Dr. Suyash Shukla is an Assistant Professor in the Department of Computer Science at BITS Pilani, Dubai Campus. He earned his Ph.D. in Computer Science and Engineering from the Indian Institute of Technology (IIT) Roorkee, following his M.Tech. from the National Institute of Technology (NIT) Rourkela. His doctoral research focused on machine learning–based software effort estimation and productivity modeling.
His primary research area lies in Software Engineering, with a specific focus on addressing critical challenges such as Software Effort Estimation, Software Fault Prediction, Software Reliability, Software Vulnerability Prediction, and Malware Detection. Within this domain, he aims to enhance the quality, productivity, and security of software systems through data-driven and predictive modeling approaches. He also actively explores Machine Learning (ML) and Deep Learning (DL) techniques, leveraging their advanced predictive and representation-learning capabilities to model complex phenomena in software development. By integrating ML and DL into the Software Engineering lifecycle, his work contributes to building intelligent software analytics frameworks that improve estimation accuracy, fault localization, reliability forecasting, and vulnerability detection, ultimately promoting automation and decision support in software project management and maintenance.
Dr. Shukla has published his research in several reputed international journals, including IEEE Transactions on Engineering Management, Applied Intelligence Journal, Software Quality Journal, Knowledge and Information Systems, and Journal of Software: Evolution and Process. He has also presented his work at prominent international conferences, including the IEEE World Congress on Services (IEEE SERVICES), the IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER), and the International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE).
