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Bilde av Prasad, Dilip K.
Bilde av Prasad, Dilip K.
Department of Computer Science dilip.prasad@uit.no +4777645694 Here you can find me

Dilip K. Prasad

Associate professor

Job description

Dilip K. Prasad (IEEE Senior Member) is an associate professor at the Department of Computer Science, UiT The Arctic University of Norway. He received the Ph.D and B.Tech degree in Computer Science and Engineering from Nanyang Technological University, Singapore and Indian Institute of Technology (Indian School of Mines), Dhanbad, India, respectively. He was a senior research fellow at Nanyang Technological University, Singapore from 2015-2019 and research Fellow at National University of Singapore from 2012-2015. Prior to Ph.D., he has worked for 5 years with IBM, Infosys, Mediatek and Philips.He has been selected as a Fellow for Kauffman Global Scholarship in 2011, in which he was trained in entrepreneurship at Harvard University, MIT, Stanford University and the Kauffman Foundation. He has been awarded with Rolls-Royce Inventer Award in 2016. He has published 130+ internationally peer-reviewed research articles and patents. He is a co-founder of Bio-AI lab at UiT. Since 2019, he has secured ~21 million Euro research and innovation grant as a PI/co-PI from European Union, Research Council of Norway. His research interest in sustainable AI, Scalable AI, Interpretable AI and application of AI for life sciences. He is a co-author of the book titled "Interpretability in Deep Learning", Springer, 2023.

