Farhad Soleimanian Gharehchopogh | Artificial Intelligent | Best Researcher Award

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Assoc. Prof. Dr. Farhad Soleimanian Gharehchopogh | Artificial Intelligent | Best Researcher Award

Dean of Faculty at Urmia Branch, Islamic Azad University, Iran

Dr. Farhad Soleimanian Gharehchopogh is a distinguished academic with a profound background in computer science and software engineering. He is renowned for his contributions to machine learning, artificial intelligence, and computational intelligence. His research focuses on solving complex problems using evolutionary algorithms and optimization techniques. Dr. Soleimanian is also an active participant in academic circles, serving on the editorial boards of several prestigious journals and regularly presenting his findings at international conferences. With numerous publications in high-impact journals, he has significantly influenced his field. His dedication to research and education has earned him accolades, making him a respected figure among peers and students alike.

Professional Profile

Education

Dr. Farhad Soleimanian Gharehchopogh holds a Ph.D. in Computer Science, specializing in Software Engineering from Urmia University, Iran. His doctoral research focused on advanced optimization techniques and their applications in artificial intelligence. Prior to his Ph.D., he completed a Master of Science in Software Engineering at Islamic Azad University, Tabriz Branch, where he developed a strong foundation in programming, data structures, and algorithm design. He earned his Bachelor of Science in Computer Science from Islamic Azad University, Urmia Branch, where he first explored his interest in computational intelligence. His academic journey has been characterized by a consistent focus on deepening his understanding of complex computational systems.

Professional Experience

Dr. Farhad Soleimanian Gharehchopogh has held various academic positions throughout his career, contributing to the growth of computer science education and research. He has served as an Assistant Professor at Islamic Azad University, Urmia Branch, where he taught undergraduate and graduate courses in software engineering and computer science. In addition to teaching, he has supervised numerous master’s and Ph.D. students, guiding their research in areas like machine learning and optimization algorithms. He has also collaborated with international researchers on various projects, aiming to solve real-world problems using advanced computational methods. His professional experience is marked by a commitment to fostering innovation in both academic and practical applications of computer science.

Research Interest

Dr. Soleimanian’s research interests are centered around machine learning, artificial intelligence, and computational optimization. He is particularly interested in developing new algorithms for data mining, evolutionary computing, and swarm intelligence. His work often explores how optimization techniques, such as genetic algorithms, particle swarm optimization, and ant colony optimization, can be applied to solve complex problems in various fields. Additionally, he is passionate about deep learning and its applications in pattern recognition, natural language processing, and image analysis. Dr. Soleimanian continually seeks to advance the field through innovative research, aiming to bridge the gap between theoretical concepts and practical implementations.

Research Skills

Dr. Farhad Soleimanian Gharehchopogh possesses a wide array of research skills that make him a leader in computational intelligence and software engineering. He has extensive experience in developing and implementing optimization algorithms, leveraging his expertise in evolutionary computing and metaheuristics. Proficient in programming languages such as Python, MATLAB, and C++, he applies these skills to simulate and analyze complex models. Dr. Soleimanian is also skilled in statistical analysis and data visualization, enabling him to derive meaningful insights from large datasets. His ability to collaborate effectively with other researchers and his strong analytical mindset have allowed him to make significant contributions to his field.

Awards and Honors

Dr. Soleimanian’s excellence in research and education has been recognized with several awards and honors throughout his career. He has received accolades for his high-quality research papers presented at international conferences and published in peer-reviewed journals. His contributions to the field have been acknowledged with best paper awards and recognition from academic societies. He has also been honored for his outstanding teaching and mentoring, guiding students towards academic and professional success. Dr. Soleimanian’s dedication to advancing computer science and his commitment to academic excellence have made him a recipient of numerous prestigious awards, highlighting his impact in both research and education.

