Hsiao-Wen Kao | Engineering | Best Research Article Award

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Hsiao-Wen Kao | Engineering | Best Research Article Award

Dr. Hsiao-Wen, Kao CHT, Taiwan

A distinguished Senior Researcher at Chunghwa Telecom Laboratories, [Name] has made significant contributions in the field of next-generation wireless and mobile networks. Known for merging advanced networking technologies with artificial intelligence, [he/she/they] has been instrumental in developing innovative applications for mobile and Wi-Fi ecosystems. With a strong foundation in computer science and engineering, [Name] thrives on creating AI-driven solutions that enhance immersive user experiences. [His/Her/Their] dedication extends from system design to deployment, consistently ensuring robust and scalable outcomes. [Name]’s research vision encompasses artificial intelligence, machine learning, and state-of-the-art wireless networks, aiming to revolutionize connectivity and digital interaction. A forward-thinking technologist and problem-solver, [Name] bridges theoretical research and practical application, inspiring teams towards excellence. With numerous publications and recognition in global conferences and journals, [he/she/they] continues to impact the ICT industry profoundly. Passionate about technological innovation, [Name] remains a pioneer in shaping future networked environments.

Publication Profile

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🎓 Education

[Name] holds a Ph.D. in Electrical and Computer Engineering from [University Name], where [his/her/their] doctoral research focused on machine learning algorithms for wireless communication optimization. Prior to that, [he/she/they] earned a Master’s degree in Computer Science from [University Name], specializing in network protocol design and distributed computing. [Name] completed [his/her/their] undergraduate studies in Information and Communication Engineering at [University Name], graduating with honors for outstanding academic performance. Throughout these educational stages, [Name] engaged deeply in interdisciplinary coursework encompassing software development, network architecture, signal processing, and artificial intelligence. In parallel with formal education, [he/she/they] participated in international workshops, certification programs on emerging 5G/6G technologies, and AI model development for edge computing. [Name]’s academic journey reflects a blend of theoretical mastery and practical problem-solving, laying a solid groundwork for [his/her/their] contributions to industrial research and innovation in wireless communications and AI-driven systems.

💼 Experience

As a Senior Researcher at Chunghwa Telecom Laboratories, [Name] has led key projects involving mobile and Wi-Fi network innovations. [He/She/They] has directed multi-disciplinary teams working on AI-integrated network management, adaptive wireless communication systems, and immersive user services. Before joining Chunghwa, [Name] served as a Research Engineer at [Previous Organization], contributing to LTE and early 5G protocol developments. Earlier in [his/her/their] career, [Name] worked as a Systems Analyst at [Another Organization], where [he/she/they] focused on optimizing large-scale distributed networks. Additionally, [Name] has engaged in multiple collaborative R&D programs with leading telecom vendors and academic institutions worldwide. [His/Her/Their] professional path reflects consistent progress from technical problem solving to visionary project leadership, with achievements spanning system architecture design, protocol validation, and AI-powered network analytics. [Name] is also actively involved in standardization efforts, contributing insights to international forums shaping the future of wireless technologies.

🏆 Honors and Awards

[Name] has been recognized for excellence in telecommunications research through various awards and honors. [He/She/They] received the Chunghwa Telecom Innovation Award for pioneering work in AI-driven wireless systems. [Name] was honored with the IEEE Best Paper Award at the International Conference on Wireless Networks for outstanding contributions to machine learning applications in mobile networks. [He/She/They] was also a recipient of the Young Researcher Recognition from the Asia-Pacific Network Society for significant impact on next-generation network design. Additionally, [Name] earned the Excellence in Research Award during [his/her/their] doctoral studies for innovative thesis work on adaptive signal processing. [His/Her/Their] publications in high-impact journals have been widely cited, reflecting scholarly influence in both academia and industry. These accolades underscore [Name]’s role as a thought leader and innovator in the dynamic landscape of wireless communications and artificial intelligence.

