Mohamad Abu Seman | AI and Robotic System | Best Researcher Award

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Dr. Mohamad Abu Seman | AI and Robotic System | Best Researcher Award

Senior Lecturer from University Sains Malaysia | Malaysia 

Dr. Mohamad Tarmizi Abu Seman is a Senior Lecturer at Universiti Sains Malaysia (USM), widely recognized for his pioneering work in mechanical engineering and intelligent systems integration. With an academic and research career rooted in innovation and community impact, Dr. Abu Seman has consistently contributed to the advancement of engineering solutions that intersect with artificial intelligence, smart healthcare systems, and sustainable technologies. His extensive research has produced practical tools and systems, from smart rehabilitation gloves and diabetic insoles to IoT-based agriculture and intelligent parking solutions. He has been instrumental in supervising numerous undergraduate and postgraduate students, leading them in cutting-edge research that addresses real-world challenges. Dr. Abu Seman has received multiple national and international accolades for his innovations and continues to serve on key research projects funded by Malaysian research councils and ministries. His involvement in applied engineering and technology-based community solutions demonstrates his commitment to both academic excellence and social betterment. As a member of professional networks like IEEE, he maintains strong academic connections and continually expands his interdisciplinary scope. His contributions place him at the forefront of Malaysian engineering innovation, with increasing global visibility in science, health, and technology domains.

Professional Profile

Scopus Profile | ORCID Profile | Google Scholar

Education

Dr. Mohamad Abu Seman holds a Doctor of Philosophy (Ph.D.) in Mechanical Engineering, marking the culmination of years of rigorous academic training and specialized research. His academic foundation is rooted in applied mechanical engineering, where he focused on areas such as Computational Fluid Dynamics (CFD), Finite Element Analysis (FEA), and mechanical system optimization. His doctoral research explored aerodynamic performances, smart sensor systems, and heat energy applications, combining computational and experimental methodologies to advance engineering practices. Throughout his academic journey, Dr. Abu Seman developed expertise in simulation software such as ANSYS and MATLAB, allowing him to translate complex engineering theories into practical, problem-solving innovations. His academic credentials are complemented by his continued learning through research-based teaching and national innovation competitions. His education laid a strong foundation for his future research endeavors in smart embedded systems, energy-efficient devices, and AI-integrated mechanical systems. The application of his doctoral studies is evident in the range of projects he has undertaken, including robotics, sensor technologies, and sustainable engineering solutions. Dr. Abu Seman’s academic journey has not only shaped his technical competencies but also positioned him as a thought leader in intelligent mechanical systems both in Malaysia and the wider ASEAN research community.

Experience

As a Senior Lecturer at Universiti Sains Malaysia (USM), Dr. Mohamad Abu Seman has demonstrated multifaceted professional excellence in teaching, research, and applied innovation. He has led and contributed to a wide range of university-community partnership projects, focusing on smart agriculture, robotic rehabilitation, and inclusive design for differently-abled individuals. His current and past grant-funded research initiatives include the development of intelligent glove systems, IoT-powered irrigation, and robotic mechanisms, amounting to over RM 700,000 in research funding. Dr. Abu Seman has played an integral role in supervising undergraduate and postgraduate students, many of whom have produced award-winning capstone projects and published academic papers under his guidance. His engineering expertise spans smart mechanical systems, AI-driven embedded applications, and biomedical design. Additionally, he has represented his institution at national and international engineering competitions and innovation exhibitions, further solidifying his professional credibility. Dr. Abu Seman’s experience is deeply rooted in both academic mentorship and real-world problem-solving, often bridging the gap between engineering theory and tangible community impact. He continues to contribute as a principal investigator in active research projects, and his career trajectory exemplifies sustained leadership in research, innovation, and collaborative knowledge exchange.

