Charles Sturt University
Charles Sturt University

Associate Professor Manoranjan Paul

Associate Professor Manoranjan Paul

PhD Monash

Profile

Manoranjan Paul received the BSc Eng (honours) degree in Computer Science and Engineering from Bangladesh University of Engineering and Technology (BUET), Bangladesh, in 1997 and the PhD degree from Monash University, Australia in 2005. He has also completed Graduate Certificate in University Leadership in 2017 and Graduate Certificate in Learning & Teaching in Higher Education in 2015 from Charles Sturt University.

Currently, Manoranjan Paul is an Associate Professor in Computer Science and the Head of E-Health Research at Charles Sturt University (CSU).

Previously A/Prof Paul was an Assistant Professor/Lecturer (1997-01) at Ahsanullah University, Assistant Lecturer (2001-05) at Monash University, Post-Doctoral Research Fellow at University of New South Wales (2005-06), Post-Doctoral Research Fellow (2006-09) at Monash University, Post-Doctoral Research Fellow (2009-11) at Nanyang Technological University (Singapore), Lecturer (2011-12) at CSU, and Senior Lecturer (2013-16) at CSU. He was an Associate Director of Centre for Research in Complex Systems (2013-17).

His major research interests are in the fields:

  • Video Coding
  • Image Processing (medical imaging, hyperspectral)
  • E-Health
  • Human-Computer Interaction
  • EEG Signal Analysis
  • Cybersecurity
  • Computer Vision

He has published more than 150 fully refereed international journals, book chapters, books, and conference articles. A/Prof Paul regularly published in the top ranked journals such as IEEE Transactions. A/Prof Paul is a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE) and Australian Computer Society (ACS).

A/Prof Paul is the ICT Researcher of the Year 2017 awarded by Australian Computer Society. He obtained Faculty Research Excellent Award 2013 and Faculty Research Supervision Excellence Award 2015 at CSU. He obtained $15 million competitive grant money including Australian Research Council (ARC) Discovery Project Grant, Australia-China Science Research Grant, Cybersecurity CRC, etc.

A/Prof Paul was an invited Keynote speakers in DICTA 2017, CSWN 2017, DICTA 2013, WoWMoM 2014, and ICCIT 2010. He is an Associate Editor of Eurasip Journal on Advances in Signal Processing (JCR Rank Q2). He is also a Guest Editor of Journal of Multimedia and Journal of Computers. He has supervised 12 PhD in completion. For detailed information, please visit his personal website.

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Teaching Responsibilities

  • ITC369: Computer Vision
  • ITC713: Advanced Readings in Information Technology
  • ITC200 Database Administration
  • ITC206 Programming in Java 1
  • ITC262 Operating Systems
  • ITC313 Programming in Java 2
  • ITC421 Programming in Java 1 for Postgraduate Students