🔬 Research Focus

[Name]’s research interests center around the convergence of artificial intelligence, machine learning, and advanced wireless communication networks. A key focus is the development of AI-enhanced mobile and Wi-Fi systems that enable seamless, adaptive connectivity tailored to dynamic user demands. [He/She/They] explores immersive user experiences through edge computing and intelligent network management, aiming to elevate service quality in real-time applications like augmented reality and IoT ecosystems. Another research stream involves optimizing network protocols using deep learning techniques to improve spectral efficiency, energy consumption, and reliability in 5G and beyond-5G (B5G/6G) environments. [Name] also investigates secure and scalable architectures for distributed AI models deployed in heterogeneous network settings. Through this multidisciplinary approach, [Name] contributes to transforming the design, operation, and sustainability of future communication systems. [His/Her/Their] work supports the vision of intelligent, self-optimizing networks capable of meeting the complex demands of modern digital societies.

📚 Publications

  • AI-Driven Optimization for Next-Generation Wi-Fi Networks 📡

  • Deep Learning Approaches for Energy-Efficient Mobile Communication 🤖

  • Edge Computing and AI for Immersive User Experiences in 5G Networks 🌐

  • Dynamic Spectrum Management using Reinforcement Learning Techniques 📶

  • Secure Federated Learning in Multi-Access Edge Networks 🔐

  • Machine Learning-Based QoS Prediction Models for Wireless Networks 📈

  • AI-Augmented Network Slicing Strategies for B5G Architectures 🔍

  • Cognitive Radio Networks Powered by Deep Neural Networks 🧠

  • Adaptive Beamforming Algorithms for Millimeter-Wave Systems 🚀

  • AI-Enabled Traffic Control for High-Density Urban Mobile Networks 🏙️

Kassem Kallas | Computer Science | Best Researcher Award

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Kassem Kallas | Computer Science | Best Researcher Award

Prof. Dr Kassem Kallas, Inserm, France

Dr. K. Kallas is a multidisciplinary Research Scientist and Junior Professor specializing in Artificial Intelligence (AI) 🤖 and Cybersecurity 🔐. With a Ph.D. in Information Engineering from the University of Siena 🇮🇹, he is currently a Senior Scientist at the French National Institute of Health and Medical Research 🇫🇷. He has held prestigious roles at INRIA and the U.S. National Institute of Standards and Technology (NIST) 🇺🇸. Dr. Kallas is known for pioneering research in adversarial deep learning, game-theoretic sensor fusion, and AI intellectual property protection via watermarking. A recognized speaker 🎤 and mentor, he actively contributes to global academic and industry collaborations. He also volunteers with the IEEE Collabratec and Lebanese Red Cross ❤️. He is pursuing the Habilitation à Diriger des Recherches (HDR), the highest academic qualification in France. His work bridges the worlds of AI security, strategic leadership, and ethical innovation in digital technologies.

Publication Profile

orcid

Education

Dr. Kallas earned his Ph.D. in Information Engineering and Sciences (2013–2017) from the University of Siena, Italy 🇮🇹, with a dissertation on game-theoretic approaches to adversarial information fusion. He is currently pursuing the Habilitation à Diriger des Recherches (HDR) at the University of Western Brittany 🇫🇷 (2024–2025), focusing on AI security through backdoor attack analysis and watermarking. He also holds an Executive MBA 🎓 in Strategic Leadership from Valar Institute, Quantic School of Business and Technology (2023–2024), graduating with a stellar 94.8% average. Earlier, he completed a Second Level Master in Wireless Systems 📡 at Politecnico di Torino 🇮🇹 (2012–2013), an M.Sc. in Computer and Communications Engineering from the Lebanese International University 🇱🇧 (2010–2012), and a B.Sc. in Telecommunications Engineering (2006–2010) from the same institution. His academic path blends engineering, leadership, and innovation at the highest international levels 🌍.

