Sushant Kumar Pandey

Hello and welcome to my website.

I am working as an Assistant Professor at Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence , Faculty of Science and Engineering, University of Groningen, Netherlands. My research group is Software Engineering and Architecture (SEARCH), lead by Prof. Paris Avgeriou.

Before that I was working as a postdoctoral researcher at the Dept. of Computer Science and Engineering in the division of SE Chalmers | University of Gothenburg, Sweden. Where I was in a research team of Testing, Req, Innovation, People(TRIP) at Gothenburg University. Currently, I am working with Dr. Jennifer Horkoff and Prof. Miroslaw Staron.

I had experience in working with my industrial partner is Volvo Cars Group, Gothenburg, where we did many research studies. During my PhD at Indian Institute of Technology (BHU), I worked under supervision of Prof. Anil Kumar Tripathi.

I am working on various problems in the software engineering domain using AI tools, such as input prioritization, design pattern recognition, and software defect prediction. I am also working in a Data leak issue in computer vision.

During my Ph.D. I worked on various aspects of Software defect prediction; my Ph.D. thesis title is "Observations on Software Defect Prediction."

Sorry, but I don't update this website regularly.

You can reach me at following mail addresses:

[email protected]

[email protected] , [email protected] ,

[email protected]

Background and Achievements

EDUCATION
- Ph.D, 2017 to 2021, from Indian Institute of Technology (Banaras Hindu University), Varanasi, India, with 8.4 coursework grade. Thesis title "Observations on Software Defect Prediction."
- Mater of Technology (M.Tech), 2014 to 2014, from National Institute of Technology, Patna, Bihar, India, in Information Technology with 8.21 CGPA, Thesis title "Intrusion Detection system using Anomaly detection technique in Wireless Sensor Network."
- Bachelor of Technology (B. Tech) in Information Technology (IT), 2008 to 2012 from United college of Engineering and research, Greater Noida, Uttar Pradesh Technical University (UPTU), India.
- Intermediate and High school from CBSE, New Delhi, India.
Experience
- Teaching assistant at Dept. of CSE, NIT Patna, India, 2014 to 2016.
- Research scholar and teaching assistant at IIT(BHU), Varanasi, India, 2017 to 2021.
- Post PhD researcher at IIT(BHU), Varanasi, India, June 2021 to Feb 2022.
- Postdoctoral researcher at Dept. of CSE Chalmers | University of Gothenburg, Sweden, March 2022 to March 2024.
Publications

JOURNALS

- - “DNNAttention: A deep neural network and attention based architecture for cross project defect number prediction”, Sushant Kumar Pandey et al. Knowledge Based Systems, Elsevier, and impact factor 8.8, Science citation indexed (SCI), 2021.
  - “An empirical study toward dealing with noise and class imbalance issues in software defect prediction”, Sushant Kumar Pandey et al. Soft Computing, Springer, and impact factor 4.1 Science Citation Index Expanded (SCIE), 2021.
  - “BCV-Predictor: A bug count vector predictor of a successive version of the software system”, Sushant Kumar Pandey et al. Knowledge Based Systems, Elsevier, and impact factor 8.8, Science citation indexed (SCI), 2020.
  - “Software Defect Prediction using K-PCA and various Kernel based Extreme Learning Machine: An Empirical Study”, Sushant Kumar Pandey et al. IET Software, impact factor: 1.6, Science citation indexed expanded (SCIE), 2020.
  - “BPDET: An effective software bug prediction model using deep representation and ensemble learning techniques”, Sushant Kumar Pandey et al. Expert system with Applications, Elsevier, impact factor: 8.5, Science citation indexed expanded (SCIE), 2019.
  - “Machine Learning Based Methods for Software Fault Prediction: A Survey”, Sushant Kumar Pandey et al. Expert system with Applications, Elsevier, impact factor: 8.5, Science citation indexed expanded, 2020.
  - “Design and performance analysis of various feature selection methods for anomaly-based techniques in intrusion detection system”, Sushant Kumar Pandey. Security and Privacy, Wiley, and impact factor: 1.9, 2019.
  - Pandey, Sushant Kumar, et al. "Data Handling for Assuring Production Quality of Image Intensive Autonomous Drive Systems: An Industrial Case Study." Journal of Software Engineering for Autonomous Systems 1.1-2 (2023): 29-47.
  - Pandey, Sushant Kumar, Arya Haldar, and Anil Kumar Tripathi. "Is deep learning good enough for software defect prediction?." Innovations in Systems and Software Engineering (2023): 1-16.
  - “An anomaly detection technique-based intrusion detection system for wireless sensor network”, Sushant Kumar Pandey. Inderscience, Scopus, 2019.
  - “DNNT-CBVP: Deep Neural Network and Transfer learning based Cross-project Bug count Vector Prediction,” Neurocomputing, Elsevier, impact factor 5.77, 2023 (Second revision submitted).
  - Pandey, Sushant Kumar, and Anil Kumar Tripathi. "DBDNN-Estimator: A Cross-Project Number of Fault Estimation Technique." SN Computer Science 5.1 (2023): 29.

