Mr. Md. Asraful Sharker Nirob | Data Science | Best Researcher Award

Posted on by Academic achievements

Mr. Md. Asraful Sharker Nirob | Data Science | Best Researcher Award

Mr. Md. Asraful Sharker Nirob | Data Science – Researcher at Daffodil International University, Bangladesh

Md. Asraful Sharker Nirob is a highly motivated early-career researcher in computer science with a focus on machine learning, deep learning, and artificial intelligence applications. With a strong academic background and research involvement at the Health and Informatics Lab, he is driven to solve real-world problems in agriculture and healthcare using intelligent systems. His experience spans industry and academia, with a combination of technical expertise and leadership qualities that position him as a rising figure in applied AI research.

Profile:

Orcid | Scopus | Google Scholar

Education:

Nirob completed his Bachelor of Science in Computer Science and Engineering from a well-regarded university in Bangladesh, graduating with a CGPA of 3.70 out of 4.00. Throughout his academic journey, he maintained a high level of performance, actively engaged in research projects, and participated in student organizations. His academic background provided him with a solid foundation in software engineering, machine learning, data science, and algorithmic problem-solving.

Experience:

He is currently serving as a Research Assistant at the Health and Informatics Lab, where he works on AI-based models for disease diagnosis and predictive analysis. His responsibilities include dataset curation, preprocessing, and implementing neural network models using frameworks such as TensorFlow and PyTorch. Previously, he worked as a Junior Software Engineer, contributing to responsive web application development using React.js, JavaScript, and version control systems. He also gained administrative and communication experience as a Student Associate at the university’s career development center.

Research Interest:

Nirob’s research interests lie in machine learning 🤖, computer vision 👁️, deep learning 🧠, and natural language processing 💬. He is particularly passionate about explainable AI, neural network architectures, and hybrid deep learning models. His projects often explore the intersection of AI and practical domains like agriculture and medical imaging, with a goal to enhance classification accuracy, interpretability, and real-world impact.

Award:

Md. Asraful Sharker Nirob is a strong candidate for the Best Researcher Award due to his excellent research contributions, early career productivity, and innovative use of AI in solving domain-specific problems. His technical skills, multi-disciplinary collaborations, leadership in co-curricular activities, and strong academic record make him a well-rounded researcher. His dedication to publishing high-quality research and building accessible datasets adds further weight to his nomination.

Publications:

  • “XSE-TomatoNet” 🍅 – MethodsX, 2025
    Introduced an explainable AI approach using EfficientNetB0; cited for improving agricultural diagnostics.
  • “COLD-12” 🌿 – Franklin Open, 2025
    Hybrid CNN model for cotton disease detection; praised for high accuracy and innovation in multi-level features.
  • “Dragon Fruit Dataset” 🍓 – Data in Brief, 2023
    Created a comprehensive fruit maturity grading dataset; referenced in multiple dataset-driven research works.
  • “Brain Tumor Classification with Explainable AI” 🧠 – ECCE Conference, 2025
    Proposed a multi-scale attention fusion model; appreciated for bridging AI with medical imaging.
  • “Credit Card Fraud Detection” 💳 – IJRASET, 2024
    Leveraged behavioral biometrics and Random Forest; cited in interdisciplinary cybersecurity studies.
  • “Lemon Leaf Dataset” 🍋 – Data in Brief, 2024
    Shared high-quality annotated lemon disease dataset; reused in computer vision-based plant disease research.
  • “Sugarcane Disease Classification” 🌱 – IEEE STI Conference, 2024
    Applied hybrid DL model to agriculture; useful in smart farming systems and cited in precision agri-tech work.

