Dr. Narinder Singh Punn

Teaching Research Fellow (TRF)

Indian Institute of Information Technology Allahabad,

Prayagraj, Uttar Pradesh, India

Email: pse2017002@iiita.ac.in / nspunn1993@gmail.com

Recent Activities

  1. Delivered a tutorial on “Unrevealing Data Correlations with Self-Supervised Learning” at the 26th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2022.
  2. A tutorial proposal entitled “Target Class Learning for Anomaly/Outlier Detection: a robust strategy” is accepted at the 26th International Conference on Pattern Recognition (ICPR) 2022.
  3. Selected among 200 young researchers to meet laureates in mathematics and computer science, and participate in the upcoming 9th Heidelberg Laureate Forum (2022).
  4. A tutorial proposal entitled “Software Testing and Quality Assurance for Data Intensive Applications” is accepted at the 25th  International Conference on Evaluation and Assessment in Software Engineering (EASE) 2022.
  5. A tutorial proposal entitled “Unrevealing Data Correlations with Self-Supervised Learning” is accepted at the 26th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2022.
  6. Delivered a tutorial on “Software Testing and Quality Assurance for Data Intensive Applications” at the 15th Innovations in Software Engineering Conference (ISEC) 2022.
  7. Our paper entitled “CHS-Net: A Deep learning approach for hierarchical segmentation of COVID-19 infected CT images.” is accepted for publication in Journal of Neural Processing Letters, Springer 2022.
  8. Our paper entitled “Modality specific U-Net variants for biomedical image segmentation: A survey.” is accepted for publication in Journal of Artificial Intelligence Reviews, Springer 2022.
  9. A tutorial entitled “A Tutorial on Biomedical Image Segmentation using Deep Learning” is accepted at the 27th International Conference on Database Systems for Advanced Applications (DASFAA) 2022.
  10. Our paper entitled “RCA-IUnet: A residual cross-spatial attention guided inception U-Net model for tumor segmentation in breast ultrasound imaging” is accepted for publication in the Journal of Machine Vision and Applications, Springer 2022.

Brief Biography

My name is Narinder Singh Punn and I am currently working as a Teaching Research Fellow (TRF) at the Indian Institute of Information Technology Allahabad (IIITA), Prayagraj, India. I completed my Bachelor’s degree in computer science and engineering from the National Institute of Technology Hamirpur (NITH) in 2015. I have 2 years of experience as a software developer at Intellect Design Arena Ltd., Chennai, India. Later, I joined a dual degree program (M.Tech. + Ph.D.) of IIITA in 2017 where I completed my Master’s degree with Software Engineering specialization in December 2019 and Doctorate of Philosophy in Information Technology in April 2022.

I am always fascinated by the potential of machine learning and deep learning algorithms and hence follows my research interest. I have published papers in international journals, conferences and preprint servers. My main research includes: Machine learning, Deep learning, Big data analytics and Data stream processing in healthcare and other domains. I have also gained outreach experience in delivering tutorial sessions and organizing several workshops and conferences on international platforms.

Publications

Journal:

  1. Punn, Narinder Singh, and Sonali Agarwal. “CHS-Net: A Deep Learning Approach for Hierarchical Segmentation of COVID-19 via CT Images.” Neural Processing Letters 2022: 1-22. [SCIE indexed, IF: 2.908]
  2. Punn, Narinder Singh, and Sonali Agarwal. “Modality specific U-Net variants for biomedical image segmentation: a survey.” Artificial Intelligence Review, 2022: 1573-7462. [SCI indexed, IF: 8.139]
  3. Punn, Narinder Singh, and Sonali Agarwal. “RCA-IUnet: a residual cross-spatial attention-guided inception U-Net model for tumor segmentation in breast ultrasound imaging.” Machine Vision and Applications 33, no. 2, 2022: 1432-1769. [SCIE indexed, IF: 2.012] 
  4. Punn, Narinder Singh, and Sonali Agarwal. “Automated diagnosis of COVID-19 with limited posteroanterior chest X-ray images using fine-tuned deep neural networks.” Applied Intelligence 51, no. 5, 2021: 2689-2702. [SCI indexed, IF: 5.086]
  5. Punn, Narinder Singh, and Sonali Agarwal. “Multi-modality encoded fusion with 3D inception U-net and decoder model for brain tumor segmentation.” Multimedia Tools and Applications 80, no. 20 2021: 30305-30320.  [SCIE indexed, IF: 2.757]
  6. Punn, Narinder Singh, and Sonali Agarwal. “Inception u-net architecture for semantic segmentation to identify nuclei in microscopy cell images.” ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) 16, no. 1, 2020: 1-15. [SCIE indexed, IF: 3.144]

Conference:

  1. Nagabhushan, P., Sanjay Kumar Sonbhadra, Narinder Singh Punn, and Sonali Agarwal. “Towards Machine Learning to Machine Wisdom: A Potential Quest.” In 9th International Conference on Big Data Analytics, pp. 261-275. Springer, Cham, 2021.
  2. Gupta, Sachin, Narinder Singh Punn, Sanjay Kumar Sonbhadra, and Sonali Agarwal. “MAG-Net: Multi-task Attention Guided Network for Brain Tumor Segmentation and Classification.” In 9th International Conference on Big Data Analytics, pp. 3-15. Springer, Cham, 2021.
  3. Rajput, Gaurav, Narinder Singh Punn, Sanjay Kumar Sonbhadra, and Sonali Agarwal. “Hate speech detection using static BERT embeddings.” In9th  International Conference on Big Data Analytics, pp. 67-77. Springer, Cham, 2021.
  4. Agrawal, Prachi, Narinder Singh Punn, Sanjay Kumar Sonbhadra, and Sonali Agarwal. “Impact of Attention on Adversarial Robustness of Image Classification Models.” In IEEE International Conference on Big Data (Big Data), pp. 3013-3019. IEEE, 2021. [Core rank: B]
  5. Sudhanshu, Narinder Singh, Punn, Sanjay Kumar Sonbhadra, and Sonali Agarwal. “Recommending best course of treatment based on similarities of prognostic markers.” In 28th International Conference on Neural Information Processing (ICONIP), pp. 393-404. Springer, Cham, 2021. [Core rank: B]
  6. Rajora, Harish, Narinder Singh Punn, Sanjay Kumar Sonbhadra, and Sonali Agarwal. “Machine learning equipped web based disease prediction and recommender system.” arXiv preprint arXiv:2106.02813, 2021. (accepted in MISP 2021)
  7. Batra, Himanshu, Narinder Singh, Punn, Sanjay Kumar Sonbhadra, and Sonali Agarwal. “BERT-Based Sentiment Analysis: A Software Engineering Perspective.” In 32nd International Conference on Database and Expert Systems Applications (DEXA), pp. 131-148. Springer, Cham, 2021. [Core rank: B] 
  8. Nasalwai, Nikhil, Narinder Singh Punn, Sanjay Kumar Sonbhadra, and Sonali Agarwal. “Addressing the Class Imbalance Problem in Medical Image Segmentation via Accelerated Tversky Loss Function.” In 25th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), pp. 390-402. Springer, Cham, 2021. [Core rank: A]
  9. Dandekar, Mohit, Narinder Singh, Punn, Sanjay Kumar Sonbhadra, and Sonali Agarwal. “Fruit classification using deep feature maps in the presence of deceptive similar classes.” In International Joint Conference on Neural Networks (IJCNN), pp. 1-6. IEEE, 2021. [Core rank: B]
  10. Sumanth, Uppala, Narinder Singh Punn, Sanjay Kumar Sonbhadra, and Sonali Agarwal. “Enhanced Behavioral Cloning-Based Self-driving Car Using Transfer Learning.” In 5th International Conference on Data Management, Analytics and Innovation (ICDMAI), pp. 185-198. Springer, Singapore, 2022. [h-index: 9]
  11. Chowdary, G. Jignesh, Narinder Singh Punn, Sanjay Kumar Sonbhadra, and Sonali Agarwal. “Face mask detection using transfer learning of inceptionv3.” In 8th International Conference on Big Data Analytics (BDA), pp. 81-90. Springer, Cham, 2020.
  12. Punn, Narinder Singh, Sonali Agarwal, Muhammad Syafrullah, and Krisna Adiyarta. “Testing big data application.” In 6th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI), pp. 159-162. IEEE, 2019. [h-index: 10]
  13. Punn, Narinder Singh, and Sonali Agarwal. “Crowd analysis for congestion control early warning system on foot over bridge.” In  12th International Conference on Contemporary Computing (IC3), pp. 1-6. IEEE, 2019. [h-index: 4]
  14. Punn, Narinder Singh, and Sonali Agarwal. “Testing Concept Drift Detection Technique on Data Stream.” In 6th International Conference on Big Data Analytics (BDA), pp. 89-99. Springer, Cham, 2018.

Book chapter:

  1. Punn, Narinder Singh, Sanjay Kumar Sonbhadra, and Sonali Agarwal. “COVID-19 epidemic analysis using machine learning and deep learning algorithms.” MedRxiv, 2020. (published as book chapter in AI and Data Science – Technology, Innovation & Use Cases in Indonesia 2021)

Pre-print/Upcoming:

  1. Punn, Narinder Singh, and Sonali Agarwal. “BT-Unet: A self-supervised learning framework for biomedical image segmentation using Barlow Twins with U-Net models.” arXiv preprint arXiv:2112.03916, 2021.
  2. Agarwal, Sonali, Narinder Singh Punn, Sanjay Kumar Sonbhadra, M. Tanveer, P. Nagabhushan, K. K. Pandian, and Praveer Saxena. “Unleashing the power of disruptive and emerging technologies amid COVID-19: A detailed review.” arXiv preprint arXiv:2005.11507, 2020.
  3. Punn, Narinder Singh, Sanjay Kumar Sonbhadra, and Sonali Agarwal. “Monitoring COVID-19 social distancing with person detection and tracking via fine-tuned YOLO v3 and Deepsort techniques.” arXiv preprint arXiv:2005.01385, 2020.

Achievements

Heidelberg Laureate Forum:

  1. Selected among 200 young researchers to meet laureates in mathematics and computer science, and participate in the upcoming 9th Heidelberg Laureate Forum (2022).
  2. Selected among 224 young researchers to meet laureates in mathematics and computer science, and participate in 8th Heidelberg Laureate Forum (2021).
  3. Selected and participated in the Virtual Heidelberg Laureate Forum to meet laureates in mathematics and computer science (2020).

Tutorial:

  1. Delivered a tutorial on “Unrevealing Data Correlations with Self-Supervised Learning” at the 26th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2022.
  2. Delivered a tutorial on “Software Testing and Quality Assurance for Data Intensive Applications” at the 15th Innovations in Software Engineering Conference (ISEC) 2022.
  3. Delivered a tutorial on “AI techniques to combat COVID-19” at the 28th International Conference on Neural Information Processing (ICONIP) 2021.
  4. Delivered a tutorial on “AI techniques to combat COVID-19” at the 8th IEEE International Conference on Data Science and Advanced Analytics (DSAA) 2021.

Honors and awards:

  1. Achieved best paper award for our paper published in the 5th International Conference on Data Management, Analytics and Innovation held online (2021).
  2. Achieved honor and appreciation for securing first position in poster presentation under the category of Masters in Technology at 2nd Researcher’s Day on National Science Day held at Indian Institute of Information Technology Allahabad, India (2019).
  3. Gem award winner for my contribution in webservices development in the field of financial transaction by the “Intellect Design Arena Limited”, Chennai, India (2016).

Talks:

  1. Delivered a talk in the International Conference on Computational Mathematics and its Applications, held at Indian Institute of Technology Indore (2019).
  2. Invited as speaker in Distributed Machine Learning for Big Data Workshop held at Universitas Budi Luhur, Jakarta, Indonesia (2019).

Outreach experience:

  1. Participated, presented and reviewed papers in the International Conference on Machine Intelligence and Signal Processing (MISP) held online at National Institute of Technology Arunachal Pradesh, India (2021).
  2. Participated and presented in the 28th International Conference on Neural Information Processing (ICONIP) held online at Indonesia (2021).
  3. Participated and presented in the 3rd International Conference on Machine Intelligence and Signal Processing (MISP) held online at India (2021).
  4. Participated and presented in the 32nd International Conference on Database and Expert Systems Applications, (DEXA) held online at Austria (2021).
  5. Participated and presented in the 25th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) held online at India (2021).
  6. Participated and presented in the 5th International Conference on Data Management, Analytics and Innovation (ICDMAI) held online at India (2021).
  7. Participated and presented in the 6th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI) held at Indonesia (2019).
  8. Participated and presented in the 12th International Conference on Contemporary Computing (IC3) held at Jaypee Institute of Information Technology at India (2019).
  9. Participated and presented in the 6th International Conference on Big Data Analytics (BDA) held at India (2018).
  10. Participated in the IEEE 12th International Conference on Industrial and Information Systems (ICIIS) held at Sri Lanka (2017).

Projects/Research assignments:

  1. Member of Technology Enabled Learning Environment (TEAL 2.O) on going project (2020-23) funded under European Union (EU), Erasmus (European Region Action Scheme for the Mobility of University students), Capacity building program.

Events organized/attended at IIITA:

  1. Participated, presented and member organizing committee in the 9th International Conference on Big Data Analytics (BDA) held at Indian Institute of Information Technology Allahabad, India (2021).
  2. Member organizing committee of the International Conference on Machine Intelligence and Signal Processing, held at Indian Institute of Information Technology Allahabad, India (2019).
  3. Participated in Faculty Development Programme on Data Sciences by AICTE Training and Learning Academy held at Indian Institute of Information Technology Allahabad, India (2019).
  4. Participated in the Global Initiative of Academic Networks (GIAN) course on Parallel and Distributed Data Stream Mining held at Indian Institute of Information Technology Allahabad, India (2017).
  5. Member organizing committee of IEEE CIS summer school at Indian Institute of Information Technology Allahabad, India (2019).

Other contributions:

  1. Active member of research group, Big Data Analytics lab at Indian Institute of Information Technology Allahabad, India.
  2. Guiding young minds (students) with keen interest towards deep learning technology to achieve their research goals.
  3. Developing tutorials for ease in understanding and hands-on experience with deep learning libraries.