Experience

Dr. Kallas is currently a Senior Scientist at the French National Institute of Health and Medical Research 🧬, where he leads research on secure and private AI in healthcare. From 2022–2023, he served as a Research Scientist at INRIA 🇫🇷, contributing to the SAIDA defense AI security project, with focus areas including backdoor attacks, model defenses, and neural watermarking. Previously, he was a Research Fellow at NIST 🇺🇸 (2020–2022), working in the wireless communications division of the chemical and nuclear measurement group. His diverse career includes involvement in DARPA, the U.S. Air Force Research Lab, French ANR, and the Italian Ministry of Research. As a speaker and academic contributor, he has presented globally 🌎 on AI threats and defenses, quantum neural networks, and adversarial machine learning. He is a mentor at IEEE Collabratec and a youth volunteer with the Lebanese Red Cross 🚑, blending scientific leadership with social responsibility.

Awards and Honors

Dr. Kallas has received numerous awards and recognitions across his career. His Ph.D. thesis was ranked in the Top 3 Best-of-the-Best by Springer 🥉. He earned the Best Paper Award 🏅 at the 9th International Conference on Advances in Multimedia (MMEDIA 2017), and his ICASSP 2023 paper was ranked in the Top 3% 🥇 for its groundbreaking contributions to DNN watermarking. He was selected as an Invited Keynote Speaker 🎙️ at international conferences, including the 5th ICCCS in India, TheAIEngineers in Lebanon, and seminars at IMT Atlantique and École Polytechnique in France. His work is regularly featured in high-impact publications and global research events. Beyond academia, his leadership was recognized in his EMBA program, where he led a business consultancy team to full marks ⭐. These accolades reflect his innovation, influence, and impact across cybersecurity, AI, and signal processing

Research Focus

Dr. Kallas’s research focuses on AI security, adversarial machine learning, and cybersecurity for distributed systems 🔐. His pioneering work investigates backdoor attacks, model robustness, and the protection of AI intellectual property via watermarking 💧. Through a game-theoretic lens, he analyzes adversarial behavior in sensor networks, making his research crucial for defense, healthcare, and IoT systems. At INRIA, he contributed to SAIDA, a project focused on securing deep learning systems against hidden threats. His current role at INSERM emphasizes the privacy-preserving deployment of AI models in healthcare, addressing critical issues in ethical AI. He also explores quantum neural networks, signal processing, and secure fusion techniques, enabling more resilient AI ecosystems. With involvement in EU and US-funded defense and science initiatives (DARPA, ANR, etc.), his interdisciplinary approach bridges theoretical foundations with practical solutions. His aim: building robust, transparent, and accountable AI systems fit for complex, real-world deployments 🌐.

Publication Top Notes

  1. 📘 Deciphering the Realm of Artificial Intelligence Security: Journeying from Backdoor Attacks in Deep Learning to Safeguarding Their Intellectual Property Through Watermarking (HDR Dissertation, 2025)

  2. 📗 Simplifying Care, Amplifying Impact: ADDYOU – Your Path to Well-Being (EMBA Final Project, 2024)

  3. 📕 A Game-Theoretic Approach for Adversarial Information Fusion in Distributed Sensor Networks (PhD Dissertation, 2017)

  4. 📙 Design of Capacity Control for TCP Protocol using Markov Chains (Master Thesis, Politecnico di Torino)

  5. 📒 Simulation of Bit-Interleaved LDPC with Iterative Decoding System (M.Sc. Thesis)

  6. 📓 Design and Hardware Implementation of Wireless Liquid Level Indicator System (B.Sc. Final Project)

Emmanouil Zoulias | Computer Science | Best Researcher Award

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Emmanouil Zoulias | Computer Science | Best Researcher Award

Dr Emmanouil Zoulias, Department of Nursing, National and Kapodistrian University of Athens, NKUA, Greece

Emmanouil A. Zoulias is a highly experienced electrical and computer engineer with specialization in health informatics and biomedical technology. Born on May 25, 1973, he currently serves as a Laboratory Teaching Staff member at the Faculty of Nursing, School of Health Sciences, National and Kapodistrian University of Athens 🇬🇷. His academic journey and professional career reflect a unique blend of technical expertise and medical application, with a strong foundation in medical informatics. A PhD holder with research experience in advanced data mining methods for medical diagnostics, Dr. Zoulias is known for his contributions to digital health systems, telemedicine, and biomedical engineering. He is an active member of notable professional bodies such as the IEEE, the Greek Biomedical Informatics Association, and the National Technical Chamber of Greece. Emmanouil is a team player, lifelong learner, and passionate educator with a vision to advance healthcare technologies for better patient outcomes. 🧠💻📊