Conclusion

Dr. Farhad Soleimanian Gharehchopogh is a strong candidate for the Best Researcher Award, given his extensive research output, mentorship of graduate students, and recognition among the top-cited scientists globally. His consistent contributions to the academic and research community, particularly in computer engineering, make him well-suited for this award. Addressing the minor areas for improvement, such as updating student mentorship records and highlighting recent publications, would further solidify his application.

Publications Top Notes

  • Recent applications and advances of African Vultures Optimization Algorithm
    Authors: AG Hussien, FS Gharehchopogh, A Bouaouda, S Kumar, G Hu
    Journal: Artificial Intelligence Review 57 (12), 1-51
    Year: 2024
    Citations: Not specified
  • An Improved Artificial Rabbits Optimization Algorithm with Chaotic Local Search and Opposition-Based Learning for Engineering Problems and Its Applications in Breast Cancer
    Authors: FA Özbay, E Özbay, FS Gharehchopogh
    Journal: CMES-Computer Modeling in Engineering & Sciences 141 (2)
    Year: 2024
    Citations: Not specified
  • Chaotic RIME optimization algorithm with adaptive mutualism for feature selection problems
    Authors: M Abdel-Salam, G Hu, E Çelik, FS Gharehchopogh, IM El-Hasnony
    Journal: Computers in Biology and Medicine 179, 108803
    Year: 2024
    Citations: 6
  • A hybrid principal label space transformation-based ridge regression and decision tree for multi-label classification
    Authors: SHS Ebrahimi, K Majidzadeh, FS Gharehchopogh
    Journal: Evolving Systems, 1-37
    Year: 2024
    Citations: Not specified
  • Multifeature Fusion Method with Metaheuristic Optimization for Automated Voice Pathology Detection
    Authors: E Özbay, FA Özbay, N Khodadadi, FS Gharehchopogh, S Mirjalili
    Journal: Journal of Voice
    Year: 2024
    Citations: Not specified
  • A Quasi-Oppositional Learning-based Fox Optimizer for QoS-aware Web Service Composition in Mobile Edge Computing
    Authors: RH Sharif, M Masdari, A Ghaffari, FS Gharehchopogh
    Journal: Journal of Grid Computing 22 (3), 64
    Year: 2024
    Citations: Not specified
  • A novel offloading strategy for multi-user optimization in blockchain-enabled Mobile Edge Computing networks for improved Internet of Things performance
    Authors: AM Rahmani, J Tanveer, FS Gharehchopogh, S Rajabi, M Hosseinzadeh
    Journal: Computers and Electrical Engineering 119, 109514
    Year: 2024
    Citations: 5
  • An Intrusion Detection System on The Internet of Things Using Deep Learning and Multi-objective Enhanced Gorilla Troops Optimizer
    Authors: H Asgharzadeh, A Ghaffari, M Masdari, FS Gharehchopogh
    Journal: Journal of Bionic Engineering 21 (5), 2658-2684
    Year: 2024
    Citations: 2
  • Visualization and classification of mushroom species with multi-feature fusion of metaheuristics-based convolutional neural network model
    Authors: E Özbay, FA Özbay, FS Gharehchopogh
    Journal: Applied Soft Computing 164, 111936
    Year: 2024
    Citations: 1
  • A software defect prediction method using binary gray wolf optimizer and machine learning algorithms
    Authors: H Wang, B Arasteh, K Arasteh, FS Gharehchopogh, A Rouhi
    Journal: Computers and Electrical Engineering 118, 109336
    Year: 2024
    Citations: 1

Fahd Alharithi | Artificial Intelligence | Best Researcher Award

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Assoc Prof Dr. Fahd Alharithi | Artificial Intelligence | Best Researcher Award

Department chair at Taif University, Saudi Arabia

Dr. Fahd Saad Alharithi is an accomplished researcher and academic with a Ph.D. in Computer Science from Florida Institute of Technology and extensive experience in both teaching and research. Currently an Assistant Professor at Taif University, his research spans a wide array of topics, including medical data categorization, oil spill detection, COVID-19 diagnosis, and IoT security. Dr. Alharithi has published numerous papers in high-impact journals such as Sensors and Remote Sensing, showcasing his innovative approaches and significant contributions to his field. In addition to his research, he has a strong background in teaching, having served as a lecturer and teaching assistant at various institutions. His involvement in volunteer work and leadership roles further highlights his commitment to community service. While his diverse research and impactful publications are noteworthy, highlighting research grants and awards could strengthen his profile for recognition.

