost, Y. Kanagasingam(2021), Retinal image registration using log-polar transform and robust description of bifurcation points, Biomedical Signal Processing and Control, Volume 66, 102424, ISSN 1746-8094, https://doi.org/10.1016/j.bspc.2021.102424. (IF 4.9)

4.        Md.M.R. Rana, A. Hasnat, Rahaman G.M.A., (2022), SMIFD-1000: Social media image forgery detection database, Forensic Science International: Digital Investigation, Volume 41, 301392, ISSN 2666-2817, https://doi.org/10.1016/j.fsidi.2022.301392. (IF 2.0)

5.        Rahaman G.M.A., S. R. . Ali, and S. . Paul (2021), Diabetic Retinopathy Lesion Detection From Multispectral Retinal Images Through Neural Network, Khulna Univ. Stud., pp. 41–55, Sep., https://doi.org/10.53808/KUS.2020.17.1and2.2001-E

6.        Rahaman G.M.A., Jussi Parkkinen, and Markku Hauta-Kasari(2020). A Novel Approach to Using Spectral Imaging to Classify Dyes in Colored Fibers. Sensors 20, no. 16: 4379.     https://doi.org/10.3390/s20164379 (IF 3.4)

7.        Sayed M.A., Saha S., Rahaman G.M.A., Ghosh T.K., Kanagasingam Y (2020) An Innovate Approach for Retinal Blood Vessel Segmentation using Mixture of Supervised and Unsupervised Methods. Image Processing, IET, (https://doi.org/10.1049/ipr2.12018 (IF 1.78)

8.        Rahaman G.M.A, Rajon A H M, Rahman A. (2012), Effective Approach for Automatic Detection of Vessels, Optic Disk and Macula: Retinal Spectral Image Analysis Perspective. International journal of Applied Research in Computer Science and Information Technology (IJAR-CSIT), Vol. 2

9.        Rahaman G.M.A., Hossain M. M., Arif M. A., Chowdhury E. & Debnath S. (2010). Mining structured objects (data records) based on maximum region detection by text content comparison from website. International Journal of Electrical and Computer Sciences (IJECS-IJENS), 10(2), 22-28.

10.     Chatterjee A., Shuvankar M., Rahaman G.M.A., and Abu S.M.A. (2010), Fingerprint identification and verification system by minutiae extraction using artificial neural network. The International Journal of Computer and Information Technology JCIT 1(1) pp. 12-16

11.     Ripon K.S.N., Rahman A. and Rahaman G.M.A. (2010) A domain-independent data cleaning algorithm for detecting similar-duplicates. Journal of Computers 5(12) pp. 1800-1809 DOI: 10.4304/jcp.5.12.1800-1809

12.     Rahaman G.M.A., Md. M. Hossain (2009). Automatic Defect Detection and Classification Technique from Image: A Special Case Using Ceramic Tiles.            arXiv:0906.3770 [cs.CV], https://doi.org/10.48550/arXiv.0906.3770

13.     Rahaman G.M.A. and Alam A.F.M.(2008). An Efficient Approach for fast Fingerprint Identification based on Minutiae Local Structure. Southeast University Journal of Engineering and Technology SEUJSE 2(2) (print version only)

14.     Protik, P.,  Rahaman, G. M.A., & Saha, S. (2023). Automated Detection of Diabetic Foot Ulcer Using Convolutional Neural Network. In The Fourth Industrial Revolution and Beyond: Select Proceedings of IC4IR+ (pp. 565-576). Singapore: Springer Nature Singapore. DOI: https://doi.org/10.1007/978-981-19-8032-9_40

15.     Jamil, M. S., Banik, S. P., Rahaman, G.M.A., & Saha, S. (2023). Advanced GradCAM++: Improved Visual Explanations of CNN’s decision in Diabetic Retinopathy. In Computer Vision and Image Analysis for Industry 4.0 (pp. 64-75). 6000 Broken Sound Parkway NW, Suite 300, Boca Raton, FL 33487-2742: CRC Press.

