Fully Funded by Ministry of Education, Govt. of India

शिक्षा मंत्रालय, भारत सरकार द्वारा वित्त पोषित

Dr. Santosh Singh Rathore

Dr. Santosh Singh Rathore

Designation: Assistant Professor

Department: Computer Science

Honour: Ph.D. (IIT Roorkee)

Area of Interest: Predictive Modeling in Software Engineering, Software Fault Prediction, Empirical Software Engineering, Applied Machine Learning, Web Services

Office Phone : +91-9407203020

Residence Phone: +91-9407203020

Address: Room No. 214, F-Block, ABV-IIITM, Morena Link Road, Gwalior-474015 (M.P.)

Email: santoshs@iiitm.ac.in, santosh.srathore@gmail.com

Website: https://sites.google.com/site/santoshiiitmdj/home?

Biography

Professional Experience

  1. Assistant Professor, Indian Institute of Information Technology and Management, Gwalior, March. 2019 to present.
  2. Assistant Professor, Computer Science and Engineering Department, NIT Jalandhar, India, Jan 2018- March 2019
  3. Assistant Professor, Computer Science and Engineering Department, Thapar University, India, July 2017-Jan 2018

 

Academic Credentials

Ph.D.: Indian Institute of Technology Roorkee, 2017.

M.Tech.: Indian Institute of Information Technology Design and Manufacturing Jabalpur,  2013.

B.E.: NRIITM College Gwalior, Under R.G.P.V. University, Bhopal, 2010.

 

 

Sponsored Projects-

1. Title: Artificial Intelligence Enabled Dialogue based Online Medical System Development for Precision Healthcare

Role: Principal Investigator
Funding Agency: DST- SERB, Start-Up Research Grant, Govt. of India, (2021-23)
Amount: 15,43,344/-


2. Title: AUTOEMR: An AI-based System for Generating Structured Medical Information
Role: Principal Investigator
Funding Agency: TIIC, ABV-IIITM Gwalior, (2021-22)
Amount: 3,00,000/-


3. Title: Design of NextGen Hearing Aids
Role: Co-Principal Investigator
Funding Agency: TIIC, ABV-IIITM Gwalior, (2021-22)
Amount: 3,00,000/-

4. Title: Inferring High-level Code Similarities in Software System using String-Metric based Hybrid Technique
Role: Co-Principal Investigator
Funding Agency: Grant for R & D proposal, TEQIP-III, Dr. B. R. Ambedkar, NIT Jalandhar (2018-19)
Amount: 3,00,000/-

Book-

  1. Santosh Singh Rathore and Sandeep Kumar, "Fault Prediction Modeling for the Prediction of Number of Software Faults", SpringerBrief in Computer Science, Springer Singapore, DOI: https://doi.org/10.1007/978-981-13-7131-8.
  2. Sandeep Kumar and Santosh Singh Rathore, "Software Fault Prediction; A Road Map", SpringerBrief in Computer Science, Springer Singapore, DOI: 10.1007/978-981-10-8715-8.

 