Profile

Education

Dr. Fahd Saad Alharithi completed his educational journey with a strong foundation in Computer Science. He earned his Ph.D. from the Florida Institute of Technology, USA, in 2019, where he focused on advanced topics in the field. Prior to that, he obtained his Master of Science degree in Computer Science from the University of New Haven, USA, in 2013. His academic journey began with a Bachelor of Science degree in Computer Science from Taif University, Saudi Arabia, in 2008. This comprehensive educational background, spanning both international and local institutions, has equipped Dr. Alharithi with a robust theoretical and practical understanding of Computer Science, paving the way for his subsequent research and teaching career. His diverse educational experiences contribute significantly to his expertise and innovative approaches in the field.

Professional Experience

Dr. Fahd Saad Alharithi has garnered extensive experience in academia and education, currently serving as an Assistant Professor in the Computer Science Department at Taif University since 2019. His career began with roles as a Lecturer and Teacher Assistant at Taif University and the University of New Haven, where he honed his teaching and research skills. Dr. Alharithi has also contributed as a Trainer at New Horizons Institute, showcasing his versatility in the field. His professional journey is marked by significant research achievements, including innovative publications in medical data categorization, AI-assisted algorithms, and IoT security. His role extends beyond teaching, encompassing volunteer work with the Hemaya Group and leadership positions like President of the Saudi Student Club. Dr. Alharithi’s career reflects a robust blend of research excellence, educational dedication, and active community involvement.

Research Interest

Dr. Fahd Saad Alharithi’s research interests primarily focus on advancing computational methods and applications across various domains. His work explores medical data categorization using flexible mixture models, oil spill detection through SAR image analysis, and the development of hybrid convolutional neural network models for diagnosing diseases from chest X-ray images. Dr. Alharithi is also deeply involved in enhancing IoT security with AI-assisted bio-inspired algorithms and addressing environmental challenges through intelligent garbage detection systems. His research extends to secure communication protocols and energy-efficient solutions for sensor networks, demonstrating a strong emphasis on both practical and theoretical advancements. By integrating innovative methodologies such as deep learning and AI, Dr. Alharithi aims to address complex problems in medical imaging, environmental monitoring, and network security, reflecting a broad and impactful approach to computational science.

Research Skills

Dr. Fahd Saad Alharithi exhibits a robust set of research skills, underscored by his extensive work in computer science and related fields. His proficiency in advanced methodologies, including deep learning, AI-assisted algorithms, and hybrid models, highlights his capacity for innovative problem-solving. Dr. Alharithi’s experience with diverse data types and applications, such as medical data categorization, oil spill detection, and IoT security, demonstrates his ability to tackle complex, interdisciplinary challenges. His strong analytical skills are evident from his impactful publications in high-impact journals like Sensors and Remote Sensing. Additionally, his adeptness in leveraging various computational techniques and his commitment to exploring novel solutions further underscore his research capabilities. Dr. Alharithi’s contributions reflect a deep understanding of both theoretical and practical aspects of his field, positioning him as a skilled researcher with a significant impact on advancing technology and knowledge.

