Kiran Ravulakollu | Machine Learning | Best Researcher Award

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Prof Dr. Kiran Ravulakollu | Machine Learning | Best Researcher Award

Dean at Woxsen University, India.

Prof. Dr. Kiran Ravulakollu is currently the Dean and Professor at the School of Technology at Woxsen University, Kamkole, Telangana, where he has played a pivotal role in establishing the school since 2021. He also serves as the Director of Research and Development at the same institution. With a strong academic background, Dr. Ravulakollu holds a Ph.D. in Computer Science from the University of Sunderland, UK, and has extensive teaching and research experience in areas such as artificial intelligence, image processing, and hybrid intelligent systems. Throughout his career, he has held various academic positions, including Assistant Dean of Research at the University of Petroleum and Energy Studies and has been instrumental in developing research ecosystems that foster collaboration and innovation. His contributions to the field are evident in his impressive publication record, with over 879 publications and numerous patents. An active participant in research advisory committees and academic councils, Dr. Ravulakollu is dedicated to advancing technology and education through strategic leadership and innovative research initiatives.

Profile:

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

Naeem Ahmed | Machine Learning | Best Innovation Award

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Mr. Naeem Ahmed | Machine Learning | Best Innovation Award

Phd. Scholor at Nanjing University of Information Science and Technology, China

Summary:

Mr. Naeem Ahmed is a dedicated academic currently pursuing a PhD in Computer Science at NUIST, China, following his completion of a Master’s degree from the University of Engineering and Technology, Taxila, Pakistan, where he focused on sentiment analysis in Urdu using supervised machine learning. He has extensive teaching experience as a lecturer in various institutions, including the Government Postgraduate College Haripur and Abbottabad University of Science and Technology, covering topics such as artificial intelligence, natural language processing, and mobile app development. Mr. Ahmed has contributed to significant research publications, particularly in the areas of sentiment analysis and medical imaging, and has developed various real-world projects leveraging machine learning and deep learning technologies. His expertise encompasses a wide range of skills, including machine learning, computer vision, and web development. Beyond his academic pursuits, he enjoys traveling, photography, and keeping up with advancements in technology and automation.

Profile:

Education:

Mr. Naeem Ahmed is currently pursuing a Doctor of Philosophy (PhD) in Computer Science at NUIST, China, which he began in September 2024. He completed his Master of Science in Computer Science from the Department of Computer Science, University of Engineering and Technology, Taxila, Pakistan, in October 2022. His master’s research focused on “Sentiment Analysis of Urdu Language using Supervised Machine Learning.” Prior to this, he earned a Bachelor of Science in Computer Science from the Department of Information Technology, University of Haripur, Pakistan, in August 2019, laying a strong foundation in the field of computer science.

Professional Experience:

Mr. Naeem Ahmed has built a solid professional foundation in academia, serving as a lecturer in the Department of Computer Science at various institutions in Pakistan. Currently, at the Government Postgraduate College Haripur, he instructs courses in artificial intelligence, operating systems, and data structures, where he emphasizes the importance of aligning course materials with industry trends and fostering student engagement through interactive projects. His previous role at Abbottabad University of Science and Technology involved teaching mobile app development and natural language processing, where he initiated projects that enhanced real-world problem-solving skills among students. Mr. Ahmed also held teaching positions at Government Postgraduate College Khalabat Township and the University of Haripur, covering subjects such as assembly language, software development, and information security. In addition to his teaching roles, he worked as a research assistant, where he instructed students in Python development and machine learning, and as a C#/.NET developer, where he developed applications to improve retail business operations. His diverse experience in both teaching and practical application in the technology sector underscores his commitment to education and innovation in computer science.