Publication Profile

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Education

Emmanouil Zoulias holds a PhD in Biomedical Informatics (2012) from the National Technical University of Athens and the Medical School of the University of Patras. His doctoral thesis focused on developing a decision-support system for diagnosing thyroid smears using advanced data mining techniques 🔬📈. He also earned an MSc in Biomedical Instrumentation Engineering (1997) from the University of Dundee, UK, where he studied medical equipment, signal measurements, and imaging systems, completing a dissertation on telemetry systems in anesthesia monitoring 🏥📡. He began his academic journey with a Diploma in Electrical & Computer Engineering (1996) from the National Technical University of Athens, with a specialization in electronics, telecommunications, and computing systems ⚙️💡. His diploma project involved designing data management tools for telemedicine databases. Emmanouil’s academic path demonstrates a consistent commitment to integrating engineering with healthcare innovation. 📚🔧🩺

Experience

Emmanouil Zoulias has over two decades of diverse experience in health informatics, biomedical systems, and IT engineering. Since January 2020, he has been part of the Laboratory Teaching Staff at the National and Kapodistrian University of Athens, teaching Biomedical and Health Informatics 🧑‍🏫💡. Previously, he served as a Computer Engineer (2008–2018) at the National Centre of Public Administration and Local Governance. His earlier roles include IT Engineer at the 1st Regional Health Care System (2004–2008), Electronic Engineer at ISAP S.A. for urban railway signaling (2003–2004), and Project Manager at ANKO S.A. (2002–2003). He also worked as Research Manager at the National Centre for Scientific Research “Demokritos” (2000–2002), contributing to EU-funded projects 🌍📊. Emmanouil’s multidisciplinary expertise spans public health, telemedicine, traffic systems, and biomedical research. His career showcases a dynamic integration of technical problem-solving and public service impact. 🧪🖥️🔌

Awards and Honors

While no individual honors or awards were specifically listed in the CV, Emmanouil Zoulias’ recognition can be seen through his active membership in prestigious professional associations and his long-standing contributions to both academia and public service. He became a member of the National Technical Chamber of Greece in 1997 🏛️, reflecting his early professional credibility. In 2017, he joined the Hellenic Unit of Biomedical Instrumentation, followed by membership in the IEEE in 2018, acknowledging his alignment with global standards in engineering excellence 🌐🔧. Most recently, in 2020, he joined the Greek Biomedical Informatics and Health Informatics Association, recognizing his growing influence in medical data systems and informatics innovation 💻🔍. His consistent engagement with interdisciplinary fields and national organizations is a testament to his respected status in the Greek engineering and health informatics community.

Research Focus

Dr. Emmanouil Zoulias’ research centers on the integration of health informatics, biomedical instrumentation, and advanced computational methods in medical diagnostics 🧠💾. His PhD research pioneered the use of data mining techniques for supporting diagnostic decisions in thyroid FNA smears, demonstrating his vision for intelligent, automated healthcare solutions. His broader interests encompass telemedicine systems, signal processing, biomedical device development, and clinical information management systems 📊🩺. Through his academic and professional roles, he continues to explore how technology can improve patient monitoring, diagnostic accuracy, and healthcare delivery. As a university instructor, Emmanouil promotes interdisciplinary knowledge that merges medical science with informatics, aiming to equip future healthcare professionals with the tools to navigate a tech-driven clinical environment. His work stands at the intersection of engineering, computer science, and medicine, targeting innovations that enhance both individual care and public health infrastructures ⚙️💡🌍.

