Bappaditya Mandal

Biography

My research interest are in the areas of computer vision, machine learning, pattern recognition and video analytics. I have been working on similar research topics for my PhD work and the projects involved in the Institute for Infocomm Research, A*STAR, Singapore. I have received B.Tech. degree in Electrical Engineering from the Indian Institute of Technology, Roorkee, India and Ph.D degree in Electrical and Electronic Engineering from Nanyang Technological University, Singapore, in 2003 and 2008, respectively. I have worked as a Scientist for >9 years at the Cognitive Vision Lab, Visual Computing Department in the Institute for Infocomm Research, A*STAR, Singapore, between May 2008 to June 2017 for a number of research projects and published extensively in Journals, conferences and workshops. I have been in the Kingston University London for a short while before joining as a Lecturer in Computer Science at Keele University, UK in March 2018.

I was recipient of the prestigious “Award for Leading, Educating and Nurturing Talent (TALENT)” from A*STAR Singapore, the “Best Student Paper Award 2016: Honourable Mention Award” from the member society of International Association for Pattern Recognition (IAPR) in Singapore with my student, Long service award from the Institute in 2014, the Best Biometric Student Paper Award at the 19th International Conference on Pattern Recognition, Florida, USA, 2008, full Research Scholarship Award from Nanyang Technological University, Singapore between 2004 and 2008. In 2001, I have received the Summer Undergraduate Research Award from IIT Roorkee, India.

Along with my team members, I have own international benchmarking competition, national and international awards, student best paper awards, technological disclosures (licensing) and other accolades over the past few years. Besides, I have also played an active/lead role in a couple of video related reverse-engineering visual intelligence for cognitive enhancement projects which spans the area of face processing, summarization of ego-centric videos, activity analysis, patient behaviour monitoring and biometrics. I have worked with many SMEs companies, tried to enhance their existing or develop new products and solve their research & development problems in Singapore.

Research and scholarship

Research Interests:

Computer Vision

Face processing,
Ego-centric video summarization,
Characterization of social interactions,
Subspace modelling,
Activity analysis,
Feature extraction,
Biometrics.

Machine Learning

Deep learning, CNN, RNN,
Semi-supervised and unsupervised learning,
Generative and adversarial models,
Invariance models,
Manifold learning.

Scholarships:

There are large number of Scholarships available for local and overseas international students. Please check the entry requirements and how to apply for Postgraduate Research, here: https://www.keele.ac.uk/pgresearch /

Please refer to the following websites for details of availability and how to apply:

[1] Keele University Scholarships (https://www.keele.ac.uk/studentfunding/bursariesscholarships /)

[2] Keele University PhD Scholarships from SEND project (https://www.keele.ac.uk/business/smartenergynetworkdemonstrator/informationforgraduatesandstudents /)

[3] A*STAR Scholarships & Attachments (https://www.a-star.edu.sg/Scholarships/for-graduate-studies/a-star-research-attachment-programme-(arap))

[4] A*STAR Research Attachment Programme (ARAP), (https://www.a-star.edu.sg/Scholarships/for-graduate-studies/a-star-research-attachment-programme-(arap))

[5] External Funding Bodies (https://www.sheffield.ac.uk/postgraduate/research/scholarships/externalall).

[6] Applicants from China: Please consider support from the China Scholarship Council (CSC). (http://www.csc.edu.cn/chuguo)

[7] From time to time there are few other openings, please contact me directly.

Only short-listed candidates would be notified.

Teaching

CSC-10024 Programming I (Semester 1)

CSC-30025 Advanced Web Technologies (Semester 2)

Further information

https://sites.google.com/site/bappadityamandal/home

Selected Publications

Bhattacharya G, Puhan NB, Mandal B. 2022. Kernelized dynamic convolution routing in spatial and channel interaction for attentive concrete defect recognition. Signal Processing: Image Communication, 116818, vol. 108. doi> link> full text>
Kaothalkar A, Mandal B, Puhan N. 2022. StructureNet: Deep Context Attention Learning for Structural Component Recognition. Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. SCITEPRESS - Science and Technology Publications. doi> link> full text>
Bhattacharya G, Mandal B, Puhan NB. 2021. Interleaved Deep Artifacts-Aware Attention Mechanism for Concrete Structural Defect Classification. IEEE Trans Image Process, 6957-6969, vol. 30. link> doi> full text>
Bhattacharya G, Mandal B, Puhan NB. 2021. Multi-Deformation Aware Attention Learning for Concrete Structural Defect Classification. IEEE Transactions on Circuits and Systems for Video Technology, 3707-3713, vol. 31(9). doi>
Mandal B, Puhan NB, Verma A. 2018. Deep Convolutional Generative Adversarial Network-Based Food Recognition Using Partially Labeled Data. IEEE Sensors Letters. doi> full text>