Referred Journals -

  1. Surendra S. Gangwar, Santosh Singh Rathore, Satyendra Singh Chouhan, Sanskar Soni, "Predictive modeling for suspicious content identification on Twitter", In Social Network Analysis and Mining, vol. 12, no. 1, pp. 1-13, Springer, 2022.
  2. Lalit Purohit, Santosh Singh Rathore, Sandeep Kumar, "Feature selection and clustering based web service selection using qoSs", In Applied Intelligence, Springer, 2022.
  3. Saurabh Tiwari and Santosh Singh Rathore, "Understanding general concepts of requirements engineering through design thinking: An experimental study with students", In Computer Applications in Engineering Education, Wiley, 2022.
  4. Nalin Singh, Santosh Singh Rathore, and Sandeep Kumar, "Towards a Super-Resolution based Approach for Improved Face Recognition in Low-Resolution Environment", In Multimedia Tools and Applications, Springer (Accepted), 2022.
  5. Debanjan Sadhya, Santosh Singh Rathore, Amitesh Singh Rajput, and Abhinav Anand, "Securing Multimedia Videos Using Space-Filling Curves", In Multimedia Tools and Applications, Springer (Accepted), 2022.
  6. Santosh Singh Rathore, Satyendra Singh Chouhan, Dixit Kumar Jain, and Aakash Gopal Vachhani, "Generative Oversampling Methods for Handling Imbalanced Data in Software Fault Prediction", In IEEE Transactions on Reliability, 2022, DOI: 10.1109/TR.2022.3158949 (in early access).
  7. Rohit Singh and Santosh Singh Rathore, "Linear and Non-Linear Bayesian Regression Methods for Software Fault Prediction", In International Journal of System Assurance Engineering, 2021, DOI: 10.1007/s13198-021-01582-1.
  8. Santosh Singh Rathore, "An exploratory analysis of regression methods for predicting faults in software systems", In Soft Computing, Springer, 2021, https://doi.org/10.1007/s00500-021-06048-x. Paper is also available here.
  9. Santosh Singh Rathore and Sandeep Kumar, "Software Fault Prediction based on the Dynamic Selection of Learning Technique: Findings from the Eclipse Project Study", In Applied Intelligence, 2021, https://doi.org/10.1007/s10489-021-02346-x. Paper is also available here.
  10. Satyendra S. Chouhan and Santosh S. Rathore, "Generative Adversarial Networks-Based Imbalance Learning in Software Aging-Related Bug Prediction", In IEEE Transaction on Reliability, 2021, vol. 99, pp. 1-19, DOI: 10.1109/TR.2021.3052510. Paper is also available here.
  11. Gaurav Yadav, Santosh Singh Rathore, and Debanjan Sadhya, ''Named entity recognition for weather domain text in Hindi'', International Journal of Swarm Intelligence, 2021. DOI: 10.1504/IJSI.2021.118623.
  12. Santosh Singh Rathore and Sandeep Kumar, "An empirical study of ensemble techniques for software fault prediction", In Applied Intelligence, 2020, pp. 1-30, DOI: https://doi.org/10.1007/s10489-020-01935-6. Paper is also available here.
  13. Santosh S. Rathore and Sandeep Kumar, " An Approach for the Prediction of Number of Software Faults Based on the Dynamic Selection of Learning Techniques", In IEEE Transaction on Reliability, 2018, DOI: 10.1109/TR.2018.2864206. Paper is also available here.
  14. Santosh S. Rathore and Sandeep Kumar, "A Study on Software Fault Prediction Techniques", In AI review, Springer, 2017, DOI https://doi.org/10.1007/s10462-017-9563-5. Paper is also available here.
  15. Santosh S. Rathore and Sandeep Kumar, "Linear and non-linear heterogeneous ensemble methods to predict the number of faults in software systems," In Knowledge-Based Systems, Elsevier, vol. 119, pp. 232-256, 2017. Paper is also available here.
  16. Santosh S. Rathore and Sandeep Kumar, "Towards an Ensemble Based System for Predicting the Number of Software Faults," In Expert Systems with Applications, Elsevier, vol. 82, pp. 357-382, 2017. Paper is also available here.
  17. Santosh S. Rathore and Sandeep Kumar, "An empirical study of some software fault prediction techniques for the number of faults prediction," In Soft Computing, vol. 21, no. 24, pp. 7417-7434, Springer, 2016. Paper is also available here.
  18. Santosh S. Rathore and Sandeep Kumar, "A decision tree logic based recommendation system to select software fault prediction techniques," In Computing, vol. 99, no. 3, pp. 255-285, Springer, 2016. Paper is also available here.

