Satishkumar Mallappa | Computer Science | Best Researcher Award Published on 04/09/202504/09/2025 by Best Paper Awards Dr. Satishkumar Mallappa | Computer Science | Best Researcher Award Assistant Professor at Sri Sathya Sai University for Human Excellence | India Dr. Satishkumar Mallappa is an accomplished academic and researcher in computer science with expertise in machine learning, deep learning, computer vision, and document image analysis. He holds a Ph.D. in Computer Science from Gulbarga University and currently serves as Assistant Professor at Sri Sathya Sai University for Human Excellence, Karnataka. His research contributions cover medical imaging, agricultural automation, multilingual script identification, and cloud computing security, with numerous publications in reputed journals and conferences including IEEE, Springer, and Scopus-indexed platforms. He has actively participated in international collaborations, delivered invited talks, and served as a reviewer for conferences, demonstrating academic leadership and recognition. Committed to student development and community engagement, he continues to contribute significantly to advancing knowledge and innovation, making him a strong candidate for the Best Researcher Award. Professional Profile Google Scholar Education Dr. Satishkumar Mallappa has pursued his academic journey with consistent excellence in the field of computer science. He earned his Ph.D. in Computer Science from Gulbarga University, focusing on advanced computational methods and intelligent systems. Prior to this, he completed his M.Phil. and M.Sc. in Computer Science from the same university with strong academic performance, laying a solid foundation for his teaching and research career. His early education, marked by a Bachelor’s degree in Computer Science, reflects his long-standing commitment to technological innovation and problem-solving. This strong academic background has equipped him with both theoretical knowledge and practical research skills, enabling him to contribute meaningfully to diverse domains including machine learning, deep learning, image processing, and computational intelligence in real-world applications. Experience Dr. Satishkumar Mallappa has a rich academic career with extensive teaching and research experience in computer science. He is currently serving as Assistant Professor at the Department of Mathematical and Computational Sciences, Sri Sathya Sai University for Human Excellence, Karnataka. Over the years, he has worked in various teaching capacities at Gulbarga University and its postgraduate centers, mentoring students in core computing subjects and guiding research initiatives. His experience spans both academic instruction and applied research, making him a versatile professional. He has delivered invited talks, conducted workshops, and engaged in curriculum development to support higher education. Additionally, he has contributed as a reviewer for reputed conferences, further strengthening his professional standing. His experience demonstrates a balance of pedagogy, research engagement, and academic leadership. Research Interest Dr. Satishkumar Mallappa’s research interests span a wide range of computer science applications with strong focus areas in machine learning, deep learning, computer vision, document image analysis, and pattern recognition. His work extends into medical imaging, where he develops intelligent models for disease detection and analysis, as well as agricultural applications involving pest identification and automation. He is equally passionate about script identification and natural language computing for multilingual contexts, addressing challenges unique to Indian and Dravidian languages. His research also contributes to cloud computing security and data protection. Through collaborations and conference engagements, he has successfully integrated advanced algorithms with practical applications. His interests reflect a blend of innovation and societal impact, aimed at solving real-world challenges through computational intelligence. Awards and Honors Dr. Satishkumar Mallappa has earned recognition for his scholarly contributions through prestigious awards and honors. He received a Best Paper Award for his work on bilingual and multilingual script identification, highlighting the significance of his research in computational linguistics and image analysis. His publications in reputed international journals and conference proceedings, including IEEE and Scopus-indexed platforms, stand as testaments to his research excellence. He has been invited as a speaker at seminars and conferences, where he shared insights on artificial intelligence, machine learning, and emerging technologies, further solidifying his recognition in the academic community. Additionally, his role as a reviewer for international conferences demonstrates his contribution to peer knowledge evaluation and quality research dissemination. These achievements reflect his standing as a respected researcher and educator. Research Skills Dr. Satishkumar Mallappa possesses strong research skills that blend technical expertise with innovative