Full Publications Listshow

Journal Articles

Bhattacharya G, Puhan NB, Mandal B. 2022. Kernelized dynamic convolution routing in spatial and channel interaction for attentive concrete defect recognition. Signal Processing: Image Communication, 116818, vol. 108. doi> link> full text>
Mishra SS, Mandal B, Puhan NB. 2022. MacularNet: Towards Fully Automated Attention-Based Deep CNN for Macular Disease Classification. SN Computer Science, Article 142, vol. 3(2). doi> link> full text>
Bhattacharya G, Puhan NB, Mandal B. 2022. Stand-Alone Composite Attention Network for Concrete Structural Defect Classification. IEEE Transactions on Artificial Intelligence, 265-274, vol. 3(2). doi> link>
Bhattacharya G, Mandal B, Puhan NB. 2021. Interleaved Deep Artifacts-Aware Attention Mechanism for Concrete Structural Defect Classification. IEEE Trans Image Process, 6957-6969, vol. 30. link> doi> full text>
Sultana NN, Mandal B, Puhan NB. 2021. Deep Regularized Discriminative Network. SN Computer Science, 1-9, vol. 2(4). doi> link> full text>
Panda R, Puhan NB, Mandal B, Panda G. 2021. GlaucoNet: Patch-Based Residual Deep Learning Network for Optic Disc and Cup Segmentation Towards Glaucoma Assessment. SN Computer Science, Article 99, vol. 2. doi> link> full text>
Behera SS, Mishra SS, Mandal B, Puhan NB. 2020. Variance-guided attention-based twin deep network for cross-spectral periocular recognition. IMAGE AND VISION COMPUTING, Article ARTN 104016, vol. 104. link> doi>
Bhattacharya G, Mandal B, Puhan NB. 2021. Multi-Deformation Aware Attention Learning for Concrete Structural Defect Classification. IEEE Transactions on Circuits and Systems for Video Technology, 3707-3713, vol. 31(9). doi>
Goel I, Puhan NB, Mandal B. 2020. Deep Convolutional Neural Network for Double-Identity Fingerprint Detection. IEEE Sensors Letters, 1-4, vol. 4(5). doi> link>
Mishra SS, Mandal B, Puhan NB. 2019. Multi-Level Dual-Attention Based CNN for Macular Optical Coherence Tomography Classification. IEEE SIGNAL PROCESSING LETTERS, 1793-1797, vol. 26(12). link> doi> full text>
Mandal B, Puhan NB, Verma A. 2018. Deep Convolutional Generative Adversarial Network-Based Food Recognition Using Partially Labeled Data. IEEE Sensors Letters. doi> full text>
Panda R, Puhan NB, Rao A, Mandal B, Padhy D, Panda G. 2018. Deep convolutional neural network-based patch classification for retinal nerve fiber layer defect detection in early glaucoma. J Med Imaging (Bellingham), 044003, vol. 5(4). link> doi>
Sultana NN, Mandal B, Puhan NB. 2018. Deep residual network with regularised fisher framework for detection of melanoma. IET COMPUTER VISION, 1096-1104, vol. 12(8). link> doi> full text>
Pandey P, Deepthi A, Mandal B, Puhan NB. 2017. FoodNet: Recognizing Foods Using Ensemble of Deep Networks. IEEE SIGNAL PROCESSING LETTERS, 1758-1762, vol. 24(12). link> doi>
Cambria E, Chattopadhyay A, Linn E, Mandal B, White B. 2017. Storages Are Not Forever. COGNITIVE COMPUTATION, 646-658, vol. 9(5). link> doi>
Chakraborty A, Mandal B, Yuan J. 2017. Person Reidentification Using Multiple Egocentric Views. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 484-498, vol. 27(3). link> doi>
Mandal B, Li L, Wang GS, Lin J. 2017. Towards Detection of Bus Driver Fatigue Based on Robust Visual Analysis of Eye State. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 545-557, vol. 18(3). link> doi>
Xu Q, Ching S, Mandal B, Li L, Mukawa M, Tan C. 2016. SocioGlass: Social interaction assistance with face recognition on google glass. Journal of Scientific Phone Apps and Mobile Devices, vol. 2(7). doi> link> full text>
Xu Q, Ching S, Lim J-H, Yiqun L, Mandal B, Li L. 2016. MedHelp: Enhancing medication compliance for demented elderly people with wearable visual intelligence. Journal of Scientific Phone Apps and Mobile Devices, vol. 2(3). doi> link> full text>
Mandal B, Wang Z, Li L, Kassim AA. 2016. Performance evaluation of local descriptors and distance measures on benchmarks and first-person-view videos for face identification. NEUROCOMPUTING, 107-116, vol. 184. link> doi>
Lu H, Pan Y, Mandal B, Eng H-L, Guan C, Chan DWS. 2013. Quantifying limb movements in epileptic seizures through color-based video analysis. IEEE Trans Biomed Eng, 461-469, vol. 60(2). link> doi>
Mandal B and Eng H-L. 2012. Regularized Discriminant Analysis for Holistic Human Activity Recognition. IEEE INTELLIGENT SYSTEMS, 21-31, vol. 27(1). link> doi>
Mandal B, Jiang X, Eng H-L, Kot A. 2010. Prediction of eigenvalues and regularization of eigenfeatures for human face verification. PATTERN RECOGNITION LETTERS, 717-724, vol. 31(8). link> doi>
Manda B, Jiang X, Kot A. 2008. Face Verification Using Modeled Eigenspectrum. The Open Artificial Intelligence Journal, 35-45, vol. 2(1). doi>
Jiang X, Mandal B, Kot A. 2008. Eigenfeature regularization and extraction in face recognition. IEEE Trans Pattern Anal Mach Intell, 383-394, vol. 30(3). link> doi>
Jiang X, Mandal B, Kot A. 2009. Complete discriminant evaluation and feature extraction in kernel space for face recognition. MACHINE VISION AND APPLICATIONS, 35-46, vol. 20(1). link> doi>
Jiang XD, Mandal B, Kot A. 2006. Enhanced maximum likelihood face recognition. ELECTRONICS LETTERS, 1089-1091, vol. 42(19). link> doi>
Mandal B. Improved Eigenfeature Regularization for Face Identification. link>