Award and Recognition

Dr. Fahd Saad Alharithi’s research has garnered considerable recognition within the academic community. He has published extensively in high-impact journals, including Sensors, Remote Sensing, and Computers, Materials & Continua, showcasing his significant contributions to fields such as medical data categorization, oil spill detection, and AI-assisted algorithms. His innovative work, particularly in developing hybrid convolutional neural network models and intelligent systems for garbage detection, underscores his leadership in advancing technology. Although specific awards and formal recognitions are not detailed in his resume, Dr. Alharithi’s influential publications and his role in mentoring and educating future researchers highlight his exceptional impact in computer science. His involvement in volunteer activities and community service further demonstrates his commitment to fostering academic and professional excellence.

Conclusion

Dr. Taimoor Asim is a strong candidate for the Best Researcher Award due to his substantial contributions to Mechanical Engineering, particularly in fluid dynamics and renewable energy systems. His extensive research experience, leadership roles, and professional achievements make him a noteworthy contender. To strengthen his candidacy, he could focus on broadening his research impact, exploring diverse research areas, and enhancing community engagement related to his work. Overall, Dr. Asim’s profile reflects a high level of expertise and dedication, aligning well with the criteria for the Best Researcher Award.

Publications Top Notes

  1. Machine learning approaches for advanced detection of rare genetic disorders in whole-genome sequencing
    • Authors: Alzahrani, A.A., Alharithi, F.S.
    • Journal: Alexandria Engineering Journal
    • Year: 2024
    • Volume: 106, pp. 582–593
  2. IoT-enabled healthcare systems using blockchain-dependent adaptable services
    • Authors: Arul, R., Alroobaea, R., Tariq, U., Alharithi, F.S., Shoaib, U.
    • Journal: Personal and Ubiquitous Computing
    • Year: 2024
    • Volume: 28(1), pp. 43–57
    • Citations: 13
  3. A comprehensive cost performance analysis for a QoS-based scheme in network mobility (NEMO)
    • Authors: Hussein, L.F., Abass, I.A.M., Aissa, A.B., Alzahrani, A.A., Alharithi, F.S.
    • Journal: Alexandria Engineering Journal
    • Year: 2023
    • Volume: 76, pp. 349–360
    • Citations: 1
  4. Performance Analysis of Machine Learning Approaches in Automatic Classification of Arabic Language
    • Authors: Alharithi, F.S.
    • Journal: Information Sciences Letters
    • Year: 2023
    • Volume: 12(3), pp. 1563–1578
    • Citations: 1
  5. A blockchain-based hybrid platform for multimedia data processing in IoT-Healthcare
    • Authors: Taloba, A.I., Elhadad, A., Rayan, A., Alharithi, F.S., Park, C.
    • Journal: Alexandria Engineering Journal
    • Year: 2023
    • Volume: 65, pp. 263–274
    • Citations: 74
  6. Optimal Sizing and Deployment of Renewable Energy Generators in Practical Transmission Network Using Grid-Oriented Multiobjective Harmony Search Algorithm for Loss Reduction and Voltage Profile Improvements
    • Authors: Kumar, P., Swarnkar, N.K., Mahela, O.P., Mazon, J.L.V., Alharithi, F.S.
    • Journal: International Transactions on Electrical Energy Systems
    • Year: 2023
    • Volume: 2023, 6315918
    • Citations: 1
  7. Energy-Aware Live VM Migration Using Ballooning in Cloud Data Center
    • Authors: Gupta, N., Gupta, K., Qahtani, A.M., Singh, A., Goyal, N.
    • Journal: Electronics (Switzerland)
    • Year: 2022
    • Volume: 11(23), 3932
    • Citations: 4
  8. NLP-Based Application for Analyzing Private and Public Banks Stocks Reaction to News Events in the Indian Stock Exchange
    • Authors: Dogra, V., Alharithi, F.S., Álvarez, R.M., Singh, A., Qahtani, A.M.
    • Journal: Systems
    • Year: 2022
    • Volume: 10(6), 233
    • Citations: 7
  9. Deep learned BLSTM for online handwriting modeling simulating the Beta-Elliptic approach
    • Authors: Hamdi, Y., Boubaker, H., Rabhi, B., Dhahri, H., Alimi, A.M.
    • Journal: Engineering Science and Technology, an International Journal
    • Year: 2022
    • Volume: 35, 101215
    • Citations: 6
  10. A software for thorax images analysis based on deep learning
    • Authors: Almulihi, A.H., Alharithi, F.S., Mechti, S., Alroobaea, R., Rubaiee, S.
    • Book Chapter: Research Anthology on Improving Medical Imaging Techniques for Analysis and Intervention
    • Year: 2022
    • Pages: 1166–1178

