Dr. Prerna Singh
Associate Professor & Programme Manager
dr.psingh@euglobal.edu.eu
“ Educate. Innovate. Elevate”
Dr. Prerna Singh
Key Accolades
- Ph.D. in Computer Science (2021) – University of Delhi
- UGC-NET and Junior Research Fellowship (JRF) qualified in Computer Science – June 2014. Received Fellowship from UGC on clearing NET-JRF.
- Postgraduate degree from BITS Pilani (M.S. in Software Systems)
Biographical Information
I am an enthusiastic and committed academician and IT professional with extensive experience in computer science education, research, and industry. I bring over a decade of teaching experience at reputed institutions like Kalindi College, Swami Shraddhanand College (University of Delhi), and Jagannath Institute of Management Studies. In addition, I have worked in the software industry with companies such as HCL Technologies, AVL India, and XO Infotech, where I developed and tested enterprise applications across domains.
I hold a Ph.D. in Computer Science from the University of Delhi, qualified UGC-NET and JRF in Computer Science, and earned an M.S. in Software Systems from BITS Pilani, complemented by a B.E. in Computer Science.
My academic career has spanned a wide variety of undergraduate-level computer science subjects including Data Science, Data Mining, Java, Software Engineering, Data Warehousing, E-Commerce, and Management Information Systems.
Prior to academia, I worked in various software development and testing roles. I contributed to projects involving technologies like ASP.NET, SQL Server, Oracle, XSLT, and C#, and was actively engaged in quality assurance processes using tools such as VSTS and Toad.
My research interests lie in image processing, machine learning, and data warehousing. I have published in Scopus and SCI-indexed journals, including Pattern Recognition and Image Analysis and Multimedia Tools and Applications (Springer). I have also presented my work at several prestigious conferences such as ICCCNT, ICACIE, and CISSE.
I am passionate about teaching both foundational and advanced computing subjects.I believe in an interactive, project-based learning approach and integrate real-world applications into my teaching.
Areas of expertise/ Research
- Data Science
- Machine learning
- Big Data
Research Interest Information
- Machine Learning Algorithms
- Deep Learning
- Data Science and Statistical Learning
- Big Data and Scalable Machine Learning
- Applications for ML and Data Science
- Optimization and AutoML
- Human-Centered AI and Interaction
Prospective Research Areas
- Disease Diagnosis and Classification using Machine Learning and Deep Learning
- Medical Image Segmentation
- Improving model performance by improving data quality rather than just model complexity.
- Reuse of pre-trained models and model sharing
- AutoML for small and noisy datasets
Publications
The detailed list of publications are available on open source links of Google Scholar and Orcid ID, where the research publications are regularly updated. Please click the links below to access list of publications.
