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Academic Experts
Minal Tandekar

Biography

She is an educator and researcher in computer science, with a focus on artificial intelligence and computer vision. She holds a Master’s degree in Computer Science and Engineering from Delhi Technological University, and an undergraduate degree from the Indian Institute of Engineering Science and Technology, Shibpur. Her academic journey has provided her with a strong foundation in programming, algorithms, and advanced computational methods.

Currently, Minal serves as an Assistant Professor at Jaypee Institute of Information Technology. She teaches a range of core computer science subjects, including programming languages, data structures, algorithms, data analytics, deep learning. Her classroom experience is complemented by hands-on research in deep learning techniques, particularly in image enhancement and facial recognition. Notably, her master’s thesis introduced EEF-GAN, a content-guided attention model for underwater image enhancement, which she has presented at international conferences. Continuously passionate about learning and innovation, Minal has earned certifications in Generative AI, Data Analytics, Statistics and Natural Language Processing. She remains dedicated to advancing artificial intelligence solutions that address real-world challenges and aims to contribute significantly as a leading AI researcher, inspiring and mentoring future generations in the field.

Educational Qualifications

GATE Qualified, JEE Qualified

Research Highlights

Her research specializes in deep learning applications for computer vision, focusing on image enhancement and facial recognition. Her master’s thesis introduced EEF-GAN, a novel content-guided attention model that significantly improves underwater image clarity using generative adversarial networks. This work achieved notable improvements in key image quality metrics and was presented at international conferences. Her expertise spans transformer architectures, pattern recognition, and super-resolution techniques, enabling her to address complex AI challenges and contribute to impactful visual computing solutions across diverse domains.

Areas of Interest
  • Deep Learning
  • Computer vision and Pattern recognition
  • Generative Adversarial Networks (GANs)
  • Transformer Architectures in Visual Computing
Publications
  • M. Tandekar, A. S. Parihar, “Deep Learning Approaches to Underwater Image Enhancement: Performance Metrics and Evaluations,” in Proc. Int. Conf. Innovations in Computing and Communication Technologies (ICICCT), JNU, 2024.
  • M. Tandekar, A. S. Parihar, “Underwater Image Enhancement through Deep Learning and Advanced Convolutional Encoders,” in Proc. 15th Int. Conf. Contemporary Computing and Networking Technologies (15ICC-CNT), IIT Mandi, 2024.