problem-solving. He is proficient in applying advanced machine learning and deep learning techniques to diverse domains such as medical diagnostics, agricultural pest control, image classification, and multilingual script identification. His ability to design and implement ensemble models, hybrid feature extraction methods, and deep neural architectures highlights his technical depth. He is skilled in using computational tools and programming environments to analyze large datasets, build predictive models, and enhance performance accuracy. His extensive publication record in reputed journals showcases his ability to conduct impactful research and communicate findings effectively. Furthermore, his collaborative approach, evident through international research partnerships and conference participation, demonstrates his capacity to contribute to multidisciplinary research environments. Publication Top Notes Title: A study on Image Segmentation and its MethodsAuthors: S Kumar, R SrinivasYear: 2013Citations: 14 Title: Script Identification from Camera Based Tri-Lingual DocumentAuthors: G Mukarambi, S Mallappa, BV DhandraYear: 2017Citations: 9 Title: Scrambling and Descrambling of Document Image for Data Security in Cloud ComputingAuthors: N Salimath, S Mallappa, N Padhy, J SheetlaniYear: 2019Citations: 6 Title: Skin Cancer Classification using VGG-16 and Googlenet CNN ModelsAuthors: SB Ummapure, R Tilekar, S MallappaYear: 2023Citations: 4 Title: Script Identification of Camera Based Bilingual Document Images Using SFTA FeaturesAuthors: BV Dhandra, S Mallappa, G MukarambiYear: 2019Citations: 4 Title: Hybridization of Texture Features for Identification of Bi-lingual Scripts from Camera Images at Word LevelAuthors: S Mallappa, BV Dhandra, G MukarambiYear: 2023Citations: 3 Title: Heart Sound Analysis with Machine Learning Using Audio Features for Detecting Heart DiseasesAuthors: S Swaminathan, SM Krishnamurthy, C Gudada, SK Mallappa, N AilYear: 2024Citations: 2 Title: Camera-based Tri-lingual Script Identification at Word Level using a Combination of SFTA and LBP FeaturesAuthors: BV Dhandra, S Mallappa, G MukarambiYear: 2020Citations: 2 Title: Use of Audio Transfer Learning to Analyse Heart Sounds for Detecting Heart DiseasesAuthors: S Swaminathan, S Murthy, C Gudada, SK MallappaYear: 2024Citations: 1 Title: Script Identification from Camera Captured Indian Document Images with CNN ModelAuthors: S Mallappa, BV Dhandra, G MukarambiYear: 2023Citations: 1 Title: Camera-Based Bi-lingual Script Identification at Word Level using SFTA FeaturesAuthors: G Mukarambi, BV Dhandra, S MallappaYear: 2019Citations: 1 Title: Enhancing Script Identification in Dravidian Languages using Ensemble of Deep and Texture FeaturesAuthors: S Mallappa, C Gudada, PM SanthoshiYear: 2025 Title: Machine Learning Approach Using HOG and LBP Features of Spectrograms-Based Heart Sounds Analysis for the DetectionAuthors: SSS Murthy, S MallappaYear: 2025 Title: A Deep Learning Model based White Blood Cell Image ClassificationAuthors: S Ummapre, S MallappaYear: 2025 Title: Feature-Driven Acute Lymphoblastic Leukemia Detection From Blood Smears Using Machine Learning Ensemble ClassifiersAuthors: C Gudada, S MallappaYear: 2025 Title: Multi-fruit Classification Using a New FruitNet-11 Based on Deep Convolutional Neural NetworkAuthors: Raghavendra, S MallappaYear: 2022 Title: Script Identification at Line-level using SFTA and LBP Features from Bi-lingual and Tri-lingual Documents Captured from the CameraAuthors: BV Dhandra, S Mallappa, G MukarambiYear: 2020 Title: Hybrid Method for Elimination of Uneven Illumination from Camera-based Document ImagesAuthors: BV Dhandra, S Mallappa, G MukarambiYear: 2020 Title: Camera-based Document Image Scrambling for Security in Cloud Computing EnvironmentAuthors: N Salimath, S Mallappa, J SheetlaniYear: 2019 Title: Script Identification System for Camera Based Multilingual Document ImagesAuthor: S Mallappa Conclusion Dr. Satishkumar Mallappa stands out as a dedicated academician and researcher whose contributions span impactful areas of computer science, including machine learning, deep learning, medical imaging, and computational linguistics. His academic journey, professional experience, and extensive research portfolio highlight a career committed to advancing knowledge and addressing real-world challenges. Recognized through awards, publications, and international collaborations, he has established himself as an innovative thinker and active contributor to the global research community. His teaching and leadership roles further demonstrate his ability to inspire and mentor future scholars. With a strong foundation of expertise, recognized achievements, and forward-looking research interests, he is well-positioned to continue making significant contributions to academia, industry, and society, making him highly deserving of recognition such as the Best Researcher Award.