CONFERENCES

- - - Comparing Programming Language Models for Design Pattern Recognition by Sushant Kumar Pandey, Miroslaw Staron, Jennifer Horkoff, Mirosław Ochodek, and Darko Durisic. 10th WASA, co-located with ICSA'24, Hyderabad, India.
    - Brain-Inspired Software Architecture: An Adaptive Neural Network Systems, by Ashish Ranjan, Sushant Pandey, Ashiwini, and Tribikram. NIER track ICSA'24, Hyderabad, India. (core rank A).
    - Babu, Md Abu Ahammed, et al. "Impact of Image Data Splitting on the Performance of Automotive Perception Systems." International Conference on Software Quality. Cham: Springer Nature Switzerland, 2024.
    - Chand, Sivajeet, et al. "Comparing Word-Based and AST-Based Models for Design Pattern Recognition." Proceedings of the 19th International Conference on Predictive Models and Data Analytics in Software Engineering (PROMISE). 2023.
    - Pandey, Sushant Kumar, et al. "Design Patterns Understanding and Use in the Automotive Industry: An Interview Study." International Conference on Product-Focused Software Process Improvement (PROFES'23). Cham: Springer Nature Switzerland, 2023. (Core rank B)
    - Pandey, Sushant Kumar, et al. "TransDPR: Design Pattern Recognition Using Programming Language Models." 2023 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM). IEEE, 2023. (Core rank A).
    - “Cross-Project setting using Deep learning Architectures in Just-In-Time Software Fault Prediction: An Investigation”, Sushant Kumar Pandey et al. (IEEE, AST [co located-ICSE (Core rank A*)] – 2023, Melbourne, Australia).
    - Sielicka, Paulina Anioła, et al. "Defect Backlog Size Prediction for Open-Source Projects with the Autoregressive Moving Average and Exponential Smoothing Models." 2023 18th Conference on Computer Science and Intelligence Systems (FedCSIS). IEEE, 2023. (Core rank B).
    - Mosin, Vasilii, et al. "Comparing Input Prioritization Techniques for Testing Deep Learning Algorithms." 2022 48th Euromicro Conference on Software Engineering and Advanced Applications (SEAA). IEEE, 2022. (Core rank B)
    - “Class Imbalance Issue in Software Defect Prediction Models by various Machine Learning Techniques: An Empirical Study”, 2021, IEEE, 8th International Conference on Smart Computing and Communications (ICSCC), Kerala, India
    - “Software bug prediction prototype using Bayesian network classifier: A comprehensive model”. International Conference on Computational Intelligence and Data Science (ICCIDS 2018), Elsevier, Scopus indexed. Gurugram India.
    - “Intrusion detection system using anomaly technique in wireless sensor network”, International Conference on Computing, Communication and Automation (ICCCA 2016), Scopus indexed. Greater Noida India.
Language and tools
- Programming language: C, Python, Java, and Matlab.
- Machine learning and deep learning libraries in Python.
- WEKA, and Stastica machine learning tools.
ACHIEVEMENTS
- Course certificate of Structuring Machine Learning Projects from Coursera (2018).
- Course certificate of Neural Networks and Deep Learning from Coursera (2018).
- Course certificate of Neural Convolutional Neural Networks from Coursera (2019).
- Course certificate Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization from Coursera (2019).
- Course certificate Sequence Models from Coursera (2019).
- Course certificate Improving Machine learning from Coursera (2020).
- ETHICAL HACKING & SECURITY certification from APPINE TECHNOLOGY LAB Noida, India

Links

Program committee member and reviewer

Conference Organization

EASE 2022, Industrial track PC Co-Chair

Regular Reviewer

Hobbies

Travelling, workout, movies & shows, reading new articles.

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