  • Rohit Agarwal, Ludwig Alexander Horsch, Dilip Kumar Prasad :
    Modelling Irregularly Sampled Time Series Without Imputation
    arXiv.org 2023 DOI
  • Abhinanda Ranjit Punnakkal, Suyog Sakhahari Jadhav, Krishna Agarwal, Ludwig Alexander Horsch, Dilip Kumar Prasad :
    MiShape: 3D Shape Modelling of Mitochondria in Microscopy
    arXiv.org 2023 DOI
  • Rohit Agarwal, Ankit Butola, Ludwig Alexander Horsch, Dilip Kumar Prasad, Krishna Agarwal :
    Taxonomy of hybridly polarized Stokes vortex beams
    arXiv.org 2023 DOI
  • Abhinanda Ranjit Punnakkal, Gustav Godtliebsen, Ayush Somani, Sebastian Andres Acuna Maldonado, Åsa birna Birgisdottir, Dilip K. Prasad et al.:
    Analyzing Mitochondrial Morphology Through Simulation Supervised Learning
    Journal of Visualized Experiments 2023 ARKIV / DOI
  • Sunil Bhatt, Ankit Butola, Anand Kumar, Pramila Thapa, Akshay Joshi, Suyog S. Jadhav et al.:
    Single-shot multispectral quantitative phase imaging of biological samples using deep learning
    Applied Optics 2023 DOI
  • Gustav Godtliebsen, Kenneth Bowitz Larsen, Zambarlal Babanrao Bhujabal, Ida Sundvor Opstad, Mireia Nager Grifo, Abhinanda Ranjit Punnakkal et al.:
    High-resolution visualization and assessment of basal and OXPHOS-induced mitophagy in H9c2 cardiomyoblasts
    Autophagy 2023 ARKIV / DOI
  • Rohit Agarwal, Dilip Kumar Prasad, Ludwig Alexander Horsch :
    Aux-Drop: Handling Haphazard Inputs in Online Learning Using Auxiliary Dropouts
    Transactions on Machine Learning Research (TMLR) 2023
  • Rohit Agarwal, Gyanendra Das, Saksham Aggarwal, Ludwig Alexander Horsch, Dilip Kumar Prasad :
    Mabnet: Master Assistant Buddy Network With Hybrid Learning for Image Retrieval
    Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing 2023 DOI
  • Xinqiang Chen, Xingyu Wu, Dilip K. Prasad, Bing Wu, Octavian Postolache, Yongsheng Yang :
    Pixel-Wise Ship Identification From Maritime Images via a Semantic Segmentation Model
    IEEE Sensors Journal 2022 DOI
  • S Chattopadhyay, Antoni Malachowski, Jaya Kumari Swain, Roy Ambli Dalmo, Alexander Horsch, Dilip K. Prasad :
    Mapping Functional Changes in the Embryonic Heart of Atlantic Salmon Post Viral Infection Using AI Technique
    Proceedings of IEEE International Conference on Image Processing 2022 DOI
  • Chen Xie, Deepu Rajan, Dilip K. Prasad, Chai Quek :
    An embedded deep fuzzy association model for learning and explanation
    Applied Soft Computing 2022 DOI
  • Ayush Somani, Arif Ahmed Sekh, Ida Sundvor Opstad, Åsa birna Birgisdottir, Truls Myrmel, Balpreet Singh Ahluwalia et al.:
    Virtual labeling of mitochondria in living cells using correlative imaging and physics-guided deep learning
    Biomedical Optics Express 2022 ARKIV / DOI
  • Zicheng Liu, Mayank Roy, Dilip K. Prasad, Krishna Agarwal :
    Physics-Guided Loss Functions Improve Deep Learning Performance in Inverse Scattering
    IEEE Transactions on Computational Imaging 2022 ARKIV / DOI
  • Divij Singh, Ayush Somani, Alexander Horsch, Dilip K. Prasad :
    Counterfactual Explainable Gastrointestinal and Colonoscopy Image Segmentation
    IEEE International Symposium on Biomedical Imaging 2022 ARKIV / DOI
  • Huixu Dong, Jiadong Zhou, Chen Qiu, Dilip K. Prasad, I-Ming Chen :
    Robotic Manipulations of Cylinders and Ellipsoids by Ellipse Detection With Domain Randomization
    IEEE/ASME transactions on mechatronics 2022 DOI
  • Sumit Rai, Arti Kumari, Dilip K. Prasad :
    Client Selection in Federated Learning under Imperfections in Environment
    AI 2022 ARKIV / DOI
  • S.W Jun, Arif Ahmed Sekh, Chai Quek, Dilip K. Prasad :
    seMLP: Self-evolving Multi-layer Perceptron in Stock Trading Decision Making
    SN Computer Science 2021 ARKIV / DOI
  • Ayush Somani, Divij Singh, Alexander Horsch, Dilip K. Prasad :
    T-MIS: Transparency Adaptation in Medical Image Segmentation
    Nordic Machine Intelligence (NMI) 2021 DOI
  • Arif Ahmed Sekh, Ida Sundvor Opstad, Gustav Godtliebsen, Åsa Birna Birgisdottir, Balpreet Singh Ahluwalia, Krishna Agarwal et al.:
    Physics-based machine learning for subcellular segmentation in living cells
    Nature Machine Intelligence 2021 ARKIV / DOI
  • Deepa Joshi, Ankit Butola, Sheetal Raosaheb Kanade, Dilip K. Prasad, Mithra Amitha Mithra, N.K. Singh et al.:
    Label-free non-invasive classification of rice seeds using optical coherence tomography assisted with deep neural network
    Optics and Laser Technology 2021 ARKIV / DOI
  • Jeow Li Huan, Arif Ahmed Sekh, Chai Quek, Dilip K. Prasad :
    Emotionally charged text classification with deep learning and sentiment semantic
    Neural Computing & Applications 2021 ARKIV / DOI
  • Hui Xue, Bjørn-Morten Batalden, Puneet Sharma, Jarle André Johansen, Dilip K. Prasad :
    Biosignal-Based Driving Skill Classification Using Machine Learning: A Case Study of Maritime Navigation
    Applied Sciences 2021 ARKIV / DOI
  • Suyog Jadhav, Sebastian Andres Acuña Maldonado, Ida Sundvor Opstad, Balpreet Singh Ahluwalia, Krishna Agarwal, Dilip K. Prasad :
    Artefact removal in ground truth deficient fluctuations-based nanoscopy images using deep learning
    Biomedical Optics Express 2021 ARKIV / DOI