 

Mijanur Rahaman | Machin Learning | Excellence in Research

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Mr. Mijanur Rahaman | Machin Learning | Excellence in Research

Assistant Professor at Bangladesh University of Business and Technology (BUBT), Bangladesh.

Mr. Mijanur Rahaman is an accomplished professional with a rich background in academia, research, and teaching. With extensive experience in computer science and engineering, he has excelled in various roles, including Assistant Professor and Lecturer at Bangladesh University of Business & Technology (BUBT). His research interests span diverse areas such as peer-to-peer payment systems, job skill requirements during the COVID-19 pandemic, and web programming curriculum reform. Mr. Rahaman’s contributions to scholarly literature include several published articles in prestigious journals and conferences. Beyond academia, he has actively engaged in software development, database administration, and website design, demonstrating his versatility and technical prowess. His commitment to education, coupled with strong research and technical skills, positions him as a valuable asset in the field of computer science.

Professional Profiles:

Education

Mr. Mijanur Rahaman holds a Bachelor of Science in Engineering (B.Sc. Engg.) in Computer Science & Engineering (CSE) from Bangladesh University of Business & Technology (BUBT). He completed his higher secondary education (Higher Secondary School Certificate – HSC) in Science from Lakshmipur Govt. College and his secondary education (Secondary School Certificate – SSC) in Science from Rakhalia High School, both in Bangladesh. Additionally, he is currently pursuing a Master of Science (MSc) in Computer Science (MScCS) from the American International University-Bangladesh (AIUB).

Professional Experience

Mr. Mijanur Rahaman has extensive professional experience in the field of education and technology. He has served as an Assistant Professor of Computer Science and Engineering (CSE) at Bangladesh University of Business & Technology (BUBT) since February 2016. Prior to this, he worked as a Lecturer in CSE at BUBT from October 2011 to January 2015, and as a Teaching Assistant (TA) in CSE from March 2011 to September 2011. Additionally, he worked as a Part-time Lecturer at Dhaka Edinburgh International College from August 2010 to October 2010. In these roles, he has been actively involved in teaching, curriculum development, and student mentorship, demonstrating his commitment to academic excellence and professional development.

Research Interest

Mr. Mijanur Rahaman’s research interests primarily revolve around areas such as applied research methodology, digitalization, software development, job skill analysis, quantum computing, cloud computing, and web programming. He has contributed to various publications covering topics such as near field peer-to-peer payment systems, IT-software job skill requirements during the COVID-19 pandemic, optimal job allocation algorithms, state-of-the-art reformation of web programming course curriculums, and quantum computing as a service (Qcaas). His diverse research interests reflect his dedication to exploring cutting-edge technologies and their applications in solving real-world problems.

Teaching Experience

Mr. Mijanur Rahaman has extensive teaching experience spanning over a decade. His teaching journey started as a Teaching Assistant (TA) in the Department of Computer Science and Engineering (CSE) at Bangladesh University of Business & Technology (BUBT) in March 2011. From there, he progressed to the role of Lecturer in CSE, where he continued to impart knowledge and motivate students until January 2015. Subsequently, he transitioned to the position of Assistant Professor of CSE at BUBT, where he has been serving since February 2016. Throughout his tenure, Mr. Rahaman has demonstrated a commitment to challenging and inspiring students through in-depth lectures, discussions, and hands-on learning experiences. Additionally, he has actively contributed to curriculum development and research activities, enriching the academic environment of his institution.