Chapters

Tan C, Lallee S, Mandal B. 2016. Vision and Memory: Looking Beyond Immediate Visual Perception. In Computational and Cognitive Neuroscience of Vision. Springer.
Mandal B, Lim R, Dai P, R M, Li L, Lim J-H. 2016. Trends in Machine and Human Face Recognition. In Advances in Face Detection and Facial Image Analysis. Springer.

Other

Kaothalkar A, Mandal B, Puhan N. 2022. StructureNet: Deep Context Attention Learning for Structural Component Recognition. Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. SCITEPRESS - Science and Technology Publications. doi> link> full text>
Behera SS, Mandal B, Puhan NB, IEEE. 2020. Twin Deep Convolutional Neural Network-based Cross-spectral Periocular Recognition. 2020 TWENTY SIXTH NATIONAL CONFERENCE ON COMMUNICATIONS (NCC 2020). link> doi>
Gonuguntla N, Mandal B, Puhan NB. Enhanced Deep Video Summarization Network. British Machine Vision Conference (BMVC). full text>
Mainwaring P and Mandal B. Improved Lifelog Ego-centric Video Summarization Using Ensemble of Deep Learned Object Features. British Machine Vision Conference (BMVC). link> full text>
Behera SS, Mandal B, Puhan NB. 2019. Cross-Spectral Periocular Recognition: A Survey. EMERGING RESEARCH IN ELECTRONICS, COMPUTER SCIENCE AND TECHNOLOGY, ICERECT 2018 (pp. 731-741, vol. 545). link> doi> full text>
Sultana NN, Puhan NB, Mandal B. 2018. DeepPCA Based Objective Function for Melanoma Detection. 2018 International Conference on Information Technology (ICIT). IEEE. doi>
Song S, Cheung N-M, Chandrasekhar V, Mandal B, ACM. 2018. Deep Adaptive Temporal Pooling for Activity Recognition. PROCEEDINGS OF THE 2018 ACM MULTIMEDIA CONFERENCE (MM'18) (pp. 1829-1837). link> doi> full text>
Mandal B, Fajtl J, Argyriou V, Monekosso D, Remagnino P, IEEE. 2018. DEEP RESIDUAL NETWORK WITH SUBCLASS DISCRIMINANT ANALYSIS FOR CROWD BEHAVIOR RECOGNITION. 2018 25TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) (pp. 938-942). link> doi> full text>
Jiang X-D, Mandal B, Kot A. Improved Bayesian Approach for Face Recognition. IEEE Fifth International Conference on Information, Communications and Signal Processing (ICICS 2005). IEEE. full text>
Mandal B, Jiang X-D, Kot A. Kernel Fisher Discriminant Analysis in Full Eigenspace. International Conference on Image Processing, Computer Vision, and Pattern Recognition (IPCV 2007). CSREA Press. full text>
Lu H, Eng H-L, Mandal B, Chan D, Ng Y-L. Markerless Video Analysis for Movement Quantification in Pediatric Epilepsy Monitoring. Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'11). IEEE. full text>
Molino AG, Mandal B, Jie L, Lim J-H, Subbaraju V, Chandrasekhar V. 2017. I2R VC @ ImageClef2017: Ensemble of Deep Learnt Features for Lifelog Video Summarization,. CEUR-WS.org. full text>
Sayed M, Lim R, Mandal B, Li L, Lim JH, Sim T. 2017. Analysis of Human Attentions for Face Recognition on Natural Videos and Comparison with CV Algorithm on Performance. Science of Intelligence: Computational Principles of Natural and Artificial Intelligence.
Subbaraju V, Xu Q, Mandal B, Li L, Lim J-H, IEEE. 2017. An Empirical Approach for Automatic Face Clustering on Personal Lifelogging Images. 2017 IEEE 2ND INTERNATIONAL CONFERENCE ON SIGNAL AND IMAGE PROCESSING (ICSIP) (pp. 127-131). IEEE. link> doi>
