Dr. Deepali Hirolikar, PDEA,s College of Engineering, Manjari(Bk.), Pune, India
Dr. Deepali S. Hirolikar is the Head of the Department of Information Technology at PDEA’s College of Engineering, Pune, with 18 years of experience in academia. She holds a PhD in Information Technology from Shri JJT University, Rajasthan. Dr. Hirolikar has published numerous papers in national and international journals, focusing on topics such as IoT, cloud computing, and machine learning. She has also published a book on IoT security paradigms. As an active contributor to various workshops and conferences, she has received multiple accolades for her work. 🖥️📚🎓
Publication Profile
Orcid
Experience 🏆
Prof. Dr. Deepali S. Hirolikar has amassed over 18 years of experience in academia. She currently serves as the Head of the Information Technology Department and Assistant Professor at PDEA’s College of Engineering, Manjari, Pune, a position she has held since September 6, 2005. Before this, she was a Lecturer in the Computer Engineering Department at SRGSIOT, Hadapsar.
Education 📚
She completed her SSC at Keshavraj Vidyalaya, Latur in 1995 with distinction, and her HSC at Dayanand Science Junior College, Latur in 1997 with first class. She earned her Diploma in Computer Science Engineering from PLGP, Latur in 2000 with first class, and her BE in Computer Science and Engineering from Dr. BAMU, Aurangabad in 2004 with distinction. Prof. Dr. Hirolikar obtained her ME in Information Technology from UOP Pune, MIT College of Engineering, Pune in 2011 with first class, and her PhD in Information Technology from Shri JJT University, Rajasthan in 2021.
Research Focus
Deepali Hirolikar’s research primarily focuses on using metaheuristic methods and machine learning for efficiently predicting and classifying heart disease data. Her work includes the development and application of advanced algorithms to enhance the accuracy and efficiency of heart disease prediction models. By leveraging mathematical and engineering principles, she contributes to the field of medical data analysis, particularly in identifying patterns and improving diagnostic processes. Her research also spans the integration of machine learning techniques with medical datasets to facilitate better health outcomes.
Publication Top Notes
Metaheuristic Methods for Efficiently Predicting and Classifying Real Life Heart Disease Data Using Machine Learning