  • Huixu Dong, Dilip K. Prasad, I-Ming Chen :
    Object Pose Estimation via Pruned Hough Forest with Combined Split Schemes for Robotic Grasp
    IEEE Transactions on Automation Science and Engineering 2021 DOI
  • Ayush Somani, Arif Ahmed Sekh, Ida Sundvor Opstad, Åsa Birna Birgisdottir, Truls Myrmel, Balpreet Singh Ahluwalia et al.:
    Digital Staining of Mitochondria in Label-free Live-cell Microscopy
    Springer 2021 DOI
  • Q.E. Zhe, Arif Ahmed Sekh, Chai Quek, Dilip K. Prasad :
    Recurrent Self-evolving Takagi–Sugeno–Kan Fuzzy Neural Network (RST-FNN) based Type-2 Diabetic Modeling
    Springer 2021 DOI
  • Pranab Kanti Roy, Hiranmoy Mondal, Ashis Mallick, Dilip K. Prasad :
    Inverse and efficiency of heat transfer convex fin with multiple nonlinearities
    Heat Transfer 2021 ARKIV / DOI
  • Soham Chattopadhyay, Laila Zary, Chai Quek, Dilip K. Prasad :
    Motivation detection using EEG signal analysis by residual-in-residual convolutional neural network
    Expert Systems With Applications 2021 ARKIV / DOI
  • Ratnabali Pal, Arif Ahmed Sekh, Debi Prosad Dogra, Samarjit Kar, Partha Pratim Roy, Dilip K. Prasad :
    Topic-based Video Analysis: A Survey
    ACM Computing Surveys 2021 FULLTEKST / ARKIV / DOI
  • Feng Liu, Arif Ahmed Sekh, Chai Quek, Geok See Ng, Dilip K. Prasad :
    RS-HeRR: a rough set-based Hebbian rule reduction neuro-fuzzy system
    Neural Computing & Applications 2020 ARKIV / DOI
  • Mohammad Ashrafi, Dilip K. Prasad, Chai Quek :
    IT2-GSETSK: An evolving interval Type-II TSK fuzzy neural system for online modeling of noisy data
    Neurocomputing 2020 ARKIV / DOI
  • Arif Ahmed Sekh, Ida Sundvor Opstad, Åsa Birna Birgisdottir, Truls Myrmel, Balpreet Singh Ahluwalia, Krishna Agarwal et al.:
    Learning nanoscale motion patterns of vesicles in living cells
    IEEE (Institute of Electrical and Electronics Engineers) 2020 ARKIV / DOI
  • Florian Ströhl, Suyog Jadhav, Balpreet Singh Ahluwalia, Krishna Agarwal, Dilip K. Prasad :
    Object detection neural network improves Fourier ptychography reconstruction
    Optics Express 2020 ARKIV / DOI
  • Ankit Butola, Daria Popova, Dilip K. Prasad, Azeem Ahmad, Anowarul Habib, Jean-Claude Tinguely et al.:
    High spatially sensitive quantitative phase imaging assisted with deep neural network for classification of human spermatozoa under stressed condition
    Scientific Reports 04. August 2020 ARKIV / DOI
  • Arif Ahmed Sekh, Debi Prasad Dogra, Samarjit Kar, Partha Pratim Roy, Dilip K. Prasad :
    Can We Automate Diagrammatic Reasoning?
    Pattern Recognition 2020 ARKIV / DOI
  • Ankit Butola, Sheetal Raosaheb Kanade, Sunil Bhatt, Vishesh Kumar Dubey, Anand Kumar, Azeem Ahmad et al.:
    High space-bandwidth in quantitative phase imaging using partially spatially coherent digital holographic microscopy and a deep neural network
    Optics Express 2020 ARKIV / DOI
  • Nirwan Banerjee, Samir Malakar, Deepak Kumar Gupta, Alexander Horsch, Dilip Kumar Prasad :
    Guided U-Net Aided Efficient Image Data Storing with Shape Preservation
    Springer 2023
  • Ayush Somani, Alexander Horsch, Dilip K. Prasad :
    Interpretability in Deep Learning
    Springer 2023
  • Rohit Agarwal, Ludwig Alexander Horsch, Dilip Kumar Prasad :
    Code - Modelling Irregularly Sampled Time Series Without Imputation
    2023
  • Rohit Agarwal, Ludwig Alexander Horsch, Dilip Kumar Prasad :
    Code - MABNET: Master Assistant Buddy Network for Image Retrieval
    2023
  • Huixu Dong, Jiadong Zhou, Chen Qiu, Dilip K. Prasad, I-Ming Chen :
    Learning-Based Ellipse Detection for Robotic Grasps of Cylinders and Ellipsoids
    2022
  • Xinqiang Chen, Xingyu Wu, Dilip K. Prasad, Bing Wu, Octavian Postolache, Yongsheng Yang :
    Corrections: Pixel-wise ship identification from maritime images via a semantic segmentation model (IEEE Sensors Journal (2022) 22:18 (18180-18191) DOI: 10.1109/JSEN.2022.3195959)
    IEEE Sensors Journal 2022 DOI
  • Rohit Agarwal, Krishna Agarwal, Alexander Horsch, Dilip K. Prasad :
    Auxiliary Network: Scalable and agile online learning for dynamic system with inconsistently available inputs
    2022 ARKIV
  • Divij Singh, Ayush Somani, Alexander Horsch, Dilip K. Prasad :
    Performance improvement in deep learning models for outdoor semantic segmentation for autonomous driving for unstructured environment
    2021
  • Dilip K. Prasad :
    Physics based AI - 101
    2021
  • Dilip K. Prasad :
    Performing physics-based AI for ground truth hard sub-cellular organelle segmentation using simulated expert
    2021
  • SW Pang, Chai Quek, Dilip K. Prasad :
    GEMM-eMFIS (FRI/E): A Novel General Episodic Memory Mechanism for Fuzzy Neural Networks
    2020 FULLTEKST / ARKIV
  • Ayush Singh, Ajay Bhave, Dilip K. Prasad :
    Single image dehazing for a variety of haze scenarios using back projected pyramid network
    2020 ARKIV
  • Arif Ahmed Sekh, Ida Sundvor Opstad, Åsa B. Birgisdottir, Truls Myrmel, Balpreet Singh Ahluwalia, Krishna Agarwal et al.:
    Learning Nanoscale Motion Patterns of Vesicles in Living Cells
    2020 ARKIV
  • Arif Ahmed Sekh, Krishna Agarwal, Dilip K. Prasad :
    Data-intelligence for microscopy data
    2020