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Grants

  • Manzur Murshed and Manoranjan Paul, "Multiview Video Coding using Cuboid Data Compression", Australian Research Council (ARC) Discovery Project, $315,000, 2013~2015 (External Grant).
  • L. Ang, K.P. Seng, Manoranjan Paul, and L. Zheng, "Spherical Digital Video Camera for High Precision and Rapid Imaging," CSU RIGB grant, 2015, $31,078.
  • Manoranjan Paul, Junbin Gao, Terry Bossomaier, and Michael Antolovich, "Hyperspectral imaging", Charles Sturt University RIGB grant, 2015, $63,110.
  • Manoranjan Paul and M Z. Parvez, "Epileptic seizure prediction", FoB Compact Funding, Charles Sturt University, 2015, $7,000.
  • Manoranjan Paul, "Video Workshop", FoB Compact Funding, Charles Sturt University, 2015, $10,000.
  • Subrata Chakraborty and Manoranjan Paul, "Depth and Texture Coding", Faculty of Business Compact Funding, 2014, $6,000.
  • Manoranjan Paul, "High performance computing", Execute Deans' Educational Equipment grant, 2014, $20,000.
  • Manoranjan Paul, Junbin Gao, Michael Antolovich, Terry Bossomaier, and Zahid Islam, "Depth image processing", Charles Sturt University Research Infrastructure Block Grants (RIBG), 2013, $50,000.
  • Michael Antolovich, Junbin Gao, Jim Tulip, Manoranjan Paul, David Tien, Wayne Moore, Kevin Wilkins, and David Tilbrook (2013), "Imaging Under Dangerous Conditions, specifically within the Mining Industry," Faculty Compact Funding, 2013, $85,000.
  • Manoranjan Paul, Junbin Gao, Michael Antolovich, Terry Bossomaier, and Zahid Islam, "Abnormal event detection", Charles Sturt University Research Infrastructure Block Grants (RIBG), 2012, $43,000.
  • Junbin Gao, Terry Bossomaier, Manoranjan Paul, Michael Antolovich, and Paul Kwan, "WAREIGS: Wavelet-Network-Based Augmented-Reality-Enhanced Image-Guided Surgery," Australia-China Science Research Fund (ACSRF), 2012, $38,000(External Grant).
  • Junbin Gao, Michael Antolovich, Manoranjan Paul, and Jim Tulip, "Efficient Algorithms for Nuclear Norm Minimization," Faculty of Business Compact grant, 2012-2013, $12,702.
  • Manoranjan Paul, Junbin Gao, Michael Antolovich, and Jim Tulip, "Eye controlled video coding," Faculty of Business Compact grant, 2012-2013, $12,929.
  • Manoranjan Paul, Junbin Gao, Michael, and Terry Bossomaier, "Mentoring support for obtaining grant," Faculty of Business Compact grant, 2011, $9,902.
  • Manoranjan Paul, Junbin Gao, Michael, and Terry Bossomaier, "Project Funding," Faculty of Business Compact grant, 2011, $4,600.
  • Junbin Gao, Michael Antolovich, Manoranjan Paul, Jim Tulip and David Tien, "Visiting Fellow," Faculty of Business Compact grant, 2011, $14,036.
  • Manoranjan Paul, "Charles Sturt University Seed Grant 2011", 2011, $4,620.
  • Manoranjan Paul, "A Real-Time Human Behaviour Recognition Framework for Video Surveillance," Faculty of Information Technology, Monash University Early Career Grant, 2008, $20,000 (Top ranked project but could not obtained due to CI's institution move).
  • Manoranjan Paul and Weisi Lin, "Undergraduate Research Experience on Campus (URECA) project," Nanyang Technological University, 2009, 4× $3600 = $14,400.
  • Weisi Lin and Manoranjan Paul, "Undergraduate Research Experience on Campus (URECA) project," Nanyang Technological University, 2010, 2× $3600 = $7,200.
  • Manoranjan Paul, Manzur Murshed, and Xiaofang Zhou, "Video Signal Processing and Communication Taskforce Grant," ARC (Australian Research Council) Research Network in Enterprise Information Infrastructure (EII), 2007, $25,000 (External Grant).
  • Manoranjan Paul and Heng Tao, "First Australian Video Conference (AusVideo) Grant," ARC (Australian Research Council) Research Network in Enterprise Information Infrastructure (EII), 2007, $10,000 (External Grant).
  • Manoranjan Paul, "EII workshop Travel Grant," (Australian Research Council) Research Network in Enterprise Information Infrastructure (EII), 2006-08, $6,000 (External Grant).
  • Manoranjan Paul, "Gippsland Linkage and Discovery Initiative Scheme", Monash University, 2008, $5,000.
  • Manoranjan Paul, "Publication Time Release Scheme (PTRS)," Monash University, Gippsland Campus, 2008, $2,500.
  • Manoranjan Paul, "National & International Conference Travel Grant Scheme (NICTGS)," Monash University, Gippsland Campus, 2008, $2,000.
  • Manoranjan Paul, "National Conference Travel Grant Scheme," Monash University, Clayton Campus, 2008, $700.
  • Manoranjan Paul, "Higher Study Grants," Ahsanullah University of Science and Technology, 2001, $7500.

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Research Focus

Project 1: EEG Signal Analysis

Researchers: A/Prof Manoranjan Paul (CSU), Dr. Michael Antolovich (CSU), and Dr. Zavid Parvez (ISI Foundation, Italy and A/Prof Paul’s previous PhD student at CSU)

An Electroencephalogram (EEG) is a non-invasive graphical record of ongoing electrical activity captured from the scalp which is produced by firing of neurons of the human brain due to internal and/or external stimuli. It has great potential for the diagnosis to treatment of mental disorder and brain diseases. We are focusing on detecting and predicting of epileptic seizure period by analysis EEG signals. We are looking for other applications of EEG signals.