Conclusion:

In summary, Md. Asraful Sharker Nirob demonstrates the qualities of a dedicated and impactful young researcher. With a diverse publication portfolio, technical depth, and ongoing contributions to pressing real-world problems, he stands out as a deserving nominee for the Best Researcher Award. His strong academic background, innovation in AI applications, and leadership in student activities indicate a promising future in academia and research. 🌟

 

 

 

Dr. Uddalak Mitra | Machine learning | Best Researcher Award

Posted on by Academic achievements

Dr. Uddalak Mitra | Machine learning | Best Researcher Award 

Dr. Uddalak Mitra, JIS College of Engineering, India

Dr. Uddalak Mitra is an Assistant Professor at JIS College of Engineering, affiliated with MAKAUT University, Kolkata, West Bengal. He holds a Ph.D. in Bioinformatics from Visva-Bharati University, Santiniketan, India. With expertise in bioinformatics, computational biology, machine learning, and deep learning, Dr. Mitra focuses on applying AI-driven methods to agriculture and medical diagnosis. He has published over 22 research articles and holds 9 patents under process. Actively mentoring students across academic levels, he also serves as a reviewer for reputed international journals. His research bridges biological sequence analysis and clinical applications, aiming to advance scientific and healthcare innovations.

Professional Profile:

GOOGLE SCHOLAR

ORCID

SCOPUS

Summary of Suitability for Best Researcher Award:

Dr. Uddalak Mitra is a highly suitable candidate for the Best Researcher Award due to his impactful contributions in the fields of bioinformatics, machine learning, and deep learning, with applications in healthcare and agriculture. With over 22 publications, including in SCI and Scopus-indexed journals, and 9 patents under process, he has demonstrated consistent research productivity and innovation. His interdisciplinary approach—bridging computational biology with AI-driven diagnostics—has advanced scientific understanding and clinical applications. As an active mentor and reviewer, Dr. Mitra exemplifies both academic excellence and leadership in research.

🎓 Education

  • 📘 Ph.D. in Bioinformatics
    🏫 Visva-Bharati University, Santiniketan, India
    🧬 Specialized in computational biology, machine learning, and their applications in bio-sciences.

💼 Work Experience

  • 👨‍🏫 Assistant Professor
    🏢 JIS College of Engineering, affiliated with MAKAUT University, Kolkata, West Bengal
    📆 Teaching & mentoring students (Ph.D., Master’s, UG)
    🔬 Active in interdisciplinary research combining ML/DL with bioinformatics and medical diagnostics
    🧠 Reviewer for international peer-reviewed journals

🏆 Achievements

  • 📚 22+ research publications in journals, conferences & book chapters

  • 🔍 5 papers in SCI/Scopus-indexed journals

  • 🧪 9 patents published or under process

  • 🧠 Research focus on AI-based biological sequence analysis & clinical diagnosis

  • 🤝 Member of IFERP & ISTE

🥇 Awards & Honors

  • 🏅 Award Nomination: Best Researcher Award (2025)

  • 📈 Citation Index:

    • h-index: 3

    • i10-index: 1

  • 🌐 Recognized for advancing AI-driven innovations in science and medicine

Publication Top Notes:

Ml-powered handwriting analysis for early detection of Alzheimer’s disease

CITED:11

PEER: a direct method for biosequence pattern mining through waits of optimal k-mers

CITED:6

Leveraging AI and Machine Learning for Next-Generation Clinical Decision Support Systems (CDSS)

CITED:4

An efficient tactic for analysis and evaluation of malware dump file using the volatility tool

CITED:3

Tandem repeat interval pattern identifies animal taxa

CITED:1

Ahmed Ghazi BLAIECH | Artificial intelligence | Best Researcher Award

Posted on by Academic achievements

Mr. Ahmed Ghazi BLAIECH | Artificial intelligence | Best Researcher Award

Mr. Ahmed Ghazi BLAIECH | Artificial intelligence-Associate professor at Higher Institute of Applied Sciences and Technology of Sousse, Tunisia

Ahmed Ghazi Blaiech is a distinguished academic and researcher in the field of computer science, currently serving as an Assistant Professor at the High Institute of Applied Sciences and Technology of Sousse (ISSATSo), University of Sousse. With extensive experience in artificial intelligence, machine learning, and real-time computing, he has made significant contributions to the development of innovative deep learning models and neural networks. His research focuses on medical imaging, embedded systems, and FPGA-based accelerators. Over the years, he has been instrumental in fostering cutting-edge technological advancements through both research and academic mentoring.