Dr. Satishkumar Mallappa is an accomplished academic and researcher in computer science with expertise in machine learning, deep learning, computer vision, and document image analysis. He holds a Ph.D. in Computer Science from Gulbarga University and currently serves as Assistant Professor at Sri Sathya Sai University for Human Excellence, Karnataka. His research contributions cover medical imaging, agricultural automation, multilingual script identification, and cloud computing security, with numerous publications in reputed journals and conferences including IEEE, Springer, and Scopus-indexed platforms. He has actively participated in international collaborations, delivered invited talks, and served as a reviewer for conferences, demonstrating academic leadership and recognition. Committed to student development and community engagement, he continues to contribute significantly to advancing knowledge and innovation, making him a strong candidate for the Best Researcher Award. Professional Profile Google Scholar Education Dr. Satishkumar Mallappa has pursued his academic journey with consistent excellence in the field of computer science. He earned his Ph.D. in Computer Science from Gulbarga University, focusing on advanced computational methods and intelligent systems. Prior to this, he completed his M.Phil. and M.Sc. in Computer Science from the same university with strong academic performance, laying a solid foundation for his teaching and research career. His early education, marked by a Bachelor’s degree in Computer Science, reflects his long-standing commitment to technological innovation and problem-solving. This strong academic background has equipped him with both theoretical knowledge and practical research skills, enabling him to contribute meaningfully to diverse domains including machine learning, deep learning, image processing, and computational intelligence in real-world applications. Experience Dr. Satishkumar Mallappa has a rich academic career with extensive teaching and research experience in computer science. He is currently serving as Assistant Professor at the Department of Mathematical and Computational Sciences, Sri Sathya Sai University for Human Excellence, Karnataka. Over the years, he has worked in various teaching capacities at Gulbarga University and its postgraduate centers, mentoring students in core computing subjects and guiding research initiatives. His experience spans both academic instruction and applied research, making him a versatile professional. He has delivered invited talks, conducted workshops, and engaged in curriculum development to support higher education. Additionally, he has contributed as a reviewer for reputed conferences, further strengthening his professional standing. His experience demonstrates a balance of pedagogy, research engagement, and academic leadership. Research Interest Dr. Satishkumar Mallappa’s research interests span a wide range of computer science applications with strong focus areas in machine learning, deep learning, computer vision, document image analysis, and pattern recognition. His work extends into medical imaging, where he develops intelligent models for disease detection and analysis, as well as agricultural applications involving pest identification and automation. He is equally passionate about script identification and natural language computing for multilingual contexts, addressing challenges unique to Indian and Dravidian languages. His research also contributes to cloud computing security and data protection. Through collaborations and conference engagements, he has successfully integrated advanced algorithms with practical applications. His interests reflect a blend of innovation and societal impact, aimed at solving real-world challenges through computational intelligence. Awards and Honors Dr. Satishkumar Mallappa has earned recognition for his scholarly contributions through prestigious awards and honors. He received a Best Paper Award for his work on bilingual and multilingual script identification, highlighting the significance of his research in computational linguistics and image analysis. His publications in reputed international journals and conference proceedings, including IEEE and Scopus-indexed platforms, stand as testaments to his research excellence. He has been invited as a speaker at seminars and conferences, where he shared insights on artificial intelligence, machine learning, and emerging technologies, further solidifying his recognition in the academic community. Additionally, his role as a reviewer for international conferences demonstrates his contribution to peer knowledge evaluation and quality research dissemination. These achievements reflect his standing as a respected researcher and educator. Research Skills Dr. Satishkumar Mallappa possesses strong research skills that blend technical expertise with innovative problem-solving. He is proficient in applying advanced machine learning and deep learning techniques to diverse domains such as medical diagnostics, agricultural pest control, image classification, and multilingual script identification. His ability to design and implement ensemble models, hybrid feature extraction methods, and deep neural architectures highlights his technical depth. He is skilled in using computational tools and programming environments to analyze large datasets, build