Referred Conferences

  1. Saurabh Tiwari, Santosh Rathore, Sudhanshu Gupta, Vaibhav Gagote, and Atul Gupta. Analysis of Use Case Requirements using SFTA and SFMEA Techniques. In proceeding of 17th International Conference on Engineering of Complex Computer Systems (ICECCS), 2012, vol., no., pp.29-38, Paris - France, 18-20 July 2012. DOI: 10.1109/ICECCS.2012.10.
  2. Santosh Singh Rathore and Atul Gupta. Validating the Effectiveness of Object-Oriented Metrics over Multiple Releases for Predicting Fault Proneness. In proceeding of 19th Asia Pacific Software Engineering Conference (APSEC'12), Hongkong, pp 270-275, 4-7 Dec 2012. DOI: 10.1109/APSEC.2012.148.
  3. Saurabh Tiwari, Santosh Singh Rathore, Abhinav Singh, Abhijeet Singh, and Atul Gupta. An Approach to Generate Actor-Oriented Activity Charts from Use Case Requirements. In proceeding of 19th Asia Pacific Software Engineering Conference (APSEC'12), Hongkong, pp 350-355, 4-7 Dec 2012 DOI: 10.1109/APSEC.2012.149.
  4. Santosh Singh Rathore and Atul Gupta. Investigating Object-Oriented Design Metrics to Predict Fault-Proneness of Software Modules. In proceeding of 6th International Conference on Software Engineering (CONSEG'12), Indore-India, 5-7 Sep 2012. DOI: 10.1109/CONSEG.2012.6349484.
  5. Saurabh Tiwari, Santosh Singh Rathore, and Atul Gupta. Selecting Requirement Elicitation Techniques for Software Projects. In proceeding of 6th International Conference on Software Engineering (CONSEG'12), Indore-India, 5-7 Sep 2012.
  6. Santosh Singh Rathore and Atul Gupta. A Comparative Study of Feature-Ranking and Feature-Subset Selection Techniques for Improved Fault Prediction. In proceeding of 7th India Software Engineering Conference (ISEC'14), Chennai-India, 19-21 Feb 2014. DOI: http://dx.doi.org/10.1145/2590748.2590755 .
  7. Santosh Singh Rathore and Sandeep Kumar. Predicting Number of Faults in Software System using Genetic Programming. In Proceedings of 2015 International Conference on Soft Computing and Software Engineering (SCSE'15), the University of California, Berkeley, USA. DOI:10.1016/j.procs.2015.08.454.
  8. Santosh Singh Rathore and Sandeep Kumar. A Decision Tree Regression based Approach for the Number of Software Faults Prediction. In SIGSOFT Software Engineering Notes, vol. 41, no. 1 (February 2016), pages 1-6.
  9. Santosh Singh Rathore and Sandeep Kumar. Ensemble Methods for the Prediction of Number of Faults: A Study on Eclipse Project. In proceeding of ICIIS 2016 conference, held at IIT Roorkee, Dec 3-4, 2016.
  10. Saurabh Tiwari and Santosh Singh Rathore. Coupling and Cohesion Metrics for Object-Oriented Sofware: A Systematic Mapping Study. In proceeding of the 11th Innovation in Software Engineering Conference (ISEC), 2018, India.
  11. Pushpendra Singh Rajawat, Deepak Kumar Gupta, Santosh Singh Rathore, and Avtar Singh. Predictive Analysis of Medical Data using a Hybrid Machine Learning Technique. In Proceedings of the 2018 First International Conference on Secure Cyber Computing and Communication (IEEE-ICSCCC), pp. 228-233, 2018.
  12. Saurabh Tiwari and Santosh S. Rathore, “Teaching Software Process Models to Software Engineering Students: An Exploratory Study,” In Proceedings of the 2019 26th Asia-Pacific Software Engineering Conference (APSEC), pp. 308-315, 2019.
  13. Nitin, Kuldeep Kumar, and Santosh Singh Rathore, "Analyzing Ensemble Methods for Software Fault Prediction", In the proceedings of the 1st International Conference on Advanced Communication & Computational Technology (ICACCT-2019), NIT Kurukshetra, 6-7 December 2019.
  14. Saurabh Tiwari, Santosh S. Rathore, Shreya Sagar, Yash Mirani, “Identifying Use Case Elements from Textual Specification: A Preliminary Study”, In the Proceedings of the 28th IEEE International Requirements Engineering Conference (RE’20), Zurich, Switzerland, 2020, DOI 10.1109/RE48521.2020.00059.
  15. Satyendra S. Chouhan, Santosh S. Rathore, and Ritesh C., "A Study of Standardization and Instance Filtering Techniques with Various Classification Algorithms for the Aging-Related Bug Prediction in Software System," In the Proceedings of the International Conference on Paradigms of Computing, Communication and Data Sciences (PCCDS-2020), NIT Kurukshetra, 01- 03 May 2020.
  16. Shubam Yadav, Santosh S. Rathore, and Satyendra Chouhan, "Authorship Identification Using Stylometry and Document Fingerprinting," In the Proceedings of the 8th International Conference, BDA 2020, Sonepat, India, December 15-18, 2020.
  17. S. Kumar, D. Sadhya, and Santosh S. Rathore, "Efficient Text Normalization via Hybrid Bi-directional LSTM," In Proceedings of 2021 IEEE Bombay Section Signature Conference (IBSSC), pp. 1-6. 2021.
  18. A. Negi, Santosh S. Rathore, and D. Sadhya, "USB Keypress Injection Attack Detection via Free-Text Keystroke Dynamics", In Proceedings of 2021 8th IEEE International Conference on Signal Processing and Integrated Networks (SPIN), pp. 681-685, 2021.
  19. S. Tiwari, Santosh S. Rathore, S. U. Farooq, and P. Patani, "How Students Are Using GitHub? A Survey," In Proceedings of 15th Innovations in Software Engineering Conference (ISEC), pp. 1-5, 2022.

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