M.Tech.(GNDU, Amritsar),
Ph.D.(GNDU, Amritsar)
Teaching Experience: 18 Years
1. Professor, Dept. of Computer Sceince & Technology, Central University of Punjab, Bathinda from 14 January 2023 to Till Date
2. Associate Professor, Central University of Punjab, Bathinda from 13 January 2020 to 13 Jan 2023
3. Assistant Professor, Central University of Punjab, Bathinda from 28 December 2015 to 12 January 2020
4. Assistant Professor, Baba Banda Singh Bahadur Engineering College, Fatehgarh Sahib from 11 August 2006 to 27 Dec 2015
5. Lecturer, Rayat Institute of Engineering & Information Technology, Railmajra, Nawanshahr from 23 July 2004 to 10 August 2006
Administrative Experience: 15 Years
Dean, School of Engineering & Technology since 30th May 2023
Member, Academic Council, Central University of Punjab Since March 2020.
Chairman, School Board, School of Engineering and Technology, Central University of Punjab
Head of Department, Computer Science & Technology, Central University of Punjab, Bathinda from March 2020 to 10th April 2023
Nodal Officer, Online Examination, Central University of Punjab, Bathinda from January 2017 to June 2021
Incharge, ERP Implementation, Baba Banda Singh Bahadur Engineering College, Fatehgarh Sahib from June 2014 to December 2015
Co-ordinator, Sikh Religion Examination(SRE)-2008(National Level Exam), Baba Banda Singh Bahadur Engineering College, Fatehgarh Sahib
Member, RDC Baba Banda Singh Bahadur Engineering College, Fatehgarh Sahib from December 2006 to December 2015
Dy. Incharge Examination, Rayat Institute of Engineering and Information Technology, Railmajra, Nawanshahr from January 2007 to August
Any Other Experience
Organised International Conferences in Years 2008, 2010, and 2012
Organised National Conferences and Seminars in Year 2014, 2015 and 2016
Co-ordinator of In-house Software Development in Central University of Punjab, Bathinda
Delivered Expert Talk and Key Note lectures in various International and National Conferences technical Sessions.
Big Data Analysis & Analytics
Data Sciences and Engineering
Software Engineering
Software Metrics of Object Oriented Systems
Machine Learning
Big data Analysis and Visualisation
Natural Language Processing
Text Analysis
1. Research Grant of Rs. 37 Lakh from ICMR, New Delhi as Principal Investigator for the project titled Big data Dashboard for Analysis and visualization of COVID DATA- An Indian Scenario project IRIS No/Proposal ID 2021-6329.
2. Research Project of Rs 6 lakh from the ICSSR as Co-PI for the project titled Effect of Blended learning on Pedagogy, Achievement Motivation and Academic Achievement of Class VIII Science student
3. Research Grant of Rs. 50000 for project Defect Prediction Model of Static Code Features for Cross-Company and Cross-Project Software sponsorship from Computer Society of India, Mumbai
4. Research Grant of Rs. 3,00,000 for project Cross Company Threshold Model for Software Faliure, Sponsored by Central University of Punjab, Bathinda
Member, Indian Society for Technical Education, New Delhi
Member , Institution of Engineers India, Kolkata (Member IEI, State Council, Punjab-Hry-Chandigarh)
Member, Computer Society of India, Mumbai
Best ISTE Section Teachers Awards-2014, Indian Society for Technical Education, New Delhi
Best ISTE Section Teachers Award 2017, Indian Society for Technical Education, New Delhi
Appreciation Award-2018 , Central University of Punjab, Bathinda
Papers:
Sharma, S., & Singh, S. (2021). Texture-Based Automated Classification of Ransomware. Journal of The Institution of Engineers (India): Series B, 102(1), 131-142.
Singh, R., & Singh, S. (2021). Text similarity measures in news articles by vector space model using NLP. Journal of The Institution of Engineers (India): Series B, 102(2), 329-338.
Singh, S., & Singla, R. (2021). Defect prediction model of static code features for cross-company and cross-project software. International Journal of Information Technology, 13(2), 667-675.
Itoo, F., & Singh, S. (2021). Comparison and analysis of logistic regression, Naïve Bayes and KNN machine learning algorithms for credit card fraud detection. International Journal of Information Technology, 13(4), 1503-1511.
Singh, S., & Beniwal, H. (2021). A survey on near-human conversational agents. Journal of King Saud University-Computer and Information Sciences.((in press)(IF 8.89)
Kanozia, R., Arya, R., Singh, S., Narula, S., & Ganghariya, G. (2021). A study on fake news subject matter, presentation elements, tools of detection, and social media platforms in India. Asian Journal for Public Opinion Research, 9(1), 48-82.