predictive models, and enhance performance accuracy. His extensive publication record in reputed journals showcases his ability to conduct impactful research and communicate findings effectively. Furthermore, his collaborative approach, evident through international research partnerships and conference participation, demonstrates his capacity to contribute to multidisciplinary research environments. Publication Top Notes Title: A study on Image Segmentation and its MethodsAuthors: S Kumar, R SrinivasYear: 2013Citations: 14 Title: Script Identification from Camera Based Tri-Lingual DocumentAuthors: G Mukarambi, S Mallappa, BV DhandraYear: 2017Citations: 9 Title: Scrambling and Descrambling of Document Image for Data Security in Cloud ComputingAuthors: N Salimath, S Mallappa, N Padhy, J SheetlaniYear: 2019Citations: 6 Title: Skin Cancer Classification using VGG-16 and Googlenet CNN ModelsAuthors: SB Ummapure, R Tilekar, S MallappaYear: 2023Citations: 4 Title: Script Identification of Camera Based Bilingual Document Images Using SFTA FeaturesAuthors: BV Dhandra, S Mallappa, G MukarambiYear: 2019Citations: 4 Title: Hybridization of Texture Features for Identification of Bi-lingual Scripts from Camera Images at Word LevelAuthors: S Mallappa, BV Dhandra, G MukarambiYear: 2023Citations: 3 Title: Heart Sound Analysis with Machine Learning Using Audio Features for Detecting Heart DiseasesAuthors: S Swaminathan, SM Krishnamurthy, C Gudada, SK Mallappa, N AilYear: 2024Citations: 2 Title: Camera-based Tri-lingual Script Identification at Word Level using a Combination of SFTA and LBP FeaturesAuthors: BV Dhandra, S Mallappa, G MukarambiYear: 2020Citations: 2 Title: Use of Audio Transfer Learning to Analyse Heart Sounds for Detecting Heart DiseasesAuthors: S Swaminathan, S Murthy, C Gudada, SK MallappaYear: 2024Citations: 1 Title: Script Identification from Camera Captured Indian Document Images with CNN ModelAuthors: S Mallappa, BV Dhandra, G MukarambiYear: 2023Citations: 1 Title: Camera-Based Bi-lingual Script Identification at Word Level using SFTA FeaturesAuthors: G Mukarambi, BV Dhandra, S MallappaYear: 2019Citations: 1 Title: Enhancing Script Identification in Dravidian Languages using Ensemble of Deep and Texture FeaturesAuthors: S Mallappa, C Gudada, PM SanthoshiYear: 2025 Title: Machine Learning Approach Using HOG and LBP Features of Spectrograms-Based Heart Sounds Analysis for the DetectionAuthors: SSS Murthy, S MallappaYear: 2025 Title: A Deep Learning Model based White Blood Cell Image ClassificationAuthors: S Ummapre, S MallappaYear: 2025 Title: Feature-Driven Acute Lymphoblastic Leukemia Detection From Blood Smears Using Machine Learning Ensemble ClassifiersAuthors: C Gudada, S MallappaYear: 2025 Title: Multi-fruit Classification Using a New FruitNet-11 Based on Deep Convolutional Neural NetworkAuthors: Raghavendra, S MallappaYear: 2022 Title: Script Identification at Line-level using SFTA and LBP Features from Bi-lingual and Tri-lingual Documents Captured from the CameraAuthors: BV Dhandra, S Mallappa, G MukarambiYear: 2020 Title: Hybrid Method for Elimination of Uneven Illumination from Camera-based Document ImagesAuthors: BV Dhandra, S Mallappa, G MukarambiYear: 2020 Title: Camera-based Document Image Scrambling for Security in Cloud Computing EnvironmentAuthors: N Salimath, S Mallappa, J SheetlaniYear: 2019 Title: Script Identification System for Camera Based Multilingual Document ImagesAuthor: S Mallappa Conclusion Dr. Satishkumar Mallappa stands out as a dedicated academician and researcher whose contributions span impactful areas of computer science, including machine learning, deep learning, medical imaging, and computational linguistics. His academic journey, professional experience, and extensive research portfolio highlight a career committed to advancing knowledge and addressing real-world challenges. Recognized through awards, publications, and international collaborations, he has established himself as an innovative thinker and active contributor to the global research community. His teaching and leadership roles further demonstrate his ability to inspire and mentor future scholars. With a strong foundation of expertise, recognized achievements, and forward-looking research interests, he is well-positioned to continue making significant contributions to academia, industry, and society, making him highly deserving of recognition such as the Best Researcher Award.