Research Interests

Dr. Abu Seman’s research interests lie at the intersection of mechanical engineering, smart systems, and artificial intelligence, with a focus on real-world applications in healthcare, agriculture, and industrial automation. He is particularly passionate about the design and simulation of intelligent assistive devices, such as smart diabetic insoles and rehabilitation gloves, which utilize embedded systems, IoT, and sensor-based feedback for enhanced performance and usability. Another major area of his research focuses on energy-efficient systems and robotic mechanisms that aid in automation for improved human well-being and sustainability. Projects like the development of a universal robotic gripper, IoT-enabled irrigation systems, and embedded traffic systems showcase his interdisciplinary and application-driven approach. He has also delved into predictive analytics using AI for transportation systems, biomedical applications, and real-time industrial monitoring. These interests are driven by a commitment to integrating AI and mechanical structures to create smarter, safer, and more adaptive engineering systems. Dr. Abu Seman also engages in bio-inspired system design and fuzzy logic control applications for automation and autonomous vehicles. His ongoing research continuously aligns with evolving industry needs and national development priorities, making him a prominent contributor to Malaysia’s vision for innovation-led engineering development.

Research Skills

Dr. Abu Seman possesses a robust arsenal of technical skills that enable him to deliver impactful and solution-oriented research in mechanical engineering. He is proficient in Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA), leveraging software like ANSYS, MATLAB, and SolidWorks for simulation and modeling purposes. His work incorporates embedded technology, robotic automation, smart sensors, and artificial intelligence frameworks, showcasing his multi-disciplinary fluency. Dr. Abu Seman has also demonstrated competence in design thinking and prototyping, guiding student-led innovations from ideation to final implementation. He is highly skilled in using Raspberry Pi and Arduino systems for building smart devices in healthcare and IoT agriculture. His experience in leading grant-funded research has sharpened his skills in project formulation, technical reporting, and data visualization. With knowledge of deep learning, fuzzy control systems, and adaptive algorithms, he applies computational intelligence to mechanical systems with practical relevance. His skill set also includes academic writing, having published in high-impact Scopus and WoS-indexed journals. Moreover, his guidance of undergraduate and postgraduate students reveals his mentoring capacity and commitment to skill transfer. Dr. Abu Seman continues to refine his skills to align with emerging trends in smart engineering, robotics, and AI integration.

Awards and Honors

Dr. Mohamad Abu Seman has been the recipient of numerous national and international awards that recognize both his innovation and social impact. He earned the Silver and Special Awards at the Asia International Innovation Exhibition (AIINex) for his automated door system developed in response to COVID-19 SOP compliance. His leadership in student innovation led to his team winning Champion in the “OKU Smart Parking Lot System” project during the Engineering Innovative Design Competition (ENGINNOVATE) at USM. He was also awarded The People’s Choice Award at the Malaysian Innovative Healthcare Symposium (MIHS) for the Smart Diabetic Insole project. These recognitions reflect his commitment to technological inclusivity, especially projects that support marginalized communities like the elderly and the disabled. Dr. Abu Seman’s research has also been showcased at international IEEE conferences and Springer’s Lecture Notes series, underlining his global academic reach. His recognition goes beyond technical merit; it also underscores his ability to align innovation with public health and community development goals. These awards have positioned him as a leading innovator in Malaysia’s academic engineering landscape, reaffirming his capability to translate research into socially responsible engineering solutions.

Publication Top Notes

  • Smart water-quality monitoring system based on enabled real-time internet of things – 2020, 57 citations

  • Monitoring temperature, humidity and controlling system in industrial fixed room storage based on IoT – 2020, 19 citations

  • Embedded operating system and industrial applications: a review – 2021, 13 citations

  • Internet of things based automated agriculture system for irrigating soil – 2022, 11 citations

  • Application of deep learning in iron ore sintering process: a review – 2024, 7 citations

  • Intelligent pressure and temperature sensor algorithm for diabetic patient monitoring: An IoT approach – 2024, 7 citations

