SYED NAVAZ A S | Computer Science | Research Excellence Award

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Dr. SYED NAVAZ A S | Computer Science | Research Excellence Award

Shine & Inspire Academy | India

Dr. A. S. Syed Navaz is an accomplished academician, researcher, and educational leader with over 14 years of teaching experience at both undergraduate and postgraduate levels in the field of Computer Science and Applications. He holds a Ph.D. in Computer Science from Prist University, Thanjavur, where his doctoral research focused on Layer-Based and Flow-Based Channel Assignment in Tree-Structured Wireless Sensor Networks for Fast Data Collection, reflecting his strong expertise in networking and data communication systems. Beyond academia, Dr. Syed Navaz plays prominent leadership roles as Publisher and Chief Editor of the International Organization of Innovative Research & Publishers (IOIRP) and as Managing Director of Shine & Inspire Academy, where he supports research, Ph.D. guidance, publications, patents, entrepreneurship training, and motivational and soft-skill development. He has also successfully mobilized government funding through DST–NSTEDB for multiple Entrepreneurship Awareness Camps, demonstrating his commitment to innovation and societal development. With multidisciplinary expertise spanning education, research, entrepreneurship, blockchain consulting, and life advisory services, Dr. A. S. Syed Navaz continues to make impactful contributions to academic excellence, research advancement, and human capacity building.

 

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Featured Publications

Entropy Based Anomaly Detection System to Prevent DDoS Attacks in Cloud
– International Journal of Computer Applications, 2013
Data Visualization: Enhancing Big Data More Adaptable and Valuable
– International Journal of Applied Engineering Research, 2016
Face Recognition Using Principal Component Analysis and Neural Networks
– International Journal of Computer Networking, Wireless and Mobile Computing, 2013
Human Resource Management System
– IOSR Journal of Computer Engineering, 2013
Flow Based Layer Selection Algorithm for Data Collection in Tree Structure Wireless Sensor Networks
– International Journal of Applied Engineering Research, 2016

Vincenzo Arceri | Computer Science | Best Researcher Award

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Dr. Vincenzo Arceri | Computer Science | Best Researcher Award

Dr. Vincenzo Arceri | Computer Science | University of Parma | Italy

Dr. Vincenzo Arceri is an accomplished computer scientist and Assistant Professor at the University of Parma, Italy. His expertise lies in abstract interpretation, static program analysis, blockchain security, and formal methods for ensuring software reliability. With a strong academic background and multiple research fellowships, he has established himself as a leading voice in advancing secure, dependable software systems. Dr. Arceri has contributed significantly to the development of static analysis tools, including LiSA, a generic library for static analysis, and EVMLiSA, a specialized analyzer for Ethereum smart contracts. His research extends into improving the quality and security of large language model–generated code, showcasing his commitment to addressing emerging challenges in artificial intelligence and blockchain domains. Recognized internationally through invitations to prestigious Dagstuhl Seminars, awards, and collaborations, Dr. Arceri combines research excellence with impactful teaching, mentoring students in programming and fostering the next generation of computer scientists.

Author Profiles

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Education

Dr. Vincenzo Arceri pursued his academic journey at the University of Verona, Italy, where he obtained a Bachelor’s Degree in Computer Science in 2014 with a thesis on semantic analysis techniques for JavaScript. He continued his studies with a Master’s Degree in Computer Science, graduating cum laude in 2016, with a thesis focusing on static type analysis for PHP. Building upon his foundation, he earned his Ph.D. in Computer Science in 2020, presenting a dissertation titled “Taming Strings in Dynamic Languages – An Abstract Interpretation-based Static Analysis Approach.” His doctoral work, supervised by Prof. Isabella Mastroeni, was critically acclaimed by international reviewers such as Prof. Sergio Maffeis and Prof. Xavier Rival. Through this academic pathway, Dr. Arceri specialized in the rigorous application of abstract interpretation to real-world programming challenges, setting the stage for his future contributions to static analysis, software verification, and blockchain-related applications.