Singh, Y., Sanjay, K. S., Kumar, P., Singh, S., & Thareja, S. (2022). Molecular dynamics and 3D-QSAR studies on indazole derivatives as HIF-1α inhibitors. Journal of Biomolecular Structure and Dynamics, 1-18.(IF 5.23)
Fayaz, I., & Singh, S. (2020). Comparison and Analysis of Logistic Regression Naïive Bayes and KNN Machine Learning Algorithms for Credit Card Fraud Detection. International Journal of Information Technology, 1-9.
Kumar, A., Singh, S., & Kaur, G. (2019). Fake news detection of Indian and United States election data using machine learning algorithm.
Kumar, A., Singh, S., & Kaur, G. (2019). Analyzing And Detecting The Fake News Using Machine Learning.
Pundir, P., Singh, S., & Kaur, G. (2019). A Machine Learning Based Bug Severity Prediction using Customized Cascading Weighted Majority Voting.
Singh, S., & Singla, R. (2019). Object-Oriented Metrics for Defect Prediction. In Software Engineering (pp. 305-318). Springer, Singapore.
Kaur, A., & Singh, S. (2018). Detecting software bad smells from software design patterns using machine learning algorithms. International Journal of Applied Engineering Research, 13(11), 10005-10010.
Gautam, B., Tripathi, J., & Singh, S. (2018). A secure coding approach for prevention of SQL injection attacks. International Journal of Applied Engineering Research, 13(11), 9874-9880.
Reshi, J. A., & Singh, S. (2018). Predicting software defects through SVM: an empirical approach. arXiv preprint arXiv:1803.03220.
Singh, S., & Kaur, S. (2018). A systematic literature review: Refactoring for disclosing code smells in object oriented software. Ain Shams Engineering Journal, 9(4), 2129-2151.(IF 4.79)
Ali Reshi, J., & Singh, S. (2018). Investigating the role of code smells in preventive maintenance. Journal of Information Technology Management, 10(4), 41-63.
Singh, S., & Singla, R. (2017). Classification of defective modules using object-oriented metrics. International Journal of Intelligent Systems Technologies and Applications, 16(1), 1-13.
Kaur, S., & Singh, S. (2017). Prediction Model to Investigate Influence of Code Smells on Metrics in Apache Tomcat. International Journal of Advanced Research in Computer Science, 8(5).
Kumari, N., & Singh, S. (2017). improving smell prediction: Developing an Improved Model with Supervised Learning Techniques. Indian journal of science and technology, 10(24).
Kaur, J., & Singh, S. (2016). Neural network based refactoring area identification in software system with object oriented metrics. Indian Journal of Science and Technology, 9(10), 1-8.
Kaur, S., & Singh, S. (2015). Influence of anti-patterns on software maintenance: A review. International Journal of Computer Applications, IJCA Proceedings on International Conference on Advancements in Engineering and Technology 2015(2).
Kaur, H., & Singh, S. (2015). Analysis of CK metrics thresholds to predict faults using log transformation International Journal of Computer Applications , 74(2):1-4
Kumar, B., & Singh, S. (2015). Code clone detection and analysis using software metrics and neural network-a literature review. Complexity, 1(2), 3.
Kapila, H., & Singh, S. (2014). Bayesian inference to predict smelly classes probability in open source software. International Journal of Current Engineering and Technology, 4(3), 1724-1728.
Singh, S., & Kaur, R. (2014). Clone detection in UML class models using class metrics. ACM SIGSOFT Software Engineering Notes, 39(3), 1-3.
Kaur, R., & Singh, S. (2014). Clone detection in software source code using operational similarity of statements. ACM SIGSOFT Software Engineering Notes, 39(3), 1-5.
Singh, S., & Kahlon, K. S. (2014). Object oriented software metrics threshold values at quantitative acceptable risk level. CSI transactions on ICT, 2(3), 191-205.
Kumar, B., Singh, S., & Singh, P. (2014). Analysis of Code Clone Detection using Object Oriented System and Neural Network, International Journal of Engineering Research & Technology (IJERT), 3(9), 1386-1391.
Kapila, H., & Singh, S. (2013). Analysis of CK metrics to predict software fault-proneness using bayesian inference. International Journal of Computer Applications, 74(2).
Singh, S., Mittal, P., & Kahlon, K. S. (2013). Empirical model for predicting high, medium and low severity faults using object oriented metrics in Mozilla Firefox. International journal of computer applications in technology, 47(2-3), 110-124.