  • A MAC protocol for energy efficient wireless communication leveraging wake-up estimations on sender data – 2020, 7 citations

Conclusion

Dr. Mohamad Tarmizi Abu Seman exemplifies the qualities of an outstanding researcher, educator, and innovator. His multidisciplinary contributions in mechanical engineering, particularly in the integration of AI, embedded systems, and community-focused technologies, have made a tangible impact on both the academic community and Malaysian society. With a proven track record of student mentorship, successful research funding, impactful publications, and award-winning innovations, Dr. Abu Seman continues to raise the standards of engineering education and research excellence. His projects not only advance scientific knowledge but also directly contribute to societal welfare by addressing issues in healthcare accessibility, smart infrastructure, and inclusive technology. As he expands his research through international collaborations and aims for higher-tier publications, his potential as a future leader in smart engineering systems and AI-driven innovation remains strong. His work stands as a model of applied science for societal good, and his nomination is a testament to his dedication to transforming challenges into impactful solutions.

Serhat Kilicarslan | Neural Networks Award | Best Researcher Award

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Assoc Prof Dr. Serhat Kilicarslan | Neural Networks Award | Best Researcher Award

Software Engineer at Bandırma Onyedi Eylül University Faculty of Engineering and Natural Sciences, Turkey

Assoc. Prof. Dr. Serhat Kılıçarslan is a highly skilled and accomplished professional in the field of computer science and engineering. With a strong background in research, teaching, and practical applications, Dr. Kılıçarslan has made significant contributions to the field. His research expertise includes computer networks, Wireless Sensor Networks (WSNs), Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning (ML). He is proficient in programming languages such as C, C++, Java, Python, and MATLAB, and has a deep understanding of networking concepts, protocols, and technologies. Dr. Kılıçarslan has published extensively in reputable journals and conferences, showcasing his analytical and problem-solving abilities. Overall, Dr. Kılıçarslan’s expertise and skills have positioned him as a valuable asset in advancing the field of computer science and engineering.

Professional Profiles:

Education:

Assoc. Prof. Dr. Serhat KILIÇARSLAN has a strong academic background in computer engineering, mechatronics engineering, and technical education. He completed his Bachelor’s degree in Computer Engineering at Kocaeli University in June 2017. Following this, he pursued a Master’s degree in Mechatronics Engineering at Gazi Osmanpaşa University, graduating in September 2014. For his Master’s thesis, he developed programming software for microcontroller-based PLCs under the guidance of Assoc. Prof. Dr. Gökhan GELEN. Dr. KILIÇARSLAN continued his academic journey by completing his Ph.D. in Computer Engineering at Erciyes University in September 2021. His doctoral thesis focused on the development of non-linear activation functions for deep learning methods, under the supervision of Assoc. Prof. Dr. Mete ÇELİK.

Experience:

Assoc. Prof. Dr. Serhat KILIÇARSLAN currently serves as a faculty member at Bandırma Onyedi Eylül University, Faculty of Engineering and Natural Sciences, Department of Software Engineering. He joined the university in 2022, where he contributes to the field of software engineering through research, teaching, and academic leadership. Before joining Bandırma Onyedi Eylül University, Dr. KILIÇARSLAN served as a lecturer at Gaziosmanpaşa University. He was involved in the Department of Informatics, where he also held the position of Department Chair. Additionally, he served as a lecturer at Gaziosmanpaşa University, Pazar Vocational School, Department of Computer Technologies, specializing in Computer Programming. Dr. KILIÇARSLAN’s experience in these roles has equipped him with valuable insights and expertise in the field of software engineering and computer programming.

