Dr. Pooja Saigal received her Ph.D. degree in Machine Learning from South Asian University (established by SAARC), New Delhi in 2018. Her research interests include Machine Learning, Optimization and Image Processing. She has proposed variously supervised, unsupervised and semi-supervised machine learning algorithms and applied them on image processing problems like content-based image retrieval, segmentation, etc. She is UGC-NET qualified in Computer Science. She holds a Master’s Degree (2004) and Bachelor’s Degree (2001) in Computer Applications. She is University Topper of MCA 2004 batch and was awarded Gold Medal by the erstwhile President of India, Dr. APJ Abdul Kalam for her outstanding performance in MCA program (CPI: 90.24% and Percentage: 88.6%). She got Distinction in all 32 courses of MCA. She secured First Rank in University in BCA and was awarded by the Chief Minister of Haryana.
She has the total experience of over 15 years in teaching Information Technology & Computer Science subjects at Post-Graduate and Under-Graduate levels, with successful records of accomplishments. This includes research experience of 4 years at South Asian University, New Delhi and industry experience of 6 months with National Informatics Center (NIC), Delhi Secretariat.
She is the reviewer of SCI Indexed Journals: Neurocomputing(Elsevier); Neural Networks (Elsevier); IEEE Transactions on Cybernetics
- Multi-category ternion support vector machine”. Engineering Applications of Artificial Intelligence 85 (2019): 229-242.
- Angle-based twin parametric-margin support vector machine for pattern classification.” Knowledge-Based Systems 139 (2018): 64-77.
- Angle-based twin support vector machine.” Annals of Operations Research 269.1-2 (2018): 387-417.
- Divide and conquer approach for semi-supervised multi-category classification through localized kernel spectral clustering.” Neurocomputing 238 (2017): 296-306.
- Tree-based localized fuzzy twin support vector clustering with square loss function.” Applied Intelligence 47.1 (2017): 96-113.
- Improvements on ν-twin support vector machine.” Neural Networks 79 (2016): 97-107.
- Nonparallel hyperplane classifiers for multi-category classification.” Computational Intelligence: Theories, Applications and Future Directions (WCI), 2015 IEEE Workshop on. IEEE, 2015.
- Color image classification and retrieval through ternary decision structure based multi-category TWSVM.” Neurocomputing 165 (2015): 444-455.
- Enhanced linear block algorithm with improved similarity measure.” Electrical and Computer Engineering (CCECE), 2014 IEEE 27th Canadian Conference on. IEEE, 2014.
- “Design of frame buffer for 1 THz energy efficient digital image processor based on HSLVDCI I/O standard in FPGA.” Signal Processing and Communication (ICSC), 2013 International Conference on. IEEE, 2013.
- “Reliable ALU design with optimized voltage and implementation on 28nm FPGA.” Optimization, Reliabilty, and Information Technology (ICROIT), 2014 International Conference on. IEEE, 2014
- Color Image Segmentation using Twin Support Vector Machine, IITM Journal of Information Technology, Vol 4, ISSN 2395-5457, 2018
- Technical and Business consideration for LTE & WIMAX 802.16T: The battle for 4G Supremacy, National Seminar on Emerging Trends in IT, IITM, New Delhi, 2012
- Enterprise Application Integration (EAI): Driving Business Innovation”, National Conference on Dynamics & Developmental Changes in Business Practices: Innovation & Globalization, IITM, New Delhi, 2012
- High Performance Computing through Parallel Processing & Multi-core Processing” in IITM Journal, 2012
- Social Media Marketing: Tools and Techniques of Social Media Marketing” published in book Application of Gaming in New Media Marketing, IGI Global, 2018
- 1. Abstract entitled “Time-Efficient Variants of Twin Support Vector Machine with Applications in Image Processing”
published in IEEE Intelligent Informatics Bulletin (Aug 2018) Vol 19 (1), 2018: Selected PhD Thesis Abstract, page: 16-17. (URL: https://www.comp.hkbu.edu.hk/~cib/2018/Aug/abstract/iib_vol19no1_abstract.pdf)