Assistant Professor Dr. Avatharam Ganivada, renowned for his expertise in Medical Image Analysis, has been honored with the esteemed Best Researcher Award. 🏆 His exemplary contributions, particularly in the realm of analyzing medical images for diagnostic and therapeutic advancements, have garnered widespread acclaim. Hailing from the University of Hyderabad, India, Dr. Ganivada’s dedication to pushing the boundaries of medical research is truly commendable. His innovative approaches and groundbreaking discoveries continue to inspire both peers and students alike, shaping the future of medical imaging and healthcare. 🌟
Profile
Google Scholar
Education 🎓
Dr. Avatharam Ganivada holds a Ph.D. in Computer Science and Engineering from Calcutta University, with research conducted at the Center for Soft Computing Research, Indian Statistical Institute, during Dec. 2009–Aug. 2015. Additionally, she completed a certificate course on soft computing and machine learning at the same institute in 2009, and obtained her M.Tech. degree in Computer Science and Technology from the University of Mysore in 2008.
Experience 💼
Dr. Ganivada has a rich professional background, serving as an Assistant Professor at the School of Computer and Information Sciences, University of Hyderabad since March 2017. Prior to academia, she worked as a Data Scientist at ProKarma Soft. Pvt. Ltd., Hyderabad, from September 2015 to February 2017.
Research Interests 🧠
Dr. Ganivada’s research interests encompass various aspects of computer science, including deep learning, neural networks, pattern recognition, and bioinformatics. She is particularly focused on developing innovative solutions for image processing, object detection, and classification, as evidenced by her extensive publication record.
Awards and Recognition 🏆
Dr. Ganivada’s academic achievements have been recognized through prestigious fellowships, including the J.C. Bose Fellowship for her Ph.D. research and the AICTE GATE fellowship during her M.Tech. Additionally, she has served as a reviewer for esteemed journals and conferences in her field.
Publications 📚
- “Deep Learning and Genetic Algorithm-based Ensemble Model for Feature Selection and Classification of Breast Ultrasound Images”, Image and Vision Computing, Accepted, 2024.