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Ashima Tyagi
Assistant Professor
Profile Summary
Ms. Ashima Tyagi is an Assistant Professor at the School of Computer Science, UPES Dehradun, with around three years of teaching experience at undergraduate and postgraduate levels.
She is currently pursuing her Ph.D. in Computer Science and Engineering from Motilal Nehru National Institute of Technology Allahabad, specializing in medical image analysis using artificial intelligence.
Her research focuses on developing computer-aided diagnosis systems using machine learning and deep learning, with publications in reputed journals and conferences.
Work Experience
Ms. Ashima Tyagi has previously served as an Assistant Professor at Galgotias University and ABES Engineering College, contributing to teaching and academic development.
She has also worked as a Teaching Assistant at Motilal Nehru National Institute of Technology Allahabad during her Ph.D., gaining experience in teaching and research activities.
Educational Qualification
Ph.D. Pursuing, Computer Science and Engineering, Motilal Nehru National Institute of Technology Allahabad.
Research Interests
Machine Learning, Data Science, Predictive Analytics, Computer Vision, Health Analytics, Medical Imaging, Computer-Aided Diagnosis, Deep Learning.
Teaching Philosophy
Ms. Ashima Tyagi believes in creating an inclusive and engaging learning environment that nurtures critical thinking and problem-solving skills.
She emphasizes conceptual understanding over rote learning and adopts innovative teaching methods to support student growth and academic success.
Courses Taught
Machine Learning, Data Science, Python Programming, Data Structures, Operating Systems, Database Management System, Software Engineering, Programming with Problem Solving using C, Computer Fundamentals.
Awards and Achievements
Qualified UGC-NET in Computer Science with an All India Rank of 153 in December 2019.
Scholarly Activities
Ms. Ashima Tyagi works extensively in medical image analysis using AI for developing computer-aided diagnosis systems.
Her research involves processing large datasets, feature engineering, and building machine learning and deep learning models for healthcare applications.
She actively mentors students in research projects, guiding them through design, implementation, and successful completion.
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