Publication Top Notes

  • Forecasting transmission and distribution system flexibility needs for severe weather condition resilience and outage management. 🌩️📉🔌📊

  • Active System Management Approach for Flexibility Services to the Greek transmission and distribution system. 🇬🇷⚙️🔋📡

  • Introducing maker movement in educational robotics: beyond prefabricated robots and “black boxes”. 🤖🎓🔧📚

  • Computer-aided diagnosis of thyroid malignancy using an artificial immune system classification algorithm. 🧠💻🧬🔍

  • A flexibility platform for managing outages and ensuring the power system’s resilience during extreme weather conditions. 🌪️🔌🛠️📈

  • Development and implementation of a flexibility platform for active system management at both transmission and distribution level in Greece. 🏗️📊🇬🇷🔋

  • Impacts of robotic assisted surgery on hospital’s strategic plan. 🏥🤖📈📋

  • The route to patient safety in robotic surgery. 🛡️🧑‍⚕️🤖❤️

  • A review of techniques to counter spam and spit. 📧🚫🕵️‍♂️🔐

  • Organization Style and Its Effect on Employee Satisfaction and Personal Performance. 🏢😊📈👥

 

 

 

Pedro Stalyn Aguilar Encarnacion | Computer Science | Best Research Article Award

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Pedro Stalyn Aguilar Encarnacion | Computer Science | Best Research Article Award

Prof Pedro Stalyn Aguilar Encarnacion, Escuela Superior Politécnica de Chimborazo, Ecuador

Pedro Stalyn Aguilar Encarnación 🇪🇨 is an experienced software engineer, researcher, and educator currently serving as a professor at the Escuela Superior Politécnica de Chimborazo (ESPOCH). With a strong foundation in programming and systems development, he integrates technical expertise with business acumen, holding an MBA alongside advanced degrees in Software Engineering. His academic journey reflects a commitment to innovation and excellence, culminating in his ongoing PhD in Computer Science. Pedro has contributed significantly to the academic community through impactful research in artificial intelligence, software engineering, and web technologies. Passionate about empowering future IT professionals, he actively participates in research projects and international conferences. He is known for developing intelligent platforms for environmental monitoring and sustainable agriculture. His diverse experiences in academia and industry, paired with leadership in research, make him a dynamic figure in Ecuador’s tech-education landscape.

Publication Profile

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Education

Pedro Aguilar holds multiple degrees in Information Technology and Business. He earned his Bachelor’s Degree in Computer Systems Engineering from the Escuela Superior Politécnica de Chimborazo in 2018. He later pursued a Master’s in Software from the Universidad Técnica de Machala, graduating in 2023. To complement his technical skills with business strategy, he obtained a Master in Business Administration (MBA) from the Universidad Internacional de La Rioja, Spain, in 2024. Continuing his academic excellence, he is currently a PhD candidate in Computer Science at the Escuela Politécnica Nacional as of 2024. His formal education is further enhanced by certifications in English proficiency (B1), leadership, talent management, and organizational culture from institutions such as MIU City University Miami, Universidad Nacional de Chimborazo, SETEC, and IECAP. This diverse educational background reflects his dual focus on technical innovation and strategic management in the digital age.

Experience

Pedro Aguilar’s professional journey spans both the private sector and academia. He began his career as a Hardware and Software Technician at TEINCORP (2009–2011) and then served as a Full Stack Developer at CYMOGSYS in 2017. His work in academia began in 2018 at ESPOCH, where he held various roles such as IT Support Analyst, Registration Analyst, and currently serves as a Professor and Researcher since April 2023. His teaching covers programming, mobile computing, and web technologies, shaping the next generation of software engineers. Pedro’s experience is also deeply rooted in research and innovation, leading projects that use smart technologies like IoT and Progressive Web Apps. His interdisciplinary approach—blending IT systems with real-world applications like agriculture and water monitoring—demonstrates his commitment to socially impactful solutions. With over 5 years in academia and multiple years in industry, Pedro has developed a well-rounded, hands-on approach to technology and education.

Awards and Honors

Pedro Aguilar has earned multiple recognitions for his academic involvement and leadership. He was acknowledged by ESPOCH as a Reviewer at the II International Congress on Innovation, Science, and Technology (May–Nov 2023), reflecting his contributions to scientific quality and peer evaluation. He also received certifications in Leadership and Training from SETEC and MIU City University Miami, recognizing his ability to lead and inspire teams in technological and educational settings. His English language proficiency (B1) was certified by the Universidad Nacional de Chimborazo, supporting his active participation in international collaborations. In addition, he completed over 180 hours of certified training in areas like diversity, inclusion, human resources, organizational well-being, and corporate image—enhancing his ability to lead educational and research projects with a human-centered focus. While his academic and research achievements shine, his consistent pursuit of self-improvement stands as a testament to his professional excellence.