    • The 50 latest publications is shown on this page. See all publications in Cristin here →

    Publications outside Cristin

    Journals: 


    J30. H. Dong, G. Sun, W.-C.Pang, E. Asadi, DK Prasad, and I-Ming Chen, "Fast ellipse detection via gradient information for robotic manipulation of cylindrical objects," IEEE Robotics and Automation Letters, vol .3, issue 4, pp. 2754-2761, 2018. 

    J29. H. Dong, DK Prasad, and I-Ming Chen, “Accurate detection of ellipses with false detection control at video rates using a gradient analysis,” Pattern Recognition, vol. 81, pp. 112-130, 2018. 

    J28. DK Prasad, S. Liu, S.-HA Chen, and C. Quek, "Sentiment Analysis Using EEG Activities for Suicidology," Expert Systems with Applications, vol. 103, pp. 206-217, 2018. 

    J27. K. Agarwal, R. Machan, and DK Prasad, "Non-heuristic automatic techniques for overcoming low signal-to-noise ratio bias of localization microscopy and multiple signal classification algorithm", Scientific Reports, vol. 8, article id 4988, 2018. 

    J26. AR Iyer, DK Prasad, and C. Quek, "PIE-RSPOP: A Brain-Inspired Pseudo-Incremental Ensemble Rough Set Pseudo-Outer Product Fuzzy Neural Network," Expert Systems With Applications, vol. 95, issue 4, pp. 172-189, 2018. 

    J25. K. Agarwal and DK Prasad, "Self-analysis reveals components supporting super-resolution imaging of blinking fluorophores", Scientific Reports, vol. 7, 2017. 

    J24. DK Prasad, D. Rajan, L. Rachmawati, E. Rajabally, and C. Quek, "Video Processing from Electro-Optical Sensors for Object Detection and Tracking in the Maritime Environment: A Survey," IEEE Transactions on Intelligent Transportation Systems, vol. . 18, issue 8, pp. 1993-2016, 2017. 

