Education:
Prof. Dr. Kiran Ravulakollu has a solid academic foundation, beginning with a Bachelor’s degree in Computer Science and Engineering from Jawaharlal Nehru Technological University, Hyderabad, India, awarded in 2004. He further advanced his expertise by earning a Postgraduate Certificate in Artificial Intelligence from City, University of London, United Kingdom, in 2006. Dr. Ravulakollu’s academic journey culminated in a Ph.D. in Computer Science from the University of Sunderland, United Kingdom, in 2012. His Ph.D. research focused on developing a computational architecture inspired by the Superior Colliculus of the mid-brain, utilizing neural networks for the efficient integration of audio and visual stimuli. Additionally, he completed a Post-Graduate Certificate in Academic Practices from the University of Petroleum and Energy Studies, Dehradun, India, in 2019, further enhancing his teaching and research credentials.
Professional Experience:
Prof. Dr. Kiran Ravulakollu has an extensive professional experience in academia and research, currently serving as the Dean and Professor at the School of Technology at Woxsen University, Kamkole, Telangana, since August 2021. In this role, he successfully established the school, significantly increasing student enrollment from 31 to 1,500, faculty and staff from 2 to 75, and generating revenue of ₹80 lakhs. He has also served as the Director of Research and Development at Woxsen University since August 2022, where he developed a robust R&D ecosystem, resulting in a remarkable rise in publications from 10 to 879, citations from 428 to over 7,400, and the acquisition of 36 patents. Prior to his current roles, Dr. Ravulakollu held various positions at the University of Petroleum and Energy Studies, Dehradun, including Assistant Dean of Research and Senior Associate Professor. His academic journey began as an Assistant Professor at Sharda University, where he contributed to curriculum development and student mentoring. His research background includes a tenure as a Research Associate at the HIS Research Group at the University of Sunderland, UK, where he focused on sensory data integration for artificial agents. Throughout his career, Dr. Ravulakollu has demonstrated exceptional leadership, strategic thinking, and a commitment to fostering research excellence in technology and engineering.
Research Interests:
Prof. Dr. Kiran Ravulakollu’s research interests lie at the intersection of artificial intelligence, computer science, and intelligent systems. His Ph.D. research focused on creating computational architectures inspired by the mid-brain’s Superior Colliculus, utilizing artificial neural networks to integrate audio and visual stimuli for enhanced localization capabilities. This foundational work has propelled his ongoing investigations into various advanced topics, including image processing methodologies, artificial agents, ambient intelligence, and hybrid intelligent systems. Additionally, Dr. Ravulakollu is keenly interested in the Internet of Things (IoT) and its applications, exploring how interconnected devices can contribute to smarter solutions in urban environments. His dedication to innovation is reflected in his ability to translate complex theoretical concepts into practical applications, fostering knowledge transfer that shapes products and enhances research outcomes. Overall, his diverse research portfolio showcases a commitment to pushing the boundaries of technology and developing cutting-edge solutions for real-world challenges.
Skills:
Prof. Dr. Kiran Ravulakollu possesses a robust skill set that encompasses analytical expertise, strong research methodologies, and innovative development capabilities. His analytical skills enable him to design and implement significant projects, effectively identifying problems and conducting feasibility studies to ensure research viability. With a solid foundation in project management, he excels at coordinating research and development activities, fostering collaboration among diverse teams. Dr. Ravulakollu is adept at data analysis, utilizing advanced techniques to derive meaningful insights and inform decision-making processes. His proficiency in knowledge transfer allows him to bridge the gap between theoretical research and practical application, shaping products that meet industry demands. Additionally, his experience in developing policies and frameworks for effective administration reflects his strategic thinking ability and commitment to continuous improvement within academic and research environments. Overall, Dr. Ravulakollu’s diverse skill set positions him as a leader in his field, driving impactful research initiatives and fostering innovation.
Conclusion:
Prof. Dr. Kiran Ravulakollu’s exceptional track record in academia, research, and administration make him a highly suitable candidate for the Best Researcher Award. His ability to blend innovative research with practical applications, along with his leadership in establishing a robust R&D environment, highlights his suitability for this prestigious recognition. His career demonstrates a consistent commitment to advancing knowledge and technology in the fields of artificial intelligence, machine learning, and hybrid intelligent systems, positioning him as a leader in contemporary research.
Publication Top Noted:
SIGN LANGUAGE RECOGNITION: STATE OF THE ART
- Authors: AK Sahoo, GS Mishra, KK Ravulakollu
- Year: 2013
- Cited by: 105
Improving automated latent fingerprint detection and segmentation using deep convolutional neural network
- Authors: M Chhabra, KK Ravulakollu, M Kumar, A Sharma, A Nayyar
- Journal: Neural Computing and Applications
- Year: 2023
- Cited by: 33
Naïve Bayes Classifier with LU Factorization for Recognition of Handwritten Odia Numerals
- Authors: KKR, Pradeepta K. Sarangi, P. Ahmed
- Journal: Indian Journal of Science and Technology
- Year: 2014
- Cited by: 32
HANDWRITTEN DEVNAGARI DIGIT RECOGNITION: BENCHMARKING ON NEW DATASET
- Authors: R Kumar, KK Ravulakollu
- Journal: Journal of Theoretical & Applied Information Technology
- Year: 2014
- Cited by: 27
A Hybrid Intrusion Detection System: Integrating Hybrid Feature Selection Approach with Heterogeneous Ensemble of Intelligent Classifiers
- Authors: KKR, Amrita
- Journal: International Journal of Network Security
- Year: 2018
- Cited by: 25
Fuzzy-membership based writer identification from handwritten devnagari script
- Authors: R Kumar, KK Ravulakollu, R Bhat
- Journal: Journal of Information Processing Systems
- Year: 2017
- Cited by: 23
Indian sign language recognition using skin color detection
- Authors: AK Sahoo, KK Ravulakollu
- Journal: International Journal of Applied Engineering Research
- Year: 2014
- Cited by: 19
VISION BASED INDIAN SIGN LANGUAGE CHARACTER RECOGNITION
- Authors: AK Sahoo, KK Ravulakollu
- Journal: Journal of Theoretical & Applied Information Technology
- Year: 2014
- Cited by: 18
A review on artificial intelligence in orthopaedics
- Authors: T Hamid, M Chhabra, K Ravulakollu, P Singh, S Dalal, R Dewan
- Conference: 2022 9th International Conference on Computing for Sustainable Global Development
- Year: 2022
- Cited by: 17
WORD BASED STATISTICAL MACHINE TRANSLATION FROM ENGLISH TEXT TO INDIAN SIGN LANGUAGE
- Authors: GS Mishra, AK Sahoo, KK Ravulakollu
- Journal: ARPN Journal of Engineering & Applied Sciences
- Year: 2017
- Cited by: 17
State-of-the-Art: A Systematic Literature Review of Image Segmentation in Latent Fingerprint Forensics
- Authors: KKR, Megha Chhabra, Manoj Kumar Shukla
- Journal: Recent Patents on Computer Science
- Year: 2019
- Cited by: 16
Surface Corrosion Grade Classification using Convolution Neural Network
- Authors: KKR, Sanjay Kumar Ahuja, Manoj Kumar Shukla
- Journal: International Journal of Recent Technology and Engineering
- Year: 2019
- Cited by: 15