Mittal, P., Singh, S., & Kahlon, K. S. (2013). Empirical model for fault prediction using. object-oriented metrics in mozilla firefox. Int. J. Comput. Technol. Res, 1(6), 151-161.
Saberwal, H. K., Singh, S., & Kaur, S. (2013). Empirical Analysis Of Open Source System For Predicting Smelly Classes,‖ Inter. Journal of Engineering Research & Technology, 2(3), 1-6.
Kaur, S., Singh, S., & Kaur, H. (2013). A quantitative investigation of software metrics threshold values at acceptable risk level. International Journal of Engineering Research and Technology, 2(3), 1-7.
Singh, P., Singh, S., & Kaur, J. (2013). Tool for generating code metrics for C# source code using abstract syntax tree technique. ACM SIGSOFT Software Engineering Notes, 38(5), 1-6.
Singh, S., & Kahlon, K. S. (2012). Effectiveness of refactoring metrics model to identify smelly and error prone classes in open source software. ACM SIGSOFT Software Engineering Notes, 37(2), 1-11.
Singh, S., & Kahlon, K. S. (2011). Effectiveness of Refactoring Metrics Model to Identify Smells and Error Prone Classes in Open Source Software,‖ ACM SIGSOFT Soft. Engg. Notes, 36(5), 1-11.
Singh, S., & Kahlon, K. S. (2011). Effectiveness of encapsulation and object-oriented metrics to refactor code and identify error prone classes using bad smells. ACM SIGSOFT Software Engineering Notes, 36(5), 1-10.
Kaur, J., Singh, S., Kahlon, K. S., & Bassi, P. (2010). Neural network-a novel technique for software effort estimation. International Journal of Computer Theory and Engineering, 2(1), 17.
Singh, S., & Kahlon, K. S. (2010). Static Analysis To Model & Measure OO Paradigms. International Journal of Computer Applications, 975, 8887.
Kaur, A., Singh, S., Kahlon, K. S., & Sandhu, P. S. (2010). Empirical Analysis of CK & MOOD Metric Suit. International Journal of Innovation, Management and Technology, 1(5), 447.
Sharma, V., Singh, S., & Kahlon, K. S. (2009). Comparative Performance Study of Improved Heap Sort Algorithm on Different Hardware. Journal of Computer Science, 5(7), 476.
Kaur, A., Singh, S., & Kahlon, K. S. (2009). A metric framework for analysis of quality of object oriented design. Int J Comput Inf Eng, 3(12), 2875-2878.
Kaur, J., Singh, S., & Kahlon, K. S. (2008). Comparative analysis of the software effort estimation models. World Academy of Science, Engineering and Technology, 46, 485-487.
Sharma, V., Singh, S., & Kahlon, K. S. (2008). Performance study of improved Heap Sort algorithm and other sorting algorithms on different platforms. IJCSNS, 8(4), 101.
Sharma, V., Sandhu, P. S., Singh, S., & Saini, B. (2008). Analysis of modified heap sort algorithm on different environment. World Academy of Science, Engineering and Technology, 42.
Ph.D. Guided:
1. Sharanpreet Kaur IKG Punjab technical University 2019
2. Ramneet Kaur Guru Granth Sahib World University, Fatehgarh Sahib 2022
Ph.D. Guiding
1. Dilshad Kaur, Central University of Punjab, Bathinda
2. Seema Barda, Central University of Punjab, Bathinda
M.Tech Guided
1. Vandana Sharma, Performance comparison of modified heap sort with traditional sorting algorithms, 2009
2. Jasbinder Kaur, Comparative Analysis of the Software Effort Estimation Models, 2010
3. Amandeep Kaur, Evaluation and Metrication of Object Oriented System, 2010
4. Puneet Mittal, An Empirical Model for Fault Tolerance Analysis of OO Programing, 2012
5. Kamaljit Kaur, Comparative Analysis of Fault Predication Techniques for improving software process control, 2012