16.     S. Pal, and G.M.A. Rahaman (2022). Image Forgery Detection Using CNN and Local Binary Pattern-Based Patch Descriptor. In Innovations in Computational Intelligence and Computer Vision, pp. 429-439. Springer, Singapore. https://doi.org/10.1007/978-981-19-0475-2_38 (Best paper in Deep Learning track)

17.     Sayed M.A., Saha S., Rahaman G.M.A., Ghosh T.K., Kanagasingam Y. (2019) A Semi-supervised Approach to Segment Retinal Blood Vessels in Color Fundus Photographs. In: Artificial Intelligence in Medicine, AIME 2019. Lecture Notes in Computer Science, vol 11526, pp 347-351, Springer, Cham. DOI: 10.1007/978-3-030-21642-9_44

18.     Islam S.T., Saha S., Rahaman G.M.A., Dutta D., Kanagasingam Y. (2019) An Efficient Binary Descriptor to Describe Retinal Bifurcation Point for Image Registration. In: Pattern Recognition and Image Analysis, IbPRIA 2019. Lecture Notes in Computer Science, vol 11867. Springer, Cham. DOI: 10.1007/978-3-030-31332-6_47

19.     Ghosh T.K., Saha S., Rahaman G.M.A., Sayed M.A., Kanagasingam Y. (2019) Retinal Blood Vessel Segmentation: A Semi-supervised Approach. In: Pattern Recognition and Image Analysis, IbPRIA 2019. Lecture Notes in Computer Science, vol 11868. Springer, Cham. DOI: 10.1007/978-3-030-31321-0_9

20.     Rahaman G.M.A., Hasnat M.A., Mourya R. (2015) Collection, Analysis and Representation of Memory Color Information. In: Computational Color Imaging. CCIW 2015. Lecture Notes in Computer Science, vol 9016, pp. 93–103, Springer, Switzerland. DOI: 10.1007/978-3-319-15979-9_9

21.     Rahaman G.M.A., Norberg O., Edström P. (2015) Experimental Analysis for Modeling Color of Halftone Images. In: Computational Color Imaging. CCIW 2015. Lecture Notes in Computer Science, vol 9016, pp. 69–80, Springer, Switzerland. DOI: 10.1007/978-3-319-15979-9_7

22.     Rahaman G.M.A., Parkkinen J., Hauta-Kasari M., Norberg O. (2013) Retinal Spectral Image Analysis Methods Using Spectral Reflectance Pattern Recognition. In: Computational Color Imaging. CCIW 2013. Lecture Notes in Computer Science, vol 7786, pp. 224–238, Springer, Berlin, Heidelberg. DOI: 10.1007/978-3-642-36700-7_18

 Conference (Peer Reviewed) Papers

23.     G. M. A. Rahaman, M. Längkvist and A. Loutfi, Deep Learning based Aerial Image Segmentation for Computing Green Area Factor, 2022 10th European Workshop on Visual Information Processing (EUVIP), Lisbon, Portugal 2022, pp. 1-6,                                                  doi: 10.1109/EUVIP53989.2022.9922743

24.     Protik, P., Rahaman, G.M.A, Saha, S. (2023). Automated Detection of Diabetic Foot Ulcer Using Convolutional Neural Network. In: Hossain, M.S., Majumder, S.P., Siddique, N., Hossain, M.S. (eds) The Fourth Industrial Revolution and Beyond. Lecture Notes in Electrical Engineering, vol 980. Springer, Singapore. doi: 10.1007/978-981-19-8032-9_40

25.     S. M. A. Ahnaf, G. M. A. Rahaman and S. Saha, (2021), Understanding CNN's Decision Making on OCT-based AMD Detection", 2021 International Conference on Electronics, Communications and Information Technology (ICECIT),  pp. 1-4,   doi: 10.1109/ICECIT54077.2021.9641246.