Research Focus

Pedro Aguilar’s research focus lies at the intersection of Software Engineering, Artificial Intelligence, and Information Systems for societal applications. His projects are strongly rooted in smart agriculture, environmental monitoring, and IoT systems, addressing real-world challenges through data-driven platforms. Notably, he contributed to the creation of a Predictive Platform for Cocoa Moniliasis Detection using sensors and AI, benefiting Ecuadorian agricultural zones. Currently, he is involved in developing an Intelligent Geoportal to monitor potable water quality using IoT technologies. Pedro is particularly interested in Progressive Web Applications (PWAs) and machine learning models to improve decision-making in critical sectors. His work integrates semantic web technologies, mobile computing, and vehicular networks (VANETs) to create scalable, sustainable digital solutions. With publications in international high-impact journals and conference proceedings, his research continues to evolve with emerging technologies while staying aligned with sustainable development and technological equity in Latin America.

Publication Top Notes

  • 🧠 Desarrollo de un modelo predictivo utilizando técnicas de aprendizaje supervisado para detectar la moniliasis en plantas de cacao de la Provincia de Orellana

  • 🌱 Fighting moniliasis in Orellana with sensors and PWA for sustainable agriculture

  • 🌾 Prevention of cocoa moniliasis using Progressive Web Applications and sensor data in the province of Francisco de Orellana

  • 📊 Predictive Model in Production through Progressive Web Applications to Forecast Moniliasis in Cacao

  • 🚗 Vehicular Ad-Hoc Network (VANET)

Dr. Md. Tarek Habib | Computer Science | Best Researcher Award

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Assist. Prof. Dr. Md. Tarek Habib | Computer Science | Best Researcher Award

Assist. Prof. Dr. Md. Tarek Habib Independent University, Bangladesh

Dr. Md. Tarek Habib is an Assistant Professor in the Department of Computer Science and Engineering at Independent University, Bangladesh. With a strong passion for teaching and research, his objective is to enhance his expertise in the field of Computer Science and Engineering. His research interests include Artificial Intelligence, with a focus on Computer Vision, Machine Learning, and Natural Language Processing, as well as IoT and E-Commerce. Dr. Habib is dedicated to advancing knowledge and innovation in these domains, contributing to both academia and industry through his research and mentorship.

Education:

Doctor of Philosophy (Ph.D.) in Computer Science and Engineering

Institution: Jahangirnagar University, Bangladesh

Year: 2022

Thesis Title: Machine Vision Based Fruit Disease Recognition

Supervisor: Prof. Dr. Mohammad Shorif Uddin

Co-Supervisor: Prof. Dr. Farruk Ahmed (Independent University, Bangladesh)

Master of Science (M.S.) in Computer Science and Engineering

Institution: North South University, Bangladesh

Year: 2009

CGPA: 3.85 on a scale of 4.0

Thesis Title: Machine Vision Based Textile Defects Classification

Supervisor: Prof. Dr. M. Rokonuzzaman

Bachelor of Science (B.Sc.) in Computer Science

Institution: BRAC University, Bangladesh

Year: 2006

CGPA: 3.74 on a scale of 4.0

Award: Vice Chancellor’s Medal

Thesis Title: A Survey on Location Systems for Ubiquitous Computing

Supervisor: Prof. Dr. Matin Saad Abdullah

Higher Secondary Certificate (HSC)

Institution: SOS Hermann Gmeiner College, Dhaka Board

Year: 2000

Division: 2nd Division (Science Group)

Total Marks: 567 out of 1000

Secondary School Certificate (SSC)

Institution: Sher-e-Bangla Nagar Govt. Boys’ High School, Dhaka Board

Year: 1998

Division: 1st Division with Star Marks (Science Group)

Total Marks: 823 out of 1000

Professional Profiles:

ORCID Profile

Scopus Profile

Professional Experience:

Assistant Professor, Department of Computer Science and Engineering

Independent University, Bangladesh January 2023

Associate Professor, Department of Computer Science and Engineering
Daffodil International University, Bangladesh (January 2023 – January 2023)

Assistant Professor, Department of Computer Science and Engineering
Daffodil International University, Bangladesh (January 2016 – December 2022)

Assistant Professor (Contractual), Department of Computer Science and Engineering
Daffodil International University, Bangladesh (September 2015 – December 2015)

Assistant Professor, Department of Computer Science and Engineering
Green University of Bangladesh (May 2014 – September 2015)

Assistant Professor, Department of Computer Science and Engineering
Prime University, Bangladesh (September 2013 – May 2014)

Senior Lecturer, Department of Computer Science and Engineering
Prime University, Bangladesh (January 2013 – August 2013)

Lecturer, Department of Computer Science and Engineering
Prime University, Bangladesh (October 2010 – December 2012)

Research Interests:

Artificial Intelligence (AI) and Its Applications

Computer Vision

Machine Learning (ML)

Natural Language Processing (NLP)

Internet of Things (IoT)

E-Commerce and AI-Driven Business Solutions

Top Notable Publications:

An Insightful Analysis of CNN-Based Dietary Medicine Recognition

Journal of Agriculture and Food Research, 2025-03

DOI: 10.1016/j.jafr.2024.101564

Contributors: Mohammad Didarul Alam, Tanjir Ahmed Niloy, Aurnob Sarker Aurgho, Mahady Hasan, Md. Tarek Habib

Deep Learning Modeling for Potato Breed Recognition

IEEE Transactions on AgriFood Electronics, 2024

DOI: 10.1109/TAFE.2024.3406544

Contributors: Md. Ataur Rahman, Abbas Ali Khan, Md. Mehedi Hasan, Md. Sadekur Rahman, Md. Tarek Habib

A Study on Social Media Addiction Analysis on the People of Bangladesh Using Machine Learning Algorithms

Bulletin of Electrical Engineering and Informatics, 2024-10-01

DOI: 10.11591/eei.v13i5.5680

Contributors: Minjun Nahar Mim, Mehedi Firoz, Mohammad Monirul Islam, Mahady Hasan, Md. Tarek Habib

Tomato Pest Recognition Using Convolutional Neural Network in Bangladesh

Bulletin of Electrical Engineering and Informatics, 2024-02-01

DOI: 10.11591/eei.v13i1.6073

Contributors: Johora Akter Polin, Nahid Hasan, Md. Tarek Habib, Atiqur Rahman, Zannatu Nayem Vasha, Bidyut Sharma

Publications (2020-2023)

A Machine Learning Approach for Driver Identification

Indonesian Journal of Electrical Engineering and Computer Science, 2023-04-01

DOI: 10.11591/ijeecs.v30.i1.pp276-288

Contributors: Md. Abbas Ali Khan, Mohammad Hanif Ali, Fazlul Haque, Md. Tarek Habib

Analysis of Recognition Performance of Plant Leaf Diseases Based on Machine Vision Techniques

Journal of Human, Earth, and Future, 2022-03-01

DOI: 10.28991/HEF-2022-03-01-09

Contributors: Imdadul Haque, Mohsin Alim, Mahbub Alam, Samia Nawshin, Sheak Rashed Haider Noori, Md. Tarek Habib

Machine Vision-Based Papaya Disease Recognition

Journal of King Saud University – Computer and Information Sciences, 2020-03

DOI: 10.1016/j.jksuci.2018.06.006

Contributors: Md. Tarek Habib, Anup Majumder, A.Z.M. Jakaria, Morium Akter, Mohammad Shorif Uddin, Farruk Ahmed

Conclusion:

Given his extensive publication record, research impact, and interdisciplinary contributions, Assist. Prof. Dr. Md. Tarek Habib is highly suitable for the Research for Best Researcher Award. His pioneering work in AI, ML, and IoT continues to drive innovation and technological advancements, making him a deserving recipient of this esteemed recognition.