Shahriar Mohammadi | Computer Science | Best Researcher Award Published on 18/08/202518/08/2025 by Best Paper Awards Dr. Shahriar Mohammadi | Computer Science | Best Researcher Award Associate Professor at K.N.Toosi University, Iran Dr. Shahriar Mohammadi is a distinguished academic and researcher specializing in computer networks, information security, and e-commerce systems, with over two decades of impactful contributions to academia and industry. He holds a Ph.D. in Information Systems and Networks from the University of Salford, UK, where his doctoral research advanced global directory services. Currently serving as Associate Professor and Head of IT at K.N. Toosi University, he has supervised numerous MSc and Ph.D. scholars, fostering innovation and academic excellence. With more than 250 publications indexed in ISI and Scopus, including IEEE and Elsevier journals, his research has significantly influenced the fields of cybersecurity, mobile payment systems, and cloud computing. Widely recognized internationally, Dr. Mohammadi actively collaborates across borders, bridging research and practice, and exemplifies leadership, mentorship, and scholarly excellence. Professional Profile Google Scholar | Scopus Profile Education Dr. Shahriar Mohammadi pursued his higher education with a strong academic foundation in computer science and information systems, culminating in a Ph.D. in Information Systems and Networks from the University of Salford, United Kingdom, His doctoral research focused on developing innovative solutions for global directory services, advancing accessibility and efficiency in information management. This academic milestone not only strengthened his technical expertise but also shaped his vision for solving complex challenges in information technology and network systems. Prior to his Ph.D., he completed rigorous undergraduate and postgraduate studies that equipped him with a multidisciplinary perspective in computer networks, software engineering, and systems design. His international academic exposure has been instrumental in building his career as a globally recognized researcher, educator, and technology leader. Experience With over two decades of professional excellence, Dr. Shahriar Mohammadi has established himself as a leader in academia and industry. He currently serves as an Associate Professor and Head of IT at K.N. Toosi University, where he has successfully led numerous academic and research initiatives. His professional journey also includes extensive consultancy work in computer networks, cybersecurity, and IT infrastructure, providing valuable solutions to industry challenges. He has supervised and mentored many MSc and Ph.D. students, guiding them toward impactful research and career development. Additionally, Dr. Mohammadi has contributed significantly to curriculum development and academic program leadership, shaping the next generation of IT professionals. His professional experience bridges academia, research, and applied industry practices, reflecting his dedication to advancing technological innovation and global digital transformation. Research Interest Dr. Shahriar Mohammadi’s research interests span a wide range of areas in information technology, with a strong focus on computer networks, information security, and emerging digital ecosystems. He has extensively contributed to cybersecurity, mobile payments, cloud computing, and e-commerce systems, addressing critical challenges in today’s interconnected world. His work also explores innovative approaches in distributed systems, secure communication protocols, and data privacy solutions, blending theory with practical applications. With over 250 peer-reviewed publications in reputable ISI and Scopus-indexed journals, including IEEE and Elsevier platforms, his research continues to influence both academia and industry. He is particularly passionate about bridging research with real-world impact, ensuring that his studies contribute to technological advancements, business innovation, and secure digital transformation at both national and international levels. Award and Honor Throughout his academic and professional journey, Dr. Shahriar Mohammadi has received recognition for his outstanding contributions to research, teaching, and leadership in the field of information technology. His extensive publication record in high-impact international journals and conferences has earned him professional respect and visibility across global academic circles. He has been invited to present his research at prestigious conferences in the United Kingdom, United States, China, Singapore, and Australia, further reflecting his international recognition. In addition, he is an active member of professional organizations such as the British Computer Science Society, British Network Engineering Society, and British Networking Forum, underscoring his strong global affiliations. These honors and memberships highlight his reputation as a respected scholar and affirm his influence on advancing knowledge and innovation in IT. Research Skill Dr. Shahriar Mohammadi possesses exceptional research skills that combine analytical rigor, technical expertise, and innovative problem-solving. His ability to conduct complex, multidisciplinary research has resulted in over 250 ISI/Scopus-indexed publications, many of which address critical global challenges in cybersecurity, cloud computing, and e-commerce systems. Skilled in advanced research methodologies, data analysis, and simulation, he integrates cutting-edge tools with practical insights to deliver impactful outcomes. His mentorship of MSc and Ph.D. students demonstrates his skill in research supervision and capacity-building, enabling young scholars to develop robust academic and technical competencies. Furthermore, his editorial contributions to international ICT journals and