26.     K. M. Hasan et al., Design and Development of an Aircraft Type Multi-functional Autonomous Drone, 2020 IEEE Region 10 Symposium (TENSYMP), 2020, pp. 734-737, doi: 10.1109/TENSYMP50017.2020.9230929

27.     Md. Mehedi Rahman, , Jannatul Tajrin,  Abul Hasnat,  Naushad UzZaman, and G. M. Atiqur Rahaman (2019, December). SMIFD: Novel Social Media Image Forgery Detection Database. Proc. of IEEE 22nd International Conference on Computer and Information Technology (ICCIT), 18-20 December, 2019. doi10.1109/iccit48885.2019.9038557

28.     Rahaman G.M.A., Parkkinen J., Hauta-Kasari M., & Amirshahi S. H. (2017, February). Enhanced color visualization by spectral imaging: an application in cultural heritage. In 2017 IEEE International Conference on Imaging, Vision & Pattern Recognition (icIVPR) (pp. 1-6). IEEE. doi10.1109/ICIVPR.2017.7890870

29.     Rahaman G.M.A., Parkkinen J., Hauta-Kasari  M., & Amirshahi S. H. (2017, February). Fiber dye classification by spectral imaging. In 2017 IEEE International Conference on Imaging, Vision & Pattern Recognition (icIVPR) (pp. 1-6). IEEE. DOI: 10.1109/icivpr.2017.7890872

30.     Khan M. R., Rahman A. M., Rahaman G. M. A., & Hasnat M. A. (2016, May). Unsupervised RGB-D image segmentation by multi-layer clustering. In 2016 IEEE 5th International Conference on Informatics, Electronics and Vision (ICIEV) (pp. 719-724). IEEE DOI: 10.1109/iciev.2016.7760095

31.     Rahaman G.M.A., Norberg O., & Edström P. (2014, February). Extension of Murray-Davies tone reproduction model by adding edge effect of halftone dots. In: Proc. SPIE 9018, Measuring, Modeling, and Reproducing Material Appearance, 90180F; International Society for Optics and Photonics. doi:10.1117/12.2037754

32.     Rahaman G.M.A., Norberg O., & Edström P. (2014, February). Microscale halftone color image analysis: perspective of spectral color prediction modeling. In Proc. SPIE Color Imaging XIX: Displaying, Processing, Hardcopy, and Applications (Vol. 9015, p. 901506). International Society for Optics and Photonics. doi10.1117/12.2037256

33.     Rahaman G. M.A., Norberg O., & Edström P. (2013, July). The Effect of Media Interactions in Predicting Spectral Reflectance by Color Prediction Models. In: Proc. of 12th Congress of the International Colour Association Newcastle upon Tyne, UK,  Vol.2, pp.593-596 

34.     Arif A.S.M., Rahaman G.M.A., Biswas G. K., & Islam, S. N. (2008, December). An efficient system for recognition of human face in different expressions by some measured features of the face using laplacian operator. In IEEE Proc. 11th International Conference on Information and Communication Technology (ICCIT’08),   pp. 405-410. DOI: 10.1109/iccitechn.2008.4802977

35.     Alam A.F.M. , Ali I.A., Debnath R., Rahaman, G.M.A. (2008) Efficient Fingerprint Identification and Verification System Using Minutiae Matching Technique. In Proc. of the International Conference on Electronics, Computer and Communication (ICECC’08), pp.: 364-367.

36.     Mondal M., Rahaman G.M.A., Tarafder D.(2008). Real Time Face Recognition Using Minimum Measurements when at Least Two Thirds of the Face is Present in the Image. In: Proc. 9th International Conference on Computer and Information Technology (ICCIT 06), pp: 247-252


Books

37.     Títle: Use of Reflectance Measurements to study Turbid Media by Imaging, City: Joensuu, Finland, Editorial: Prof. Lindsay W. Macdonald and Docent Reiner Lenz., Year: 2017, Number of pages: 151, ISBN: 978-952-61-2455-1, Authors: Rahaman, G M Atiqur (PhD Thesis)

38.     Títle: Image Analysis Approach for Modeling Color Predictions in Printing , City: Sundsvall, Sweden, Editorial: Prof. Per Edstrom, Dr. Ole Norberg and Dr. Magnus Neuman, Year: 2014, Number of pages: 51, ISBN: 978-91-87557-32-3, Authors: Rahaman, G M Atiqur (Licentiate Thesis)