Award and Honors

Mr. Mijanur Rahaman has received numerous awards and honors throughout his career, recognizing his significant contributions to academia and programming contests. Notably, he excelled as a contestant in prestigious competitions like the ACM-ICPC Asia Regional Dhaka Site in 2010, where his team achieved the 13th place, and the 2008 Asia Dhaka Contest. His achievements also include receiving an Honorable Mention at the AB Bank-IUT 2nd National ICT Fest 2009. Beyond his individual accomplishments, Mr. Rahaman has demonstrated leadership as a coach for programming contest teams and as Chief Judge at the BUBT Intra-university Programming Contest 2015. Moreover, he has been invited to high-profile events such as the ICPC World Final 2021 and the ACM-ICPC Asia Dhaka Regional Contest, where he served in key roles. His active involvement in academic and extracurricular activities further underscores his commitment to fostering learning and innovation within the community.

Research Skills

Mr. Mijanur Rahaman possesses advanced research skills honed through years of academic and professional experience. His expertise encompasses various methodologies, including quantitative and qualitative research methods, literature reviews, experimental design, and data analysis techniques. He is proficient in utilizing statistical software such as SPSS, R, and Minitab for data analysis and interpretation. Moreover, Mr. Rahaman demonstrates strong critical thinking abilities, enabling him to formulate research questions, develop hypotheses, and design rigorous research studies. His keen attention to detail ensures the accuracy and reliability of research findings, while his effective communication skills enable him to disseminate research results through scholarly publications and presentations. Additionally, he stays abreast of emerging trends and best practices in his field, continually refining his research skills to contribute meaningfully to the advancement of knowledge in computer science and related disciplines.

Publications

  1. Utilizing EfficientNet for sheep breed identification in low-resolution images
    • Authors: Himel, G.M.S.; Islam, M.M.; Rahaman, M.
    • Year: 2024
    • Citations: 0
    • Type: Article
  2. Vision Intelligence for Smart Sheep Farming: Applying Ensemble Learning to Detect Sheep Breeds
    • Authors: Himel, G.M.S.; Islam, M.M.; Rahaman, M.
    • Year: 2024
    • Citations: 1
    • Type: Article
  3. An Empirical Analysis of IT-Software Job Skill Requirements During COVID-19 Pandemic Period in Bangladesh
    • Authors: Rahaman, M.; Islam, M.M.; Rahman, M.S.
    • Year: 2023
    • Citations: 0
    • Type: Conference Paper
  4. Knowledge, attitude, and practice of a local community towards the prevention and control of rabies in Gaibandha, Bangladesh
    • Authors: Rahaman, M.M.; Siddiqi, U.R.; Sabuj, A.A.M.; Ghosh, S.; Uddin, N.
    • Year: 2020
    • Citations: 7
    • Type: Article
  5. State-of-the-art reformation of web programming course curriculum in digital Bangladesh
    • Authors: Kar, S.; Islam, M.M.; Rahaman, M.
    • Year: 2020
    • Citations: 3
    • Type: Article

Praveen Naik | Artificial Intelligence Award | Best Researcher Award

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Mr. Praveen Naik | Artificial Intelligence Award | Best Researcher Award

Researcher at Meru University of Science and Technology, Kenya

Mr. Erick Mutwiri Kirimi is a dedicated and accomplished individual with a strong background in mathematics. With a Bachelor’s degree in Education Science and ongoing PhD studies in Computational and Applied Mathematics, he has developed a deep understanding of mathematical concepts and their practical applications. Mr. Kirimi’s academic journey includes serving as a part-time lecturer at several universities, where he imparts his knowledge to students. He has also gained valuable teaching experience as a mathematics and chemistry teacher, including serving as the Head of the Mathematics Department. His academic achievements are further highlighted by scholarships, including a full scholarship for his PhD studies in Computational Mathematics and a partial scholarship for his PhD studies in Applied Mathematics. These scholarships reflect his commitment to academic excellence and his potential to make significant contributions to the field of mathematics. Mr. Kirimi’s research skills, teaching abilities, leadership qualities, computer proficiency, and strong communication and interpersonal skills make him a well-rounded individual poised for success in his academic and professional endeavors.