6. Harinder Kaur, Extended Maintenance Model for Open Source Object Oriented Softwares, 2012
7. Sarabjit Kaur, Quantitative Investigation of Threshold Values of Software Metrics, 2013
8. Harashpreet Kaur, Empirical Model of Object Oriented Software Metrics for prediction of Smelly Classes, 2013
9. Pavitdeep Singh, A Hybrid Approach for Code Clone Detection Using Combination of AST Metrics, 2013
10. Heena Kapila, Bayesians Analysis Of Software Fault Prediction for Preventive Maintenance, 2013
11. Raminder Kaur, Clone Detection in Software Design and Source Code, 2014
12. Mandeep Singh, Software Productivity Empirical Model for Early Estimation of Development, 2014
13. Kanwalpreet Kaur, Optimized test Case Prioritization With Multi Criteria for Regression Testing, 2014
14. Ranjna Garg, Identifying Clone Based Refactoring Area with Object Oriented Metrics Approach, 2014
15. Navneet Choudhary, Enhancing CK Managerial Model of Design Effort Using Object Oriented Design Metrics, 2014
16. Jasmeet Kaur, Reducing Time to Market of Software with Time Duration Empirical Model, 2014
17. Balwinder Kumar, Analysis of Code Clone Detection of OO System Using FF Neural Network, 2015
18. Rozy Singla, Classification Of Fault-Prone Modules Using Object-Oriented Metrics, 2015
19. Kamaljeet Kaur, Enhancement in A-KNN Clustering technique to analyse Software Architecture, 2015
20. Sukhjeet kaur, Software System Analysis with K-Means Clustering Techniques,2016
21. Shivani gautam, Estimating Project Development Effort Using Clustered Regression Approach, 2016
22. Jaspreet Kaur, Neural Network Based Refactoring Area Identification in software System with OO Metrics,2016
23. Ramanpreet Kaur, Effort Estimation for Corrective software maintenance, 2016
24. Virjot Kaur, “Detection of Vampire Attacks in Wireless Sensor Networks”, August 2016.
25. Priyanka Rani, “Prevention of DRDOS Attacks on Web Log files Using Supervised Neural Network”. August 2016
26. Paras Nath Singh, Secure Data Aggregation With Malicious Aggregator Identification in WSN Using Watermarking, August 2016.
27. Akhlinder Singh Yadav, “Secure Data Communication Using Network Protocol in IPV6’s Flow Label Field”. August 2016
28. Brijesh Kumar, “ An improved Wavelet Transformation Based Stegnography Technique to Hide Audio Signal in Image”. September 2016
29. Neha Kumari, “Improving Smell Prediction: Developing an Improved Model with Supervised Learning Technique”, September 2017.
30. Gunseerat Kaur, “Anomaly Detection and Classification in SSL, UDP and HTTP connection using Machine Learning Algorithm”. September 2017.
31. Pooja Awana Choudhary, “Neural Network Based Bug Priority Prediction Model Using Code Extraction Features” , September 2017..
32. Shaitan Singh Meena, “Threshold Design for Cohesion and Coupling Metrics with Quantitative Analysis”. September 2017.
33. Junaid Ali Reshi, “ Software Defect Prediction Through Machine Learning Based Smell Prediction Models”. September 2017.
34. Avneet kaur,”Comparison of Maintenance Activities for Cost Estimation in an Open Source Software Projects”, September 2017.
35. Usurumati Vinod Kumar,”Predicting Software Faults Using Bayesian Network Classifier Algorithm”, September 2017.
36. Amarpreet Kaur,”Defect Prediction by Pruning Redudancy in Association Rule Mining”, September 2017.
37. Niveda Pareck, “Identification of Threshold adaptation for Object Oriented Software Metrics”, September 2017.
38. Akashdeep Kaur, “Detection of Software Code Smells from Software Design Patterns Using Machine Learning Algorithms”, May 2018.