Outcome: We are able to predict epileptic seizure by 15 minutes earlier with 90% accuracy when we use invasive EEG signals. I successfully supervised a PhD project. We published 14 papers in this area including two journals in IEEE Transactions on Biomedical Engineering and IEEE Transactions on Neural Systems and Rehabilitation Engineering.

Left image: Multi-view video coding: Disparity-adjusted 3D block formation Right Image: Pattern-based video coding: Background-foreground separation using binary pattern mask.

Project 2: Video Coding and Compression

Researchers: A/Prof Manoranjan Paul (CSU), Professor Manzur Murshed (FedUni), A/Professor Weisi Lin (NTU), Dr. Mortuza Ali (FedUni), Dr. Tanmoy Debnath (CSU), Dr. Subrata Chakraborty (USQ), Shampa Shahriyar (PhD student, Monash University), Pallab Podder (PhD student, CSU) and Niras C.V. (PhD student, Macquarie University)

Video conferencing, video telephony, tele-teaching, tele-medicine and monitoring systems are some of the video coding/compression applications that have attracted considerable interest in recent years as 3D video is now reality. The burgeoning Internet has increased the need for transmitting (non-real-time) and/or streaming (real-time) video over a wide variety of different transmission channels connecting devices of varying storage and processing capacity. Stored movies or animations can now be downloaded and many reality-type interactive applications are also available via web-cams. In order to cater for devices with different storage and transmission bandwidth requirements, raw digital video data need to be coded at different bit rates with different timing complexity. Sometimes for realistic views of the scene of action, we also need to encode/ compress/ process videos with multiple cameras (multi-view) from different angles. We are focusing on video coding and compression in different scales suitable for different devices with accepted quality and computational time.

Outcome: An ARC DP13 which partially solve interactive problem for 3D video call. Our contributions have been adapted in the latest video coding standards e.g. HEVC, VP9, AVS. Published 4 IEEE Transactions. Supervising three PhD projects on it.

Object Detection from PETS2006 sequence

Project 3: Object Detection and Background Modeling

Researchers: A/Prof Manoranjan Paul (CSU), Professor Manzur Murshed (FedUni), A/Professor Weisi Lin (NTU), and Dr. Subrata Chakraborty (USQ)

Object detection from the complex and dynamically changing background is still a challenging task in the field of computer vision. Adaptive background modeling based object detection techniques are widely used in machine vision applications for handling the challenges of real-world multimodal background. But they are constrained to specific environment due to relying on environment specific parameters, and their performances also fluctuate across different operating speeds. Camera motions of a scene makes dynamic background modeling more complicated. We are focusing on dynamic background modeling in challenging environments and their applications in different fields.

Outcome: We are able to extract background from a challenging environment. We have successfully applied background modeling in video coding and video summarization. Published 2 IEEE Transactions. Supervised one PhD project to completion.

Eye tracker and heat map

Project 4: Eye tracking Technology

Researchers: A/Prof Manoranjan Paul (CSU), Dr. Tanmoy Debnath (CSU), and Pallab Podder (PhD student, CSU)

An eye tracker is a device to capture eye movement and its duration. In my lab, we have an eye tracker. We are focusing on various research issues e.g., Abnormal event detection and prediction, speech/alcohol/drug impairment detection, retail/advertising effectiveness, video communication for deaf people, eye can be used as an input device, improving electronic document design, increasing user acceptability of learning technologies, telemedicine, and remote surgery.

Outcome: We are able to determine human engagement using eye tracker. We are able to find some facts of marker discrepancy in multiple markers scenarios. We are also able to assess quality of a video when there is no reference. We have published three papers in this area.

Project 5: Hyperspectral Imaging

Researchers: A/Prof Manoranjan Paul (CSU), Professor Junbin Gao (University of Sydney), Professor Terry Bossomaier (CSU), and Rui Xiao (PhD student, CSU)

Hyperspectral imaging sensor divides images into many bands which can be extended beyond visible. The applications of hyperspectral imaging are in the fields of military to detect chemical weapon, geological survey, agriculture to quantify crops, mineralogy to identify different minerals, physics to identify different properties of materials, surveillance to detect different objects and reflections, measurement of surface CO2 emissions, mapping hydrological formations, tracking pollution levels, and more. We are investigating different applications of hyperspectral imaging for example Fruit-life span prediction.