    J23. DK Prasad, D. Rajan, L. Rachmawati, E. Rajabally, and C. Quek, “MuSCoWERT: multi-scale consistency of weighted edge radon transform for horizon detection in maritime images,” Journal of Optical Society America A, vol. 33, issue 12, pp. 2491-2500, 2016. 

    J22. DK Prasad and K. Agarwal, “Classification of hyperspectral or trichromatic measurements of ocean color data into spectral classes”, Sensors, 16 (3), pp. 413, 2016. 

    J21. DK Prasad and Looi Wenhe, “Metrics and statistics of frequency of occurrence of metamerism in consumer cameras for natural scenes,” Journal of Optical Society America A, vol. 32, issue 7, pp. 1390-1402, 2015. 

    J20. DK Prasad, “Gamut expansion of consumer camera to the CIE XYZ color gamut using a specifically designed fourth sensor channel,” Applied Optics, vol. 54, issue 20, pp. 6146-6154, 2015. 

    J19. DK Prasad, Maylor KH Leung, Chai Quek and Michael S. Brown, “DEB: Definite error bound tangent estimator for digital curves,” IEEE Transactions on Image Processing, vol. 23, issue 10, pp. 4297-4310, 2014. 

    J18. D. Cheng, DK Prasad, and Michael S. Brown, "On Illuminant Estimation: Why Spatial Domain Methods Work and the Role of Color Distribution," Journal of Optical Society America A, vol. 31, issue 5, pp. 1049-1058, 2014. 

    J17. DK Prasad, and Michael S. Brown, “Design of macro-filter lens with simultaneous chromatic and geometric aberration correction,” Applied Optics, vol. 53, issue 1, pp. 32-37, 2014.

    J16. DK Prasad, “Fabrication imperfection analysis and statistics generation using precision and reliability optimization method,” Optics Express, vol. 21, issue 15, pp.17602-17614, 2013. 

    J15. DK Prasad, and Michael S. Brown, “Online tracking of deformable objects under occlusion using dominant points,” Journal of Optical Society America A, vol. 30, issue 8, pp.1484-1491, 2013. 

    J14. DK Prasad, Maylor KH Leung and Chai Quek, “ElliFit: An unconstrained, non-iterative, least squares based geometric Ellipse Fitting method,” Pattern Recognition, vol. 46, issue 5, pp. 1449-1465, 2013. 

    J13. DK Prasad, “PRO: A Novel Approach to Precision and Reliability Optimization Based on Dominant Point Detection,” Journal of Optimization, vol. 2013, Article ID 345287, 15 pages, 2013. 

    J12. DK Prasad, Maylor KH Leung, Chai Quek, and Siu-Yeung Cho, “A novel framework for making dominant point detection methods non-parametric,” Image and Vision Computing, vol. 30, issue 11, pp. 843-859, 2012. 

    J11. DK Prasad, Maylor KH Leung and Siu-Yeung Cho, “Edge curvature and convexity based ellipse detection method,” Pattern Recognition, vol. 45, issue 9, pp. 3204-3221, 2012. 

    J10. DK Prasad, “Survey of the Problem of Object Detection in Real Images,” International Journal of Image Processing, vol. 6, issue 6, pp. 441-466, 2012. 

    J09. DK Prasad, “Assessing Error Bound for Dominant Point Detection,” International Journal of Image Processing, vol. 6, issue 5, pp. 326-333, 2012. 

    J08. DK Prasad, Chai Quek, and Maylor KH Leung, “Fast Segmentation of Sub-Cellular Organelles,” International Journal of Image Processing, vol. 6, issue 5, pp. 317-325, 2012. 


    J07. A. Mallick, R. Ranjan, DK Prasad and Ranjan Das, "Inverse Prediction and Application of Homotopy Perturbation Method for Efficient Design of an Annular Fin with Variable Thermal Conductivity and Heat Generation", Mathematical Modeling and Analysis, vol. 21, issue 5. pp. 699-717, 2016. 

    J06. R. Ranjan, A. Mallick, and DK Prasad, "Closed form solution for a conductive-convective-radial annular fin with multiple nonlinearities and its inverse analysis," Heat and Mass Transfer, vol. 53, issue 3, pp. 1037-1049, 2017. 

    J05. R. Das and DK Prasad, “Prediction of Porosity and Thermal Diffusivity in a Porous Fin Using Differential Evolution Algorithm,” Swarm and Evolutionary Computation, vol 23, pp. 27-39, 2015. 

    J04. DK Prasad, “High Availability Based Migration Analysis to Cloud Computing for High Growth Businesses,” International Journal of Computer Networks, vol. 4, issue 2, 2012. 

    J03. A. Bowmik, R. K. Singla, P. K. Roy, D. K. Prasad, R. Das and R. Repaka, "Predicting geometry of rectangular and hyperbolic fin profiles with temperature-dependent thermal properties using decomposition and evolutionary methods," Energy Conversion & Management, vol. 74, pp. 535-547, 2013. 
    J02. DK Prasad, “Rise of International Schools in India,” International Journal of Education Economics and Development, vol. 4, no. 2, pp. 190-201, 2013. 
    J01. Janusz A. Starzyk and DK Prasad, “A Computational Model on Machine Consciousness”, International Journal of Machine Consciousness (World Scientific), vol. 3, issue 2, pp. 255-281, 2011. 

    Technology disclosure & licensing:

    DK Prasad, “Spatio-temporal registration of Image Streams” USA patent, (US 20180084226AI) 2018.

    DK Prasad, “Spatio-temporal registration of Image Streams” European patent, (EP17190114.3) 2018.

    Invention disclosure - N. Rang, DK Prasad, and MS Brown, "Raw-To-Raw Color Space Mapping" SG Provisional Patent (Application No. 10201402598Y), 2014. (licensing page)

    Invention disclosure - DK Prasad, "Spatio-temporal registration of independent sensors with approximately the same view / scene", 6th June 2016.

    Book Chapters

    1. DK Prasad and Maylor KH Leung, "Polygonal Representation of Digital Curves," Digital Image Processing, Stefan G. Stanciu (Ed.), InTech, 2012. 
    2. DK Prasad and Maylor KH Leung, "Methods for ellipse detection from edge maps of real images "in Machine Vision - Applications and Systems, Fabio Solari, Manuela Chessa and Silvio P. Sabatini (Ed.), InTech, 2012. 

     
    Conferences: 

    C32. H. Dong, DK Prasad, Q.Yuan, J.Zhou, E.Asadi, I-Ming Chen, "Efficient Pose Estimation from Single RGB-D Image via Hough Forest with Auto Context," IEEE / RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, October 1-5, 2018. 

    C31. H. Dong, G.Sun, W.-C.Pang, E.Asadi, DKPrasad, I-Ming Chen, "Fast Ellipse Detection for Robotic Manipulation of Cylindrical Objects," IEEE / RSJ International Conference on Intelligent Robots and Systems (IROS ), Madrid, Spain, October 1-5, 2018. 

    C30. A. Mallick, DK Prasad, and PP Behera. "Thermo-mechanical analysis of a radiative annular fin." AIP Conference Proceedings. Vol. 1988. No. 1st, 2018.

    C29. H. Dong, I-Ming Chen, and DK Prasad, “Robust Ellipse Detection Via Duality Principle With A False Determination Control,” International Conference on Computer Vision and Image Processing, Noida, India, September 9-12, 2017. 

    C28. H. Dong, I-Ming Chen, and DK Prasad, “Robust Ellipse Detection Via Arc Segmentation And Arc Classification,” International Conference on Image Processing (ICIP), Beijing, China, September 17-20, 2017. 

    C27. DK Prasad, C. K. Prasath, D. Rajan, L. Rachmawati, E. Rajabally, and C. Quek, “Maritime situational awareness using adaptive multisensory management under hazy conditions,” 5th International Maritime-Port Technology and Development Conference (MTEC 2017), Singapore, April 26-28, 2017.

    C26. DK Prasad, C. K. Prasath, D. Rajan, C. Quek, L. Rachmawati, and E. Rajabally, “Challenges in video-based object detection in maritime scenario using computer vision,” 19th International Conference on Connected Vehicles, Zurich, 13-14 January, 2017. 

    C25. DK Prasad, “Strategies for Resolving Camera Metamers Using 3 + 1 Channel,” IEEE International Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Las Vegas, USA, June 26 - July 1, 2016. 

    C24. DK Prasad, D. Rajan, C. Krishna Prasath, L. Rachmawati, E. Rajabally, and C. Quek, “MSCM-LiFe: Multi-Scale Cross Modal Linear Feature for Horizon Detection in Maritime Images,” IEEE TENCON, Singapore, Nov 22-25, 2016. 

    C23. R. Das and DK Prasad, Application of hybrid optimization algorithm for solving inverse problem in cylindrical fin, 7th International Conference on Computational Intelligence, Modeling and Simulation (CIMSim2015), Kuantan, Malaysia, 2015. 

    C22. N. Rang, DK Prasad, and MS Brown, “Training-Based Spectral Reconstruction from a Single RGB Image,” European Conference on Computer Vision (ECCV 2014), Zurich, Switzerland, September 6-12, 2014. 

    C21. N. Rang, DK Prasad, and MS Brown, “Raw-to-Raw: Mapping between Image Sensor Color Responses,” IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), Ohio, USA, June 24-27, 2014. 

    C20. DK Prasad, N. Rang, and MS Brown, “Quick Approximation of Cameras Spectral Response from Casual Lighting,” IEEE International Conference on Computer Vision Workshops (ICCVW 2013), Sydney, Australia, December 1-8, 2013. 

    C19. DK Prasad and C. Quek, “Comparison of Error Bounds for Non-Parametric Dominant Point Detection,” Ninth International Conference on Information, Communications, and Signal Processing (ICICS 2013), Tainan, Taiwan, December 10-13, 2013. 
    C18. DK Prasad, C. Quek, and MKH Leung, “A Precise Ellipse Fitting Method for Noisy Data,” International Conference on Image Analysis and Recognition (ICIAR 2012), Aveiro, Portugal, June 25-27, 2012.
    C17. Dilip K. Prasad, Chai Quek, and Maylor KH Leung, “A non-heuristic dominant point detection based on suppression of break points,” International Conference on Image Analysis and Recognition (ICIAR 2012), Aveiro, Portugal, June 25-27, 2012. 
    C16. Dilip K. Prasad, Chai Quek, Maylor KH Leung, and Siu-Yeung Cho, “A parameter independent line fitting method,” 1st IAPR Asian Conference on Pattern Recognition (ACPR 2011), Beijing, China, Nov 28-30, 2011. 

    C15. Dilip K. Prasad, “Adaptive traffic signal control system with cloud computing based online learning,” Eighth International Conference on Information, Communications, and Signal Processing (ICICS 2011), Singapore, December 13-16, 2011. 

    C14. Dilip K. Prasad, Raj K. Gupta and Maylor K. H. Leung, “An Error-Bounded Tangent Estimator for Digitized Elliptic Curves,” 16th IAPR International Conference on Discrete Geometry for Computer Imagery (DGCI 2011), Nancy, France, April 6-8, 2011. 

    C13. Dilip K. Prasad and Maylor K. Leung, “An ellipse detection method for real images,” 25th International Conference of Image and Vision Computing New Zealand (IVCNZ 2010), Queenstown, New Zealand, November 8-9, 2010. 

    C12. Dilip K. Prasad and Maylor K. H. Leung, “Error Analysis of Geometric Ellipse Detection Methods Due to Quantization,” Fourth Pacific-Rim Symposium on Image and Video Technology (PSIVT 2010), Singapore, November 14-17, 2010. 

    C11. Dilip K. Prasad and Maylor KH Leung, “An error bound tangent estimator for digital curves,” 25th International Conference of Image and Vision Computing New Zealand (IVCNZ 2010), Queenstown, New Zealand, November 8-9, 2010. 

    C10. Dilip K. Prasad and Maylor K. Leung, “Reliability / Precision Uncertainty in Shape Fitting Problems”, IEEE International Conference on Image Processing (ICIP 2010), Hong Kong, September 26-29, 2010. 

    C09. Dilip K. Prasad and Maylor K. H. Leung, “Clustering of Ellipses Based on Their Distinctiveness: An Aid to Ellipse Detection Algorithms,” 3rd IEEE International Conference on Computer Science and Information Technology (ICCSIT 2010), Chengdu, China, July 9-11, 2010. 
    C08. Dilip K. Prasad and Maylor K. Leung, “A Hybrid Approach for Ellipse Detection in Real Images,” 2nd International Conference on Digital Image Processing (ICDIP 2010), Singapore, February 26-28, 2010.

    C07. Dilip K. Prasad, “Application of Image Composition Analysis for Image Processing”, IMI International Workshop on Computational Photography and Aesthetics, Singapore, December 12-13, 2009.  (One page abstract & poster only)

    C06. Janusz A. Starzyk and Dilip K. Prasad, “Machine Consciousness: A Computational Model,” Third International ICSC Symposium on Models of Consciousness, BICS 2010, Madrid, Spain, July 14-16, 2010. 
    C05. Dilip K. Prasad and Janusz A. Starzyk, “A Perspective on Machine Consciousness,” Second International Conference on Advanced Cognitive Technologies and Applications, COGNITIVE 2010, Lisbon, Portugal, November 21-26, 2010. 
    C04. Dilip K. Prasad and Janusz A. Starzyk, "Object detection and representation in motivated conscious machines," Decade of the Mind - VI, Singapore, October 18-20, 2010. (3 Page Abstract & poster only)
    C03. Dilip K. Prasad and C. Krishna Prasath, “Reconfigurable Virtual Platform for Real Time Kernel,” 9th USENIX Symposium on Operating System Design and Implementation (OSDI 2010), Vancouver, BC, Canada, October 4-6, 2010. (acceptance rate ~ 16%) (Google Scholar H5 index = 39) (one page abstract, poster & demo only)
    C02. C. Krishna Prasath and Dilip K. Prasad, “Design and Development of a Real Time Kernel Reconfigurable Virtual Platform,” Second International Conference on Software Technology and Engineering (ICSTE 2010), San Juan, Puerto Rico, USA, October 3-5, 2010. 
    C01. Dilip K. Prasad, Chai H. Quek, and Maylor K. Leung, “A Hybrid Approach for Breast Tissue Data Classification,” IEEE TENCON 2009, Singapore, November 23-26, 2009. 

    Research interests

    • Sustainable AI
    • Scalable AI
    • Interpretable AI
    • Application of AI for life sciences.

    Teaching

    INF-3910-7 Computational Intelligence and its Applications

    INF-1101 Data structures and algorithms

    INF-2202 Concurrent and Data-Intensive Programming

    INF-2220 Cloud computing and big data technology

    INF-3605/8605 Interpretability in Deep Learning

    Researcher profile in Cristin
    ResearchGate
    ORCID: http://orcid.org/0000-0002-3693-6973

    Member of research group

    Center for Artificial Intelligence (CAI)   Norsk innhold

    Member of project

    VirtualStain    English content NanoAI    English content

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    Dilip K. Prasad (IEEE Senior Member) is an associate professor at the Department of Computer Science, UiT The Arctic University of Norway. He received the Ph.D and B.Tech degree in Computer Science and Engineering from Nanyang Technological University, Singapore and Indian Institute of Technology (Indian School of Mines), Dhanbad, India respectively. He was a senior research fellow at Nanyang Technological University, Singapore from 2015-2019 and research Fellow at National University of Singapore from 2012-2015. Prior to Ph.D., he has worked for 5 years with IBM, Infosys, Mediatek and Philips.He has been selected as a Fellow for Kauffman Global Scholarship in 2011, in which he was trained in entrepreneurship at Harvard University, MIT, Stanford University and the Kauffman Foundation. He has been awarded with Rolls-Royce Inventer Award in 2016. He has published 130+ internationally peer-reviewed research articles. His current research interests include image processing, machine learning and artificial intelligence. He has been a reviewer for more than 60 journals and 30+ conferences including CVPR, ICCV, ECCV, NIPS, AAAI, BMVC, WACV, ACCV, etc. He is area chair for NeurIPS 2022-23. He is a organizer chair for ICCV Workshop 2023 for "Resource Efficient Deep Learning".

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