Research Interests:

Mr. Naeem Ahmed’s research interests are centered around the fields of machine learning, natural language processing, and computer vision. His work focuses on the development and application of innovative algorithms and models for sentiment analysis, particularly in low-resource languages, as evidenced by his publication on a novel approach for Urdu sentiment analysis using deep learning models. He is also engaged in exploring the intersection of technology and healthcare, demonstrated through his research on knee osteoarthritis detection and classification using transfer learning, as well as brain tumor detection using deep learning techniques. Additionally, Mr. Ahmed is interested in addressing real-world challenges through interdisciplinary projects, such as developing systems for emotion detection and COVID-19 detection from medical imaging. His commitment to advancing the fields of artificial intelligence and data analysis is reflected in his hands-on project experience, including applications in medical imaging, mobile app development, and deep fake detection. Through his research endeavors, Mr. Ahmed aims to contribute to the ongoing advancements in technology and its practical applications in various domains.

Skills:

Mr. Naeem Ahmed possesses a diverse skill set that encompasses various areas of computer science, particularly in machine learning, deep learning, and natural language processing. His expertise in machine learning algorithms and model development allows him to tackle complex problems, including sentiment analysis, emotion recognition, and medical imaging applications. Proficient in programming languages such as Python, R, C++, and C#, he effectively utilizes frameworks and libraries like TensorFlow, PyTorch, and scikit-learn to build and deploy sophisticated models. Mr. Ahmed also has substantial experience in computer vision and image processing, which enables him to develop applications for tasks such as brain tumor detection and fall detection for elderly individuals. His background in web and desktop application development further enhances his ability to create user-friendly solutions. Additionally, Mr. Ahmed’s skills in data preprocessing, exploratory data analysis, and cloud services empower him to analyze and interpret data efficiently, ensuring that his projects are aligned with industry trends and real-world needs. Through continuous learning and hands-on experience, Mr. Ahmed is well-equipped to contribute to the evolving landscape of technology and innovation.

Concution:

Naeem Ahmed’s strong academic credentials, innovative research in machine learning and AI, and practical applications in fields like healthcare and automation make him a highly suitable candidate for the Research for Best Innovation Award. His contributions to AI research and education reflect his dedication to advancing the field.

Publication Top Noted:

Machine learning techniques for spam detection in email and IoT platforms: analysis and research challenges

  • Authors: N. Ahmed, R. Amin, H. Aldabbas, D. Koundal, B. Alouffi, T. Shah
  • Journal: Security and Communication Networks
  • Year: 2022
  • Volume: 2022
  • Article ID: 1862888
  • Citations: 103

Trust management technique using blockchain in smart building

  • Authors: M. Saeed, R. Amin, M. Aftab, N. Ahmed
  • Journal: Engineering Proceedings
  • Year: 2022
  • Volume: 20(1)
  • Article: 24
  • Citations: 6

Sentiment analysis for covid-19 vaccine popularity

  • Authors: M. Saeed, N. Ahmed, A. Mehmood, M. Aftab, R. Amin, S. Kamal
  • Journal: KSII Transactions on Internet and Information Systems (TIIS)
  • Year: 2023
  • Volume: 17(5)
  • Pages: 1377-1393
  • Citations: 3

Intrusion detection systems for software-defined networks: a comprehensive study on machine learning-based techniques

  • Authors: Z. Mustafa, R. Amin, H. Aldabbas, N. Ahmed
  • Journal: Cluster Computing
  • Year: 2024
  • Pages: 1-27
  • Citations: 2

Urdu Sentiment Analysis Using Deep Attention-Based Technique

  • Authors: N. Ahmed, R. Amin, H. Ayub, M.M. Iqbal, M. Saeed, M. Hussain
  • Journal: Foundation University Journal of Engineering and Applied Sciences
  • Year: 2022
  • Citations: 1

Detection of Face Emotion and Music Recommendation System using Machine Learning

  • Authors: D. Ali, M.T. Huque, J.J. Godhuli, N. Ahmed
  • Journal: International Journal of Research and Innovation in Applied Science
  • Year: 2022
  • Volume: 7(11)
  • Citations: 1

DEVELOPMENT OF A SYSTEM FOR FIRE DETECTION AND ALARM USING MACHINE LEARNING AND COMPUTER VISION

  • Authors: D. Ali, J.J. Godhuli, B. Khan, M.T. Huque, N. Ahmed
  • Citations: 1