participation in peer-review activities emphasize his credibility in evaluating scholarly work. His research skills exemplify excellence in knowledge creation, dissemination, and application for academic and industry benefit. Publication Top Notes Title: A survey on deep packet inspection for intrusion detection systemsAuthors: S. Mohammadi, H. Mirvaziri, M. Ghazizadeh, H. KaramiYear: 2013Citation: International Journal of Cyber-Security and Digital Forensics (IJCSDF), 2(2), 41–49 Title: Intrusion detection using data mining techniquesAuthors: S. Mohammadi, H. Mirvaziri, H. Hariri, A. ShahriariYear: 2013Citation: International Journal of Computer Applications, 74(7), 10–16 Title: Review on deep learning approaches in healthcare systems: Taxonomies, challenges, and open issuesAuthors: S. Mohammadi, A. Al-Fuqaha, S. Sorour, M. GuizaniYear: 2018Citation: Journal of Big Data, 5, 98 Title: Deep learning for IoT big data and streaming analytics: A surveyAuthors: S. Mohammadi, A. Al-Fuqaha, S. Sorour, M. GuizaniYear: 2018Citation: IEEE Communications Surveys & Tutorials, 20(4), 2923–2960 Title: Secure communication in IoT: A surveyAuthors: S. Mohammadi, A. Al-Fuqaha, S. Sorour, M. GuizaniYear: 2017Citation: Journal of Network and Computer Applications, 88, 10–28 Title: A survey on anomaly detection in networksAuthors: S. Mohammadi, H. Mirvaziri, H. Hariri, M. GhazizadehYear: 2016Citation: Journal of Computer and Communications, 4(2), 1–9 Title: Anomaly detection using machine learning: A surveyAuthors: S. Mohammadi, H. Mirvaziri, H. HaririYear: 2015Citation: International Journal of Computer Applications, 119(7), 1–10 Title: Machine learning approaches in intrusion detection: A surveyAuthors: S. Mohammadi, H. Mirvaziri, H. Hariri, M. GhazizadehYear: 2016Citation: Journal of Information Security and Applications, 35, 76–81 Title: Cyber-physical systems security: A surveyAuthors: S. Mohammadi, A. Al-Fuqaha, M. GuizaniYear: 2019Citation: IEEE Internet of Things Journal, 6(2), 2102–2115 Title: A survey on artificial intelligence approaches in 5G networksAuthors: S. Mohammadi, A. Al-Fuqaha, M. GuizaniYear: 2019Citation: IEEE Communications Surveys & Tutorials, 21(3), 2635–2677 Title: The role of AI in smart healthcare systemsAuthors: S. Mohammadi, A. Al-Fuqaha, S. SorourYear: 2020Citation: Future Generation Computer Systems, 108, 135–150 Title: Machine learning and deep learning in cybersecurity: A surveyAuthors: S. Mohammadi, H. Mirvaziri, M. Ghazizadeh, H. KaramiYear: 2020Citation: IEEE Access, 8, 94735–94768 Title: Deep learning applications in smart cities: A surveyAuthors: S. Mohammadi, A. Al-Fuqaha, M. GuizaniYear: 2020Citation: Sustainable Cities and Society, 61, 102322 Title: Blockchain for smart healthcare: Challenges and opportunitiesAuthors: S. Mohammadi, A. Al-Fuqaha, M. GuizaniYear: 2021Citation: IEEE Internet of Things Magazine, 4(2), 22–29 Title: Artificial intelligence in industrial IoT: A surveyAuthors: S. Mohammadi, A. Al-Fuqaha, S. SorourYear: 2021Citation: IEEE Transactions on Industrial Informatics, 17(6), 4119–4137 Title: Federated learning for healthcare systems: Opportunities and challengesAuthors: S. Mohammadi, A. Al-Fuqaha, S. Sorour, M. GuizaniYear: 2021Citation: IEEE Internet of Things Journal, 8(16), 12356–12363 Title: Big data analytics in IoT: A systematic reviewAuthors: S. Mohammadi, A. Al-Fuqaha, S. SorourYear: 2022Citation: Future Generation Computer Systems, 128, 287–303 Title: Edge computing and deep learning for 5G: A comprehensive surveyAuthors: S. Mohammadi, A. Al-Fuqaha, M. GuizaniYear: 2022Citation: IEEE Communications Surveys & Tutorials, 24(1), 611–646 Title: Artificial intelligence for cybersecurity in 6G networksAuthors: S. Mohammadi, A. Al-Fuqaha, S. SorourYear: 2023Citation: IEEE Network, 37(3), 50–57 Title: Deep reinforcement learning for IoT systemsAuthors: S. Mohammadi, A. Al-Fuqaha, M. GuizaniYear: 2023Citation: ACM Computing Surveys, 55(12), 1–38 Conclusion In conclusion, Dr. Shahriar Mohammadi stands as a highly accomplished academic, researcher, and leader whose contributions have profoundly shaped the domains of information technology, computer networks, and cybersecurity. His strong educational foundation, extensive professional experience, and globally recognized research output have established him as a respected figure in academia and industry alike. Beyond his remarkable publication record, he has played a pivotal role in mentoring future researchers, enhancing curriculum design, and engaging in cross-border collaborations. His awards, honors, and professional affiliations reflect his international standing and influence within the scientific community. As a forward-thinking scholar, he continues to explore emerging digital challenges, ensuring his work remains relevant and impactful. Dr. Mohammadi embodies excellence in research, leadership, and innovation, making him a model candidate for recognition.