Outcome: We are able to model a spectral predictor and develop a context-adaptive entropy coding technique which give us up to 7 compression ratio in some images whereas the current state-of-the-art methods only can provide around 3 compression ratio.  We published 4 papers in area including PLoS ONE 2016 journal.

Project 6: Video Summarising

Researchers: A/Prof Manoranjan Paul (CSU) and MD Salehin (PhD student, CSU)

In our daily life we capture video for various purposes such as security, entertainment, monitoring, investigating and so on. It requires huge memory space to store as well as enormous time to retrieve or replay important information manually from this high volume of videos. In this project, we explore the various features based on scene content, scene transition, human visual systems to extract important importation for particular application and make a shorter version of the video.

Outcome: We are able to summarize different type videos including surveillance, sports, movie, etc. We published 10 papers in this area including PLOS ONE 2017, JOSA A 2017.

Project 7: Collagen Defect Detection

Researchers: A/Prof Manoranjan Paul (CSU) and Chris Williams (Honors student, CSU)

Machine vision is now being extensively used for defect detection in the manufacturing process of collagen-based products such as sausage skins which is a multimillion dollar industry worldwide. At present the industry standard is to use a LabView software environment, whereby a graphical interface is used to manage and detect any defects in the collagen skins. Available data corroborates that this method allows for false positives to appear in the results where creases or folds are resolved to be defects in the product instead of being a by-product in the inspection process. This is directly responsible for reducing the overall system performance and resulting wastage of resources. Hence novel criteria were added to enhance the current techniques used with defect detection as elaborated in this paper. The proposed improvements aim to achieve a higher accuracy in detecting both true and false positives by utilizing a function that probes for the color deviation and fluctuation in the collagen skins. From the operating point of view, this method has a more flexible approach with a higher accuracy than the original graphical LabView program and could be incorporated into any programming environment. After implementation of the method in a well-known Australian company, investigational results demonstrate an average 26% increase in the ability to detect false positives with a corresponding substantial reduction in operating cost.

Project 8: View Synthesis for 3D video and Free Viewpoint Video

In recent years, free viewpoint video (FVV) or Free Viewpoint Television (FVT) technology is increasing popularity for rendering intermediate views from existing adjacent views to avoid the large volume of video data transmission. For generating an intermediate view on a remote display, Depth Image Based Rendering (DIBR) techniques are normally used, however, sometimes it has some missing pixels due to inaccurate depth, low precision rounding error and occlusion problem. To address the issue, we are working on hole filling technique, view rendering, and depth coding, 3D video formation.

Outcome: I can reconstruct a better virtual view compared to the existing one. I have published 12 papers on this area including IEEE Transactions on Image Processing (Rank 1 in Signal Processing, CORE A*).

Project 9: Medical Imaging

  • Diabetic retinopathy: Retinal vessel segmentation plays a key role in the detection of numerous eye diseases, and its reliable computerized implementation becomes important for automatic retinal disease screening systems. A large number of retinal vessel segmentation algorithms have been reported, primarily based on three main steps including uniforming background uniform, using the second-order Gaussian detector and applying binarisation. These methods though improve the accuracy levels, their sensitivity to low-contrast in vessels still needs attention. We are conducting research to improve retinal vessel extraction. This research is suitable for retinal image computer analyses such as automated screening for early diabetic retinopathy detection.
  • Augmented reality for surgery: We are trying to improve geometric accuracy for Augmented Reality (AR) in Oral and Maxillofacial Surgeries. We have some success on it and submitted a paper on it.
  • Bone cancer detection: We have used bioinformatics to detect bone cancer. We have published a paper on it in Journal of Computers, 2017.
  • Breast Implant: We are conducting research on visualising the Blood Vessels in Breast Implant Surgeries for better accuracy in augmented reality. We have some success and submitted a paper on it.
  • Fall detection:  With the help of ICT, we have developed a fall detection system using depth camera information. We have submitted a paper on it.

Outcome: Our unsupervised vessel extraction method for detecting vessel provides comparable results compared to the popular supervised methods. I have published 5 papers on this area including journals in Signal, Image and Video Processing 2017 and Pattern Analysis and Application 2017.

