Early Academic Pursuits
Mrs. Deepthi S embarked on her academic journey with a Bachelor of Engineering in Information Science from SJC Institute of Technology, Chikkaballapur, graduating in June 2005 with a First Class (64% aggregate). She further honed her expertise by completing her Master of Engineering in Computer Science from University Visvesvaraya College of Engineering (UVCE), Bangalore, securing First Class with Distinction (82%). Currently, she is pursuing a Doctor of Philosophy (Ph.D.) at Presidency University, Bangalore, focusing on Deep Learning Techniques for the Classification of Non-Hodgkin Lymphoma (NHL) on Histopathological Tumour Images. She has successfully completed her comprehensive viva, marking a significant milestone in her research progression.
Professional Endeavors
With an impressive 19 years of academic experience, Mrs. Deepthi S has served in prominent institutions across Karnataka. She is currently an Assistant Professor at Presidency University, Bangalore since January 2023. Prior to this, she held the same role at Cambridge Institute of Technology, Bangalore from July 2012 to December 2023. Her foundational teaching experience was shaped at SJC Institute of Technology, Chikkaballapur, where she served as a Lecturer from July 2005 to July 2012. Over the years, she has handled an extensive range of subjects that include Discrete Mathematical Structures, Graph Theory, Database Management Systems, Data Mining & Warehousing, Software Testing, Web Technologies, AI & ML, and Generative AI.
Contributions and Research Focus
Mrs. Deepthi’s research is centered around artificial intelligence, deep learning, medical image analysis, and generative AI. Her ongoing Ph.D. work aims at enhancing the classification of Non-Hodgkin Lymphoma using deep learning architectures such as DenseNet and ResNet. Her research contributions have led to multiple publications in peer-reviewed journals, including articles like “Non-Hodgkin’s Lymphoma Classification using Improved Predator Optimization Based Densenet121 Model” and “Harnessing ResNet50 and DenseNet201 for Enhanced Lymphoma Diagnosis via Feature Extraction.” She has a particular passion for applying machine learning models to solve real-world healthcare challenges, especially in histopathological tumor image classification.
Impact and Influence
Through her research, teaching, and continuous professional development, Mrs. Deepthi S has become a driving force in blending technology with healthcare innovation. Her work is recognized in reputed journals such as Frontiers in Health Informatics and Journal of Electrical Systems. With a vision to bridge academic theory with practical industry applications, she actively integrates real-time case studies and tools in her lectures, shaping the future workforce in AI and healthcare technologies.
Technical Skills
Mrs. Deepthi S is well-versed in a wide range of technical areas including Python programming, Unix system programming, data mining algorithms, rational tools, and generative AI frameworks. She has completed several certifications such as:
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Python for Beginners (SkillUp – Simplilearn)
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Programming with Python 3.x (Simplilearn)
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Blockchain Developer Training (Simplilearn)
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Generative AI using OpenAI API for Beginners (Udemy)
Teaching Experience
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Discrete Mathematical Structures
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Graph Theory
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Artificial Intelligence & Machine Learning
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Web 2.0 and Web Technologies
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Software Testing
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Management Information Systems
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Unix System Programming
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Generative AI
Workshops and FDPs
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Amazon Web Services National Training Program (AICTE)
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Reinforcement Learning FDP, May 2023
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21-Day Online International FDP on Research Tools, July 2023
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International FDPs on Generative AI, NLP, AI & Healthcare
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Workshops on AI for Net-Zero Systems, Ethical Design, and AI-powered Learning
Legacy and Future Contributions
With nearly two decades of academic service and a growing research profile, Mrs. Deepthi S is poised to become a leading contributor in AI for healthcare. Her current Ph.D. research, active publication record, and workshop leadership reflect her commitment to lifelong learning and innovation. She continues to mentor future engineers and researchers, empowering them with the knowledge, tools, and motivation to excel in an AI-driven world. Her future goals include expanding her research in generative AI applications, AI ethics, and interdisciplinary healthcare solutions