39. Mir Mohammad Yousuf, “Analysis of the Change of Bugginess and Adaptiveness of Python Software Systems”. May 2018.
40. Moha Gupta, “Detection of Design Patterns from Design Metrics Using Machine Learning Algorithm”, May 2018.
41. Jyotiraditya Tirpathi, “Detection and Removal of XSS Vulnerabilities with the help of Genetic Algorithm”. May 2018.
42. Bhawna Gautam, “ A secure Coding Approach for prevention of SQL Injection Attack”. May 2018.
43. Meenakshi, An Approach to Software Testing and Analysis of Bugs in Agile Methodology, Central University of Punjab, May 2019
44. Dhwani Aggarwal “Analysis of Software Effort Estimation Techniques: Issues and problems”, Central University of Punjab, May 2019
45. Irshad Alam, Evaluation Of India Most Visited Websites In Aspects Of Security And Structure, Central University of Punjab, May 2019
46. Abhishek Kumar, A Method For Minimization Of Deterministic Finite Automata Obtain From Given Regular Grammar, Central University of Punjab, May 2019
47. Prachi Pundhir, A machine learning Approach for Bug Severity prediction using customized cascading weighted Majority Voting, Central University of Punjab, May 2019
48. Rabish Ranjan, Detection and Mitigation of subdomain Hijacking Attacks, Central University of Punjab, June 2019
49. Ashutosh Kumar Anajan, Capturing Attacks on IoT protocols with a multipurpose Honeypot, Central University of Punjab, June 2019
50. Rajat Bhardwaj, Address Resolution Protocol: Spoofing attack and detection, Central University of Punjab, June 2019
51. Vibhuti Kumari, Twitter Sentiment Analysis Using Machine Learning, Central University of Punjab, May 2020
52. Ritika Singh “Comparative Analysis Of Text Similarity Measures In News Articles”, Central University of Punjab, May 2020
53. Abdul Wahab Rehmani, Comparative Analysis Of Intrusion Detection Model Using Machine Learning Algorithms On Big Data Environment, Central University of Punjab, May 2020
54. Shreya Suman, Fake News Detection Using NLP, Central University of Punjab, May 2020
55. Himani, Sentiment Analysis of Online reviews using Deep learning Approaches, Central University of Punjab, May 2020
56. Harpreet Kaur, Twitter Sentiment Analysis on Abrogation of Article370, Central University of Punjab, May 2020
57. Mehraj U Din Bhat, Automatic method to rate websites on the basis of terms of services, Central University of Punjab, May 2020
58. Sagarika Paul, Soil Moisture Prediction Using Machine Learning Techniques, Central University of Punjab, June 2020
59. Anukriti Srivastav, Proposed Model For Context Topic Identification of English and Hindi News Article through LDA approach, Central University of Punjab, May 2020
60. Shubham Sharma, An approach to detect ransomeware by texture based automated classifier, Central University of Punjab, May 2020
61. P P Ambili, Analysis And Implementation Of Blockchain In Disaster Relief, Central University of Punjab, May 2020
62. Rupali, Optimization of Sentiment Analysis using Machine Learning approaches, Central University of Punjab, May 2020
63. Himanshu Beniwal A Near Human Chatbot in Conversational AI, Central University of Punjab, July 2021
64. Aswin P., A Systematic approach for Speech to Text Translation and Summarization, Central University of Punjab, July 2021
65. Aamir Ali, Analyzing Peer Reviews of Scientific Papers based on Sentiment Analysis, Central University of Punjab, July 2021
66. Mudhasir Jallal, BugClassification Depend Upon Refactoring Area of Code, Central University of Punjab, July 2021
67. Nehalika Neha, Bug Classification based on its Severity using Machine Learning Algorithm, Central University of Punjab, July 2021
68. Sayed Muzafar Ahmad Shah, Hate and Offensive speech detection in Twitter data using Natural Language Processing,Central University of Punjab, July 2022
69. Harimohan Dixit, EFFECTIVENESS OF COVID 19 VACCINATION AND ITS SYMPTOMS, Central University of Punjab, July 2022
70. Asadullah, Phishing Website Detection Using URLs Features, Central University of Punjab, July 2022
71. Samar Ansh, Analyze Dark Web and Security Threats, Central University of Punjab, July 2022
72. Shalini Singh, Effective Analysis of Chatbot Framework: Rasa and Dialogflow, Central University of Punjab, July 2022
73. Amir Husain, A Study on the Relationship between Design and Architecture Smells, Central University of Punjab, July 2022
74. Aquib Azhar, Face Mask Detection System using deep neural network-based face detector and MobileNetV2, July 2022
75. Md. Majid Reja, Comparison of Public and Critic's Opinion About Taliban Government Over Afghanistan Through Sentiment Analysis, Central University of Punjab, July 2022.
76. Krishna Kumar,Multi-Class Classification of Image Documents Using Deep Learning Approach, Central University of Punjab, June 2023.
77. Arshdeep Kaur, Prediction of Alzheimer’s Disease Based on Combined Biomarkers, Central University of Punjab, June 2023.
78. Abhilasha Yadav,Exploration of Potential miRNA Biomarker and Prediction for Female Cancer Using Machine Learning, Central University of Punjab, June 2023.
79. Munish Kumar, Development and Classification of Image Dataset for Text To Image Generation, June 2023.
University Level 10
National 10
International 8
University Level
National Level 03
International Level 01
PATENT GRANTED: 01(INTERNATIONAL)
PATENT PUBLISHED : 01 (NATIONAL)
COPYRIGHT GRANTED: 04
Scopus
Citation-306
h-index: 08
Google Scholar
Citation: 782
h-index: 15