Mandal B, Lee D, Ouarti N. 2017. Distinguishing Posed and Spontaneous Smiles by Facial Dynamics. COMPUTER VISION - ACCV 2016 WORKSHOPS, PT I (pp. 552-566, vol. 10116). Springer. link> doi>
Li L, Mandal B, Tan C, Lim J-H, IEEE. 2017. Learning Cognitive Manifolds of Faces. 2017 IEEE 2ND INTERNATIONAL CONFERENCE ON SIGNAL AND IMAGE PROCESSING (ICSIP) (pp. 460-464). link> doi>
Mandal B and Ouarti N. 2016. Spontaneous vs. Posed smiles - can we tell the difference?. Advances in Intelligent Systems and Computing. Springer Verlag. doi> full text>
Song S, Chandrasekhar V, Mandal B, Li L, Lim J-H, Babu GS, San PP, Cheung N-M, IEEE. 2016. Multimodal Multi-stream Deep Learning for Egocentric Activity Recognition. PROCEEDINGS OF 29TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS, (CVPRW 2016) (pp. 378-385). link> doi>
Chakraborty A, Mandal B, Galoogahi HK, IEEE. 2016. Person Re-identification Using Multiple First-Person-Views on Wearable Devices. 2016 IEEE WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION (WACV 2016). link> doi>
Mandal B and IEEE. 2016. Appearance Based Robot Activity Recognition System. 2016 14TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS AND VISION (ICARCV). link>
Song S, Cheung N-M, Chandrasekhar V, Mandal B, Lin J, IEEE. 2016. EGOCENTRIC ACTIVITY RECOGNITION WITH MULTIMODAL FISHER VECTOR. 2016 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING PROCEEDINGS (pp. 2717-2721). link>
Mandal B and IEEE. 2016. Face Recognition: Perspectives from the Real World. 2016 14TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS AND VISION (ICARCV). link>
Gan T, Wong Y, Mandal B, Chandrasekhar V, Kankanhalli MS, ACM. 2015. Multi-sensor Self-Quantification of Presentations. MM'15: PROCEEDINGS OF THE 2015 ACM MULTIMEDIA CONFERENCE (pp. 601-610). link> doi>
Ching S, Mandal B, Xu Q, Li L, Lim J-H. 2015. Enhancing Social Interaction with Seamless Face Recognition on Google Glass: Leveraging opportunistic multi-tasking on smart phones. Proceedings of the 17th International Conference on Human-Computer Interaction with Mobile Devices and Services. ACM. doi> full text>
Lim R, Sayed M, Mandal B, Teck K, Li L, Lim JH. 2015. Evaluating Human Performance in Dynamic Perspective Invariant Face Recognition.
Q X, Mukawa M, Li L, Lim J-H, Tan C, Ching S, Tian G, Mandal B. 2015. Exploring Users Attitudes towards Social Interaction Assistance on Google Glass. Proceedings of the 6th Augmented Human International Conference. ACM. doi> full text>
Mandal B, Chia S-C, Li L, Chandrasekhar V, Tan C, Lim J-H. 2015. A Wearable Face Recognition System on Google Glass for Assisting Social Interactions. COMPUTER VISION - ACCV 2014 WORKSHOPS, PT III (pp. 419-433, vol. 9010). link> doi>
Mandal B, Zhikai W, Li L, Kassim AA. 2015. Evaluation of Descriptors and Distance Measures on Benchmarks and First-Person-View Videos for Face Identification. COMPUTER VISION - ACCV 2014 WORKSHOPS, PT I (pp. 585-599, vol. 9008). link> doi>
