Dr .pellakuri vidyullatha | Computer Vision | Excellence in Research

Associate Professor, Koneru Lakshmaiah Education Foundation, India

🔬 Short Biography 🌿💊📚

Dr. Pellakuri Vidyullatha is an Associate Professor in the Department of Computer Science and Engineering at Koneru Lakshmaiah Education Foundation (K L Deemed-to-be University), India. She holds a Ph.D. in Computer Science, with her research centered on advanced topics in artificial intelligence, machine learning, data mining, and neural networks. Dr. Vidyullatha has contributed extensively to the field through numerous research publications, particularly focusing on applications of deep learning and image segmentation techniques, including recent work on gastrointestinal tract imaging. She is also actively involved in guiding postgraduate and doctoral students, playing a significant role in academic mentorship and research supervision at the university. Her commitment to quality teaching and impactful research has earned her recognition within the academic community. Dr. Vidyullatha continues to advance knowledge in computational intelligence, contributing to both theoretical developments and practical innovations in AI and data science.

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🎓 Education

Dr. Pellakuri Vidyullatha holds dual Post-Doctoral Fellowships in Artificial Intelligence—from the University of South Florida, USA (2023–2025) under Dr. Bhuvan Unhelkar, and the Industrial University of Ho Chi Minh City, Vietnam (2022–2023) under Dr. Bui Thanh Hung. She earned her Ph.D. in Computer Science and Engineering from Koneru Lakshmaiah Education Foundation in 2017, after completing her M.Tech in Computer Science and Technology with distinction (82%) from JNTU Anantapur in 2012. Her educational background is deeply rooted in AI, machine learning, and data science, with a continuous commitment to advancing academic excellence and research acumen.

💼 Professional Experience

With over 20 years of academic and research experience, Dr. Vidyullatha is currently an Associate Professor in the Department of Computer Science Engineering at KL University, Andhra Pradesh, since 2017. Prior to that, she served as Assistant Professor at Narayana Engineering College (2006–2017). She has also completed prestigious postdoctoral fellowships in the USA and Vietnam, focusing on computer vision, deep learning, and natural language processing. Dr. Vidyullatha has successfully organized and contributed to numerous international conferences, workshops, and faculty development programs, and she has played key roles in NAAC, NBA, and NIRF-related institutional development.

🛠️ Skills and Editorial Roles

Dr. Vidyullatha specializes in Artificial Intelligence, Machine Learning, Deep Learning, Natural Language Processing, Quantum Machine Learning, and Big Data Analytics. She is proficient in tools like Python, TensorFlow, Keras, PyTorch, Tableau, and the Hadoop ecosystem. Her pedagogical strengths include flipped learning, inquiry-based learning, project-based learning, and collaborative instruction models. She also holds numerous global certifications from platforms such as Google Cloud, Microsoft Azure, Oracle, and Cisco Networking Academy, and actively participates in global AI challenges on Kaggle and TechGig.

🏅 Awards and Recognition

Dr. Vidyullatha is a multi-award-winning academic, recognized with honors such as the Best Teacher Award (2021–2023) by KL University, Dr. Sarvepalli Radhakrishnan Best Teacher Award, Inspiring Women Award (2023), and the Outstanding Post Doctoral Fellow Award (2023) by Novel Research Academy. She has been appreciated as a keynote speaker, technical session chair, and guest lecturer at various national and international platforms. She also serves as a reviewer for IEEE, InderScience, IJIRST, and other reputed journals and conferences.

Research Focus

Dr. Vidyullatha’s research is centered on advanced AI systems, deep learning models, computer vision, and NLP applications in healthcare, agriculture, and cybersecurity. Her work also spans big data analytics, graph-based algorithms, and recommender systems. With over 72 SCOPUS-indexed publications, 480 citations, and an h-index of 10, she has significantly contributed to scholarly literature. Her most recent works include topics such as emoji-based sentiment analysis, cancer prediction using AI, blockchain communication in IoT, and optimized machine learning models for image segmentation and information retrieval.