Profile:

Orcid | Scopus | Google Scholar

Education:

Ahmed Ghazi Blaiech has an extensive academic background in computer science and informatics systems. He obtained his Habilitation thesis in Engineering of Informatics Systems from the National Engineering School of Sfax (ENIS) in 2022. Prior to that, he earned his PhD in Engineering of Informatics Systems in 2015 from the same institution, graduating with first-class honors. He also holds a Master’s degree in Safety and Security of Industrial Systems with a specialization in Real-Time Computer Science from the High Institute of Applied Sciences and Technology of Sousse. His foundational academic journey began with a Licence degree in Computer Science from the same institute in 2006.

Experience:

Dr. Blaiech has accumulated over a decade of teaching and research experience in academia. Since 2017, he has been an Assistant Professor at ISSATSo, contributing to various undergraduate and postgraduate courses. Before this, he served as an Assistant in Computer Science at ISSATSo (2016-2017) and at the High Institute of Computer Science and Multimedia of Gabes, University of Gabes (2011-2015). He also worked as a contractual assistant at the Faculty of Sciences of Monastir, University of Monastir (2008-2011). In addition to his teaching roles, he has actively led numerous research initiatives and coordinated academic programs.

Research Interests:

Dr. Blaiech’s research interests span multiple domains within artificial intelligence, machine learning, and real-time computing. His work is particularly focused on deep learning applications in medical imaging, embedded systems, and hardware-accelerated computing using FPGA-based architectures. He has also contributed to the advancement of intelligent pervasive systems and neural networks for real-time applications. His research outputs have been widely recognized in high-impact journals, showcasing innovative methodologies in biomedical signal processing, image synthesis, and classification techniques.

Awards and Recognitions:

Throughout his career, Dr. Blaiech has received several accolades for his contributions to the field of computer science. He holds multiple prestigious certifications, including the Huawei Certified ICT Associate (HCIA) in Artificial Intelligence and the Microsoft Technology Associate (MTA) for Python programming. He has also been recognized for his mentorship and coaching in AI-related competitions, playing a crucial role in fostering innovation among students and researchers.

Publications:

Dr. Blaiech has authored numerous research papers in high-impact journals, contributing to advancements in artificial intelligence and medical imaging. Some of his notable publications include:

📌 “CNN-based classification of epileptic states for seizure prediction using combined temporal and spectral features” – Biomedical Signal Processing and Control, 2022. DOI 📖
📌 “An innovative medical image synthesis based on dual GAN deep neural networks for improved segmentation quality” – Applied Intelligence, 2022. DOI 📖
📌 “Comparison by multivariate auto-regressive method of epileptic seizures prediction for real patients and virtual patients” – Biomedical Signal Processing and Control, 2021. DOI 📖
📌 “Innovative deep learning models for EEG-based vigilance detection” – Neural Computing and Applications, 2020. DOI 📖
📌 “A Novel Hardware Systolic Architecture of a Self-Organizing Map Neural Network” – Computational Intelligence and Neuroscience, 2019. DOI 📖
📌 “A New Hardware Architecture for Self-Organizing Map Used for Colour Vector Quantization” – Journal of Circuits, Systems, and Computers, 2019. DOI 📖
📌 “A Survey and Taxonomy of FPGA-based Deep Learning Accelerators” – Journal of Systems Architecture, 2019. DOI 📖

Conclusion:

Dr. Ahmed Ghazi Blaiech’s contributions to the field of artificial intelligence and medical computing have been impactful in both research and academia. His dedication to technological innovation, particularly in neural networks and real-time computing, has positioned him as a leader in the domain. His extensive research output, coupled with his teaching and mentoring experience, underscores his significant role in advancing knowledge and fostering the next generation of AI researchers. Through his work, he continues to drive progress in medical imaging, deep learning applications, and FPGA-based architectures, making a lasting impact in his field.