del Molino AG, Mandal B, Li L, Hwee LJ, IEEE. 2015. ORGANIZING AND RETRIEVING EPISODIC MEMORIES FROM FIRST PERSON VIEW. 2015 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA & EXPO WORKSHOPS (ICMEW). link>
Mandal B, Li L, Chandrasekhar V, Lim JH, IEEE. 2015. WHOLE SPACE SUBCLASS DISCRIMINANT ANALYSIS FOR FACE RECOGNITION. 2015 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) (pp. 329-333). link>
Gan T, Wong Y, Mandal B, Chandrasekhar V, Li L, Lim J-H, Kankanhalli MS. 2014. Recovering Social Interaction Spatial Structure from Multiple First-Person Views. Proceedings of the 3rd International Workshop on Socially-Aware Multimedia. ACM. doi>
Chandrasekhar V, Min W, Li X, Tan C, Mandal B, Li L, Lim JH, IEEE. 2014. Efficient Retrieval from Large-Scale Egocentric Visual Data Using a Sparse Graph Representation. 2014 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW) (pp. 541-548). link> doi>
Chan D, Lu H, Mandal B, NG Y-L, Eng H-L. 2012. Automated markerless video seizure detection. 12th International Child Neurology Congress (ICNC 2012). Developmental Medicine & Child Neurology.
Mandal B, Chan D, Eng H-L, Lu H, Ng Y-L. 2012. Optical flow information and video seizure recognition. 12th International Child Neurology Congress (ICNC 2012). Developmental Medicine & Child Neurology.
Mandal B, Eng H-L, Lu H, Chan DWS, Ng Y-L. 2012. Non-intrusive head movement analysis of videotaped seizures of epileptic origin. Annu Int Conf IEEE Eng Med Biol Soc (pp. 6060-6063, vol. 2012). link> doi>
Chan D, Lu H, Eng H-L, Mandal B, Ng Y-L. 2011. COMPUTERIZED VIDEO ANALYSIS AND QUANTIFICATION OF LIMB MOVEMENTS IN AUTOMATION OF SEIZURE DETECTION IN CHILDREN. EPILEPSIA (p. 214, vol. 52). link>
Mandal B, Eng H-L, IEEE. 2010. 3-PARAMETER BASED EIGENFEATURE REGULARIZATION FOR HUMAN ACTIVITY RECOGNITION. 2010 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING (pp. 954-957). link> doi>
Mandal B, Jiang X, Kot A, IEEE. 2008. Verification of Human Faces Using Predicted Eigenvalues. 19TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1-6 (pp. 1442-1445). link>
Mandal B, Jiang X, Kot A, IEEE. 2007. Dimensionality reduction in subspace face recognition. 2007 6TH INTERNATIONAL CONFERENCE ON INFORMATION, COMMUNICATIONS & SIGNAL PROCESSING, VOLS 1-4 (pp. 1057-1061). link>
Jiang X, Mandal B, Kot A, IEEE. 2007. Face recognition based on discriminant evaluation in the whole space. 2007 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOL II, PTS 1-3 (pp. 245-+). link>
Mandal B, Jiang XD, Kot A, IEEE. 2006. Multi-scale feature extraction for face recognition. ICIEA 2006: 1ST IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS, VOLS 1-3, PROCEEDINGS (pp. 792-797). link>
Mandal B, Jiang XD, Kot A, IEEE. 2006. Multi-scale feature extraction for face recognition. 2006 1ST IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS, VOLS 1-3 (pp. 1619-+). link>
Bappaditya M. Feature regularization and extraction in eigenspace for face recognition.

Research themes

School of Computer Science and Mathematics
Keele University
Staffordshire
ST5 5AA

Email: scm.admin@keele.ac.uk
Tel:+44 (0) 1782 731830

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Dr Bappaditya Mandal