Professional Profiles:

Professional Experience:

Praveen Naik has been a Research Fellow at the National Institute of Technology Karnataka, Surathkal since 2020. In this role, he has conducted research on “Investigation of Arecanut Images for Grading through Non-Destructive Methods.” His contributions to the project include dataset curation, the development of a lightweight and efficient model, implementation of an Adaptive Genetic-Based Model Optimization, introduction of a non-destructive methodology, and successful resolution of Arecanut grading challenges. Prior to his current position, Praveen Naik served as a Senior Assistant Professor at Shri Madhwa Vadiraja Institute of Technology and Management from 2013 to 2020. During this time, he managed a variety of subjects, crafted compelling curricula, and conducted impactful lectures. He also provided mentorship to students, collaborated seamlessly with peers, and efficiently managed administrative responsibilities within the academic setting. From 2010 to 2011, Praveen Naik worked as a Software Programmer at SouthCan Software, where he played a pivotal role in the Milk Dairy Project. His responsibilities included supervising day-to-day dairy operations, overseeing tasks such as data entry, manipulation, and transactions. He also contributed to report customization using SQL-Server Reporting Service, thereby enhancing reporting functionalities for the organization.

Academic:

Since 2020, Praveen Naik has been pursuing a Ph.D. in Information Technology at the National Institute of Technology Karnataka, Surathkal. Prior to this, he completed his M.Tech in Computer Science and Engineering from Atria Institute of Technology, Bengaluru, from 2011 to 2013. Praveen’s academic journey began with a Bachelor’s degree in Information Science and Engineering from Nitte Mahalinga Adyanthaya Memorial Institute of Technology, Nitte, which he completed from 2006 to 2010.

Areas of Specialization:

Praveen Naik has specialized expertise in Object Detection, Model Optimization, and Deep Learning, with a focus on YOLOv5. His experience includes extensive work in Dataset Curation, ensuring high-quality data inputs for machine learning models.

Achievements:

Praveen Naik has demonstrated his academic prowess by qualifying in several prestigious examinations. He cleared the GATE (Graduate Aptitude Test in Engineering) in 2020, showcasing his proficiency in engineering concepts. Additionally, he achieved qualification in the UGC-NET (University Grants Commission – National Eligibility Test) in 2020, indicating his in-depth knowledge and understanding of his field. Furthermore, he passed the K-SET (Karnataka State Eligibility Test) in 2019, demonstrating his expertise and competence in the field of education.

Publications:

  1. Flower Phenotype Recognition and Analysis using YoloV5 Models
    • Authors: PM Naik, B Rudra
    • Year: 2022
    • Journal: Grenze International Journal of Engineering & Technology (GIJET)
    • Volume: 8
    • Issue: 2
    • Citations: 3
  2. Deep learning-based arecanut detection for X-ray radiography: improving performance and efficiency for automated classification and quality control
    • Authors: PM Naik, B Rudra
    • Year: 2024
    • Journal: Nondestructive Testing and Evaluation
    • Pages: 1-21
  3. Classification of Arecanut X-Ray Images for Quality Assessment Using Adaptive Genetic Algorithm and Deep Learning
    • Authors: PM Naik, B Rudra
    • Year: 2023
    • Journal: IEEE Access
    • Volume: 11
    • Pages: 127619-127636
  4. Prevention of Webshell Attack using Machine Learning Techniques
    • Authors: S YC, PM Naik, B Rudra
    • Year: 2021
    • Journal: Grenze International Journal of Engineering & Technology (GIJET)
    • Volume: 7
    • Issue: 1