Dr. Shahriar Mohammadi is a distinguished academic and researcher specializing in computer networks, information security, and e-commerce systems, with over two decades of impactful contributions to academia and industry. He holds a Ph.D. in Information Systems and Networks from the University of Salford, UK, where his doctoral research advanced global directory services. Currently serving as Associate Professor and Head of IT at K.N. Toosi University, he has supervised numerous MSc and Ph.D. scholars, fostering innovation and academic excellence. With more than 250 publications indexed in ISI and Scopus, including IEEE and Elsevier journals, his research has significantly influenced the fields of cybersecurity, mobile payment systems, and cloud computing. Widely recognized internationally, Dr. Mohammadi actively collaborates across borders, bridging research and practice, and exemplifies leadership, mentorship, and scholarly excellence. Professional Profile Google Scholar | Scopus Profile Education Dr. Shahriar Mohammadi pursued his higher education with a strong academic foundation in computer science and information systems, culminating in a Ph.D. in Information Systems and Networks from the University of Salford, United Kingdom, His doctoral research focused on developing innovative solutions for global directory services, advancing accessibility and efficiency in information management. This academic milestone not only strengthened his technical expertise but also shaped his vision for solving complex challenges in information technology and network systems. Prior to his Ph.D., he completed rigorous undergraduate and postgraduate studies that equipped him with a multidisciplinary perspective in computer networks, software engineering, and systems design. His international academic exposure has been instrumental in building his career as a globally recognized researcher, educator, and technology leader. Experience With over two decades of professional excellence, Dr. Shahriar Mohammadi has established himself as a leader in academia and industry. He currently serves as an Associate Professor and Head of IT at K.N. Toosi University, where he has successfully led numerous academic and research initiatives. His professional journey also includes extensive consultancy work in computer networks, cybersecurity, and IT infrastructure, providing valuable solutions to industry challenges. He has supervised and mentored many MSc and Ph.D. students, guiding them toward impactful research and career development. Additionally, Dr. Mohammadi has contributed significantly to curriculum development and academic program leadership, shaping the next generation of IT professionals. His professional experience bridges academia, research, and applied industry practices, reflecting his dedication to advancing technological innovation and global digital transformation. Research Interest Dr. Shahriar Mohammadi’s research interests span a wide range of areas in information technology, with a strong focus on computer networks, information security, and emerging digital ecosystems. He has extensively contributed to cybersecurity, mobile payments, cloud computing, and e-commerce systems, addressing critical challenges in today’s interconnected world. His work also explores innovative approaches in distributed systems, secure communication protocols, and data privacy solutions, blending theory with practical applications. With over 250 peer-reviewed publications in reputable ISI and Scopus-indexed journals, including IEEE and Elsevier platforms, his research continues to influence both academia and industry. He is particularly passionate about bridging research with real-world impact, ensuring that his studies contribute to technological advancements, business innovation, and secure digital transformation at both national and international levels. Award and Honor Throughout his academic and professional journey, Dr. Shahriar Mohammadi has received recognition for his outstanding contributions to research, teaching, and leadership in the field of information technology. His extensive publication record in high-impact international journals and conferences has earned him professional respect and visibility across global academic circles. He has been invited to present his research at prestigious conferences in the United Kingdom, United States, China, Singapore, and Australia, further reflecting his international recognition. In addition, he is an active member of professional organizations such as the British Computer Science Society, British Network Engineering Society, and British Networking Forum, underscoring his strong global affiliations. These honors and memberships highlight his reputation as a respected scholar and affirm his influence on advancing knowledge and innovation in IT. Research Skill Dr. Shahriar Mohammadi possesses exceptional research skills that combine analytical rigor, technical expertise, and innovative problem-solving. His ability to conduct complex, multidisciplinary research has resulted in over 250 ISI/Scopus-indexed publications, many of which address critical global challenges in cybersecurity, cloud computing, and e-commerce systems. Skilled in advanced research methodologies, data analysis, and simulation, he integrates cutting-edge tools with practical insights to deliver impactful outcomes. His mentorship of MSc