Experience

Dr. Vincenzo Arceri began his research career as a Postdoctoral Researcher at Ca’ Foscari University of Venice (2019–2021), where he worked on IoT applications in smart cities and the development of static analysis tools for Go, particularly in the context of blockchain smart contracts. His research there focused on formal verification and the precision–efficiency trade-offs in string analysis. In September 2021, he joined the University of Parma as an Assistant Professor, where he currently teaches Fundamentals of Programming to undergraduate students while continuing his research in advanced program analysis. His contributions include designing LiSA, a generic static analysis framework, and EVMLiSA, a static analyzer for Ethereum Virtual Machine bytecode. He has also explored static analysis for unsafe Rust programs and LLM-generated code. Dr. Arceri’s professional trajectory reflects a balance of teaching, applied research, and international collaboration with academic and industry partners.

Awards and Honors

Dr. Vincenzo Arceri’s research excellence has been recognized through prestigious awards and honors. In 2019, he received the Best Paper Award at VALID 2019 for his contribution to the operational semantics of Solidity, highlighting his innovative work in blockchain verification. His international reputation was further affirmed with scholarships such as the Marktoberdorf Summer School in 2018, which focused on engineering secure and dependable software systems. In 2023, he was awarded INdAM GNCS funding to support his participation in international conferences, workshops, and seminars. Furthermore, Dr. Arceri has been invited to the distinguished Dagstuhl Seminars in 2023 and 2025, gatherings known for shaping the future of computer science research. These invitations underscore his standing as an expert in abstract interpretation and static analysis. Collectively, these accolades reflect his academic rigor, groundbreaking contributions, and the international recognition he has garnered for advancing software reliability and security.

Research Focus

Dr. Vincenzo Arceri’s research centers on the application of abstract interpretation to improve the security, reliability, and correctness of software systems. He has dedicated his career to advancing static program analysis for a wide range of programming paradigms, from dynamic languages such as JavaScript and PHP to domain-specific blockchain applications. His work also addresses the challenges of analyzing unsafe Rust code and verifying smart contracts in Go and Ethereum. Notably, he has developed LiSA, a multilanguage static analysis framework, and EVMLiSA, a static analyzer tailored to EVM bytecode, demonstrating his ability to merge theoretical rigor with practical implementations. His recent projects explore the safety of LLM-generated code, aiming to ensure that AI-driven programming integrates robust security principles. By balancing precision and performance in static analysis, Dr. Arceri’s work provides a critical foundation for future-proof software engineering, cross-blockchain applications, and secure AI-integrated development practices.

Publications

  • Static analysis for dummies: experiencing LiSA.

  • Analyzing Dynamic Code: A Sound Abstract Interpreter for Evil Eval.

  • LiSA: a generic framework for multilanguage static analysis.

  • Static Program Analysis for String Manipulation Languages.

  • Static analysis for ECMAScript string manipulation programs.

  • Ensuring determinism in blockchain software with GoLiSA: an industrial experience report.

  • Information flow analysis for detecting non-determinism in blockchain.

  • Twinning automata and regular expressions for string static analysis.

  • Abstract domains for type juggling.

  • Relational string abstract domains.

Conclusion

Dr. Vincenzo Arceri exemplifies the qualities of a modern computer scientist—innovative, collaborative, and deeply committed to advancing the reliability of digital systems. His work bridges theory and practice, from foundational contributions in abstract interpretation to impactful tools for blockchain verification and AI-generated code analysis. With a growing body of influential publications, awards, and teaching contributions, he stands as a leading researcher shaping the future of secure and dependable software systems.

 

Syed Mohammod Minhaz Hossain | Computer Science | Best Researcher Award

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Assoc. Prof. Dr. Syed Mohammod Minhaz Hossain | Computer Science | Best Researcher Award

👤 Assoc. Prof. Dr. Syed Mohammod Minhaz Hossain, Premier University, Bangladesh

Syed Mohammod Minhaz Hossain is a passionate researcher and IT professional dedicated to advancing the field of Computer Science and Engineering. He is currently pursuing a Ph.D. in Computer Science & Engineering at Chittagong University of Engineering & Technology (CUET). With a strong academic background, he earned his M.Sc. and B.Sc. in Computer Science & Engineering from CUET, securing notable positions. Hossain is committed to skillful learning and aims to create a synergy between industry and academia. He has published numerous research papers and contributed significantly to the scientific community, particularly in the areas of AI, machine learning, and environmental studies. Apart from his academic journey, he is a fervent advocate of education, believing in the power of teaching to shape well-rounded professionals who can contribute to society’s progress.

Professional Profile

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 🌟  Suitability of Syed Mohammod Minhaz Hossain for the Research for Best Researcher Award:

Syed Mohammod Minhaz Hossