Dr. Tajinder Singh
Computer Science & Engineering
Ph.D entitled “Machine Learning Based Text Mining in Social Media” from National Institute of Technology, Hamirpur, India.
Assistant Professor in Department of Computer Science & Engineering and Technology, at SLIET Longowal, Punjab from 20th November 2020 to Till Date.
Worked as Assistant Professor Grade II (Level 11) in the area of Information Technology & Systems at Indian Institute of Management Kashipur, Uttrakhand, India
Worked as Assistant Professor at St. Apostle The University of Information Sciences and Technology, Ohrid, Macedonia.
Worked as Assistant Professor in the department of Computer Science & Engineering at Chandigarh University, Gharuan, Mohali, Ounjab, India.
Selected Book Chapters
1. Tajinder Singh, Madhu Kumari, Daya Sagar Gupta, Nikolai Siniak, “Axiomatic Analysis of Pre-processing Methodologies using Machine Learning in Text Mining: A Social Media Perspective in the Internet of Things”, ,Wiley, A Social Media Perspective in Internet of Thing, pp.229-256,2023.
2. Tajinder Singh, Madhu Kumari, Machine Learning-Based Text Mining in Social Media for COVID-19, CRC Press, Computational Modeling and Data Analysis in COVID-19 Research, pp.1-32, 2021.
3. Deepti Rani, Anju Sangwan, Anupma Sangwan, Tajinder Singh, Machine Learning Techniques for Underwater Wireless Sensor Networks: A Comprehensive Study, IGI Global, Energy-Efficient Underwater Wireless Communications and Networking, pp.194-211, 2021. DOI: 10.4018/978-1-7998-3640-7.ch013
4. Tajinder Singh, Madhu Kumari, How Do Clustering Help Us with Better Understanding in Social Text Streams: Data clustering and classification with ML and DL, CRC Press, Security and Risk Analysis for Intelligent Cloud Computing, 2023 (Accepted).
Member of IEEE
Selected Publications in journals
1. Burst: Real time event burst detection in social text streams, T Singh, M Kumari – The Journal of Supercomputing, Springer, 2021, (SCIE).
2. Daya Sagar Gupta, Sangram Ray, Tajinder Singh, Madhu Kumari, Post-quantum lightweight identity-based two-party authenticated key exchange protocol for Internet of Vehicles with probable security, Computer Communications, Elsevier, 2021, (SCI).
3.Ranjeet Kaur, Yogesh Kumar Sharma, Tajinder Singh, Measuring Accuracy of Stock Price Prediction Using Novel Hybrid Model – A Machine Learning Classifier, , Ciencia e Technia, 2021, (SCI).
4. Tajinder Singh, Madhu Kumari, Daya Sagar Gupta, Real-time Event Detection and Classification in Social Text Steam using Embedding, Cluster Computing, Springer, 2022, (SCI).
5. Ranjeet Kaur, Supreet Kaur, Tajinder Singh, Measuring Accuracy and analysis of Stock Price Prediction using various Machine Learning Classifiers, Jounal of Xidian Unicersity, 2020, (SCOPUS).
6. Mohammad Ahsan, MadhuKumari, Tajinder Singh, Triveni Lal Pal, Sentiment based information diffusion in online social networks, International Journal of Knowledge Discovery in Bioinformatics (IGI Global), 2018, (SCOPUS).
7. Triveni Lal Pal, Madhu Kumari, Tajinder Singh, Mohammad Ahsan, Semantic Representations in Text Data, International Journal of Grid and Distributed Computing, 2018, (ESCI, SCOPUS).
8. Tajinder Singh, Madhu Kumari, Shweta Mahajan, Feature oriented fuzzy logic based web spam detection, Journal of Information and Optimization Science (Taylor and Francis), 2018, (ESCI, SCOPUS).
9. Tajinder Singh, MadhuKumari, Triveni Lal Pal, Ahsan Chauhan, Current trends in text mining for social media, International Journal of Grid and Distributed Computing, 2017, (ESCI, SCOPUS).
SELECTED PUBLICATIONS IN INTERNATIONAL CONFERENCES
1. Amar Nath, Rajdeep Niyogi, Tajinder Singh, Multi-agent Deep Q-learning based Navigation, The 37-th International Conference on Advanced Information Networking and Applications (AINA-2023) (Accepted).
2. Tajinder Singh, Amar Nath, Rajdeep Niyogi Ramification of sentiments on robot-based smart agriculture: An analysis using real-time tweets’ The 37-th International Conference on Advanced Information Networking and Applications (AINA-2023)
3. Amar Nath, Rajdeep Niyogi, Tajinder Singh,Virendra Kumar, Multi-Agent Q-learning based Navigation in an Unknown Environment, The 36-th International Conference on Advanced Information Networking and Applications (AINA-2022).
4. Naman Goyal, Major Singh, Tajinder Singh, An axiomatic analysis for object detection and recognition using Deep learning, International Conference on Human-Centric Smart Computing, ICHCSC-2022, (SCOPUS).
5. Tajinder Singh, Madhu Kumari, Amar Nath, Rajeev Bedi, Nikolai Siniak, Event tracking and analysis in social media text stream, 7th International Conference on Advanced Computing and Intelligent Engineering, 2022 (SCOPUS).
6. Madhu Kumari, Tajinder Singh, Food Image to Cooking Instructions Conversion Through Compressed Embeddings Using Deep Learning, IEEE 35th International Conference on Data Engineering Workshops (ICDEW), 2019.
7. Tajinder Singh, Madhu Kumari, Role of text pre-processing in twitter sentiment analysis, Role of text pre-processing in twitter sentiment analysis, Procedia Computer Science, 2016.
8. M. Ahsan, Tajinder Singh, M. Kumari, “Influential node detection in social network during community detection,” 2015 International Conference on Cognitive Computing and Information Processing (CCIP), 2016, pp. 1-6.
Area of Specialization
Artificial Intelligence, Machine Learning, Text Analytics, Online Social Text Stream Analysis and E-Commerce.
Principal Investigator: Dr. Tajinder Singh
Amount Sanctioned: 5 Lac
Project Title: “TDA: Deep Learning for Threat, Derogation, Animosity Detection in social media”, Project under seed grant OF SLIET, Longowal.
Total Journal Paper Published: 13
Total International Conference Paper Published/Accepted: 8
Total Book Chapters: 4
Faculty Development Programme (FDP) Attended: 10
Invited Lectures/Talks: 05
MOOCs – Online Certifications: Qualified First phase training (08 Modules) of AICTE – National Initiative for Training of Technical Teachers (NITTT) | Coordinating Institute: NITTTR Chennai.
M.Tech Thesis Guided: 01
Thesis Title: A Deep Learning based model for human action recognition in the video sequences
PhD. Guided/Ongoing: 01
Area of research: Deep Learning
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