Research Interest:

Assoc. Prof. Dr. Serhat Kılıçarslan has a diverse research background focusing on various aspects of computer science and engineering. His research interests span several key areas, including Wireless Sensor Networks (WSNs), Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML), Software-Defined Networking (SDN), Cloud Computing, Cyber-Physical Systems (CPS), Security, Privacy, and Big Data Analytics. In the realm of WSNs, Dr. Kılıçarslan explores the design, implementation, and optimization of WSNs for applications such as environmental monitoring, healthcare, and industrial automation. In the field of IoT, he delves into the architectures, protocols, and security mechanisms of IoT systems, aiming to enhance their efficiency, reliability, and security.

Skills:

Assoc. Prof. Dr. Serhat Kılıçarslan possesses a diverse set of skills in the field of computer science and engineering, honed through his research, teaching, and professional experiences. Some of his key skills include research skills, where he has a strong track record of publication in reputable journals and conferences. He is adept at formulating research questions, designing experiments, analyzing data, and drawing meaningful conclusions. Dr. Kılıçarslan is also proficient in programming languages such as C, C++, Java, Python, and MATLAB, which he applies in developing software solutions for various research projects. With a focus on computer networks, Dr. Kılıçarslan has expertise in networking concepts, protocols, and technologies, including TCP/IP, routing, switching, and network security. He is experienced in designing, implementing, and optimizing Wireless Sensor Networks (WSNs) and IoT systems for diverse applications, leveraging his knowledge of sensor technologies, communication protocols, and data processing techniques. Dr. Kılıçarslan applies Artificial Intelligence (AI) and Machine Learning (ML) techniques, such as neural networks, deep learning, and reinforcement learning, to solve complex problems in computer networks and related areas. He also has expertise in Software-Defined Networking (SDN), cloud computing, Cyber-Physical Systems (CPS), security, privacy, and Big Data Analytics. Overall, Dr. Kılıçarslan’s skills are integral to his contributions in advancing the field of computer science and engineering, with a focus on enhancing the efficiency, reliability, and security of modern computing systems and networks.

Publications:
  1. Classification and diagnosis of cervical cancer with stacked autoencoder and softmax classification
    • Authors: K Adem, S Kılıçarslan, O Cömert
    • Year: 2019
    • Citations: 162
  2. Diagnosis and Classification of Cancer Using Hybrid Model Based on ReliefF and Convolutional Neural Network
    • Authors: S Kiliçarslan, K Adem, M Celik
    • Year: 2020
    • Citations: 82
  3. Hybrid models based on genetic algorithm and deep learning algorithms for nutritional Anemia disease classification
    • Authors: S Kiliçarslan, M Celik, S Sahin
    • Year: 2021
    • Citations: 67
  4. RSigELU: A nonlinear activation function for deep neural networks
    • Authors: S Kiliçarslan, M Celik
    • Year: 2021
    • Citations: 63
  5. DIVORCE PREDICTION USING CORRELATION BASED FEATURE SELECTION AND ARTIFICIAL NEURAL NETWORKS
    • Authors: MK Yöntem, K Adem, T İlhan, S Kılıçarslan
    • Year: 2019
    • Citations: 57
  6. An overview of the activation functions used in deep learning algorithms
    • Authors: S KILIÇARSLAN, A Kemal, M Çelik
    • Year: 2021
    • Citations: 24
  7. Detection and Classification of Pneumonia Using Novel Superior Exponential (SupEx) Activation Function in Convolutional Neural Networks
    • Authors: S Kiliçarslan, Cİ Közkurt, S Baş, A Elen
    • Year: 2023
    • Citations: 21
  8. Performance analysis of optimization algorithms on stacked autoencoder
    • Authors: A Kemal, S Kilicarslan
    • Year: 2019
    • Citations: 19
  9. COVID-19 Diagnosis Prediction in Emergency Care Patients using Convolutional Neural Network
    • Authors: A Kemal, S KILIÇARSLAN
    • Year: 2021
    • Citations: 18
  10. Deep learning-based approaches for robust classification of cervical cancer
    • Authors: I Pacal, S Kılıcarslan
    • Year: 2023
    • Citations: 13

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