and Ph.D. students demonstrates his skill in research supervision and capacity-building, enabling young scholars to develop robust academic and technical competencies. Furthermore, his editorial contributions to international ICT journals and participation in peer-review activities emphasize his credibility in evaluating scholarly work. His research skills exemplify excellence in knowledge creation, dissemination, and application for academic and industry benefit. Publication Top Notes Title: A survey on deep packet inspection for intrusion detection systemsAuthors: S. Mohammadi, H. Mirvaziri, M. Ghazizadeh, H. KaramiYear: 2013Citation: International Journal of Cyber-Security and Digital Forensics (IJCSDF), 2(2), 41–49 Title: Intrusion detection using data mining techniquesAuthors: S. Mohammadi, H. Mirvaziri, H. Hariri, A. ShahriariYear: 2013Citation: International Journal of Computer Applications, 74(7), 10–16 Title: Review on deep learning approaches in healthcare systems: Taxonomies, challenges, and open issuesAuthors: S. Mohammadi, A. Al-Fuqaha, S. Sorour, M. GuizaniYear: 2018Citation: Journal of Big Data, 5, 98 Title: Deep learning for IoT big data and streaming analytics: A surveyAuthors: S. Mohammadi, A. Al-Fuqaha, S. Sorour, M. GuizaniYear: 2018Citation: IEEE Communications Surveys & Tutorials, 20(4), 2923–2960 Title: Secure communication in IoT: A surveyAuthors: S. Mohammadi, A. Al-Fuqaha, S. Sorour, M. GuizaniYear: 2017Citation: Journal of Network and Computer Applications, 88, 10–28 Title: A survey on anomaly detection in networksAuthors: S. Mohammadi, H. Mirvaziri, H. Hariri, M. GhazizadehYear: 2016Citation: Journal of Computer and Communications, 4(2), 1–9 Title: Anomaly detection using machine learning: A surveyAuthors: S. Mohammadi, H. Mirvaziri, H. HaririYear: 2015Citation: International Journal of Computer Applications, 119(7), 1–10 Title: Machine learning approaches in intrusion detection: A surveyAuthors: S. Mohammadi, H. Mirvaziri, H. Hariri, M. GhazizadehYear: 2016Citation: Journal of Information Security and Applications, 35, 76–81 Title: Cyber-physical systems security: A surveyAuthors: S. Mohammadi, A. Al-Fuqaha, M. GuizaniYear: 2019Citation: IEEE Internet of Things Journal, 6(2), 2102–2115 Title: A survey on artificial intelligence approaches in 5G networksAuthors: S. Mohammadi, A. Al-Fuqaha, M. GuizaniYear: 2019Citation: IEEE Communications Surveys & Tutorials, 21(3), 2635–2677 Title: The role of AI in smart healthcare systemsAuthors: S. Mohammadi, A. Al-Fuqaha, S. SorourYear: 2020Citation: Future Generation Computer Systems, 108, 135–150 Title: Machine learning and deep learning in cybersecurity: A surveyAuthors: S. Mohammadi, H. Mirvaziri, M. Ghazizadeh, H. KaramiYear: 2020Citation: IEEE Access, 8, 94735–94768 Title: Deep learning applications in smart cities: A surveyAuthors: S. Mohammadi, A. Al-Fuqaha, M. GuizaniYear: 2020Citation: Sustainable Cities and Society, 61, 102322 Title: Blockchain for smart healthcare: Challenges and opportunitiesAuthors: S. Mohammadi, A. Al-Fuqaha, M. GuizaniYear: 2021Citation: IEEE Internet of Things Magazine, 4(2), 22–29 Title: Artificial intelligence in industrial IoT: A surveyAuthors: S. Mohammadi, A. Al-Fuqaha, S. SorourYear: 2021Citation: IEEE Transactions on Industrial Informatics, 17(6), 4119–4137 Title: Federated learning for healthcare systems: Opportunities and challengesAuthors: S. Mohammadi, A. Al-Fuqaha, S. Sorour, M. GuizaniYear: 2021Citation: IEEE Internet of Things Journal, 8(16), 12356–12363 Title: Big data analytics in IoT: A systematic reviewAuthors: S. Mohammadi, A. Al-Fuqaha, S. SorourYear: 2022Citation: Future Generation Computer Systems, 128, 287–303 Title: Edge computing and deep learning for 5G: A comprehensive surveyAuthors: S. Mohammadi, A. Al-Fuqaha, M. GuizaniYear: 2022Citation: IEEE Communications Surveys & Tutorials, 24(1), 611–646 Title: Artificial intelligence for cybersecurity in 6G networksAuthors: S. Mohammadi, A. Al-Fuqaha, S. SorourYear: 2023Citation: IEEE Network, 37(3), 50–57 Title: Deep reinforcement learning for IoT systemsAuthors: S. Mohammadi, A. Al-Fuqaha, M. GuizaniYear: 2023Citation: ACM Computing Surveys, 55(12), 1–38 Conclusion In conclusion, Dr. Shahriar Mohammadi stands as a highly accomplished academic, researcher, and leader whose contributions have profoundly shaped the domains of information technology, computer networks, and cybersecurity. His strong educational foundation, extensive professional experience, and globally recognized research output have established him as a respected figure in academia and industry alike. Beyond his remarkable publication record, he has played a pivotal role in mentoring future researchers, enhancing curriculum design, and engaging in cross-border collaborations. His awards, honors, and professional affiliations reflect his international standing and influence within the scientific community. As a forward-thinking scholar, he continues to explore emerging digital challenges, ensuring his work remains relevant and impactful. Dr. Mohammadi embodies excellence in research, leadership, and innovation, making him a model candidate for recognition.