Retinal scan images - described below
Analysis of output images:
(a) ground truth (right eye image), (b) output image (right eye image),
(c) ground truth (left eye image), and (d) Output image (left eye image).

Falling from a chair

Falling towards camera

 
Falling sideways

Picking up object

Sitting on sofa

Sweeping floor

Fall Detection: Some challenging scenario where the existing method fails as it considers as fall for sweeping floor, picking object but the proposed method is successful.

Upper front teeth image registration

Lower front when patient moves

Image overlaying if patient moves

If surgical instrument moves

When surgical instrument moves

Mandibular reconstruction

If surgical instrument moves

Image overlaying if patient moves

AR on Oral and Maxillofacial Surgeries and AR for Visualising the Blood Vessels in Breast Implant Surgeries

Project 10: Early Diagnosis of Alzheimer’s Disease

Successful, timely diagnosis of neuropsychiatric diseases is key to management. Research efforts in the area of diagnosis of Alzheimer’s disease have used various aspects of computer-aided multi-class diagnosis approaches with varied degrees of success. However, there is still need for more efficient and reliable approaches to successful diagnosis of the disease. We are conducting research to diagnose the Alzheimer’s disease so that we are able to detect problem earlier.

Outcome: We use k-sparse autoencoder method with deep learning framework for this purpose. The results show promising results. I am supervising a Professional Doctorate project on it. I have published 1 paper on this area.

Project 11: Cardiopulmonary measurement using the smartphone

The aim of the project is to develop a non-contact cardiopulmonary detection method in natural disaster rescue relief, based on the use of frequencies and antennas that are similar to current smartphone-like devices. Current focuses are in particular on the current Wi-Fi 2.4 GHz and 5 GHz radio frequencies wavelength, Doppler effect radar, signal processes, and a signal noise cleansing technique that detects and measures vital signs. This approach could be used as an alternative to the commercially designed, devices currently used for heartbeat and respiration detection during rescue relief with the aim of reducing device transit time and cost. This project further evaluates a new type of multi-directional antenna that could be used to detect the human physiology pulsatile from 360o degree view.

Outcome: I am supervising a DIT project on it.

Detection theory of heart and breathing using continued wave

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Professional Activities

Head (2016-present), E-Health Research Group, CSU.

Associate Director (2013-2016), Centre for Research in Complex Systems (CRiCS)

ARC (Australian Research Council) Assessor Since 2013:

  • ARC Discovery Project
  • ARC Future Fellowship

Graduated PhD Students

  • Dr Shampa Shahriyar, “Depth coding,” Monash University.
  • Dr Bin Liang, “Human Gesture Detection”, CSU.
  • Dr M. Zavid Parvez, “Detection and Prediction of Epileptic Seizure using EEG signal”, CSU.
  • Dr Pallab Podder, “Efficient video coding”, CSU.
  • Dr MD. Salehin, Video summarization, CSU.
  • Dr Niras C. V., Motion estimation hardware design, Macquarie University

Current PhD Supervision

  • Rui Xiao, “Hyperspectral imaging,” CSU.
  • Motiur Rahman, “Free viewpoint video and 360 degree video”, CSU.
  • Toufique Soomro, “Retinal Imaging”, CSU
  • Rafiqul Islam, CSU
  • Linh Pham (DIT), “Cardiopulmonary measurement using the smartphone”, CSU
  • Push Bhatkoti (DIT), “Deep learning,” CSU

Editorial (from 2009)

  • M. Aziz, M. S. Alam, V. K. Asari, M. Paul, M. Rahman, S. Zhang, and M. A. Rahman (2014): Editorial. Special issue on the selected papers from IEEE International Conference on Computer & IT (IEEE ICCIT-12), Journal of Computers, 9(8), 1739-1742, SJR Rank Q3.
  • M. Murshed, M. Paul, S. Zhang, M. A. Karim (2012): Editorial. Special issue on the selected papers from IEEE ICCIT-11, Journal of Multimedia, 7(5), 325-326, SJR Rank Q2.
  • M. Murshed, M. Paul, S. Zhang, M. A. Karim (2011): Editorial. Special issue on the selected papers from IEEE ICCIT-10, Journal of Multimedia, 6(5), 393-394, SJR Rank Q2.
  • M. Murshed, M. Paul, S. Zhang, M. A. Karim (2010): Editorial. Special issue on the selected papers from IEEE ICCIT-09, Journal of Multimedia, 5(6), 541-542, SJR Rank Q2.
  • M. A. Karim, M. Murshed, M. Paul, S. Zhang (2010): Editorial. Special issue on the selected papers from IEEE ICCIT-08, Journal of Multimedia, 5(1), 1-2, SJR Rank Q2.

Journal Editor:

Keynote Speaker

Session Chair/PC member:

  • Conference Chair:
    • General Co-Chair: Pacific-Rim Symposium on Image and Video Technology (PSIVT) 2019
    • Program Co-Chair: IEEE Int. Conference on Digital Image Computing: Techniques and Applications (DICTA) 2018
    • Program Co-Chair: Pacific-Rim Symposium on Image and Video Technology (PSIVT) 2017
    • General Chair: E-Health Workshop on Remote Health using Technology (RHT) 2017
    • Publicity Chair: IEEE Int. Conference on Digital Image Computing: Techniques and Applications (DICTA) 2016
    • General Chair: Australian Workshop on Video/Image Coding, Processing, and Understanding (VICPU) 2015
    • General Co-Chair: “Video Everywhere” Workshop in IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), 2014
    • General Co-Chair: “Free viewpoint video understanding and challenges” Workshop in IEEE Picture Coding Symposium (PCS) 2015
    • General Co-Chair: “New Video Coding Technologies” workshop in IEEE International Symposium on Circuits and Systems (ISCAS) 2010
    • General Chair: Early Career Researcher (ECR) workshop, 2008
    • General Chair: Video signal processing and communication workshop, 2007
    • General Chair: Video/image processing 2006, Monash University
  • Session Chair:
    • IEEE PSIVT 2017
    • IEEE ICASSP 2015
    • IEEE ICME 2014
    • IEEE ISCAS 2010
    • IEEE ICCIT 2010
    • IEEE ICIS 2007

International Journal Reviewer

  • IEEE Transactions on Image Processing
  • IEEE Transactions on Circuits and Systems for Video Technology
  • IEEE Transactions on Multimedia
  • IEEE Transactions on Circuits and Systems Part 1
  • IEEE Communication Letter
  • IEEE Signal Processing Letter
  • International Journal of Visual Communication and Image Representation
  • IET Image Processing
  • ACM Transactions on Multimedia Computing, Communications, and Applications

Membership

  • IEEE (Senior Member)
  • IEEE Signal Processing Society (Senior Member)
  • IEEE Communication Society (Senior Member)
  • Australian Computer Society (ACS) (Senior Member)
  • Australian Research Council Network in Enterprise Information Infrastructure (EII)

Seminar presentation at different International Conferences such as

  • PSIVT 2017 (Wuhan, China)
  • ICME 2017 (Hong Kong)
  • DICTA 2017 (Sydney, Australia)
  • DICTA 2016 (Gold Coast Australia)
  • LICE 2016, 2016 (London, UK)
  • IEEE ICVNZ 2015 (Auckland, New Zealand)
  • PSIVT 2015 (Auckland, New Zealand)
  • IEEE ICASSP 2015 (Brisbane, Australia)
  • IEEE MMM 2015
  • IEEE ICME 2014
  • IEEE ICCIT 2014
  • IEEE ICECE 2014
  • IEEE WoWMoM Video Everywhere workshop (Keynote speaker)
  • DICTA-2014
  • DICTA 2013, Australia (Tutorial Speaker)
  • IEEE ICIP-2013, Australia
  • IEEE ICCIT 2012, Bangladesh
  • IEEE ICASSP-2012, Japan
  • IEEE DICTA 2011, Australia
  • IEEE ICCIT-2010 (Keynote Speaker and Session Chair), Bangladesh
  • IEEE ICIP-2010, Hong Kong
  • IEEE ISCAS-2010 (Session Chair and Special Session Organizer), France
  • IEEE ICIP-2008, USA
  • IEEE MMSP-2008, Australia
  • IEEE ICIS-2007 (Session Chair), Australia
  • ICCIT-2006, Bangladesh
  • MMM-2007, Singapore
  • IEEE ICASSP-2004, USA
  • IEEE ICME-2004, USA
  • Post IT-2004, Australia
  • ICAPR -2003, India
  • IEEE ICCIT-2003, Bangladesh

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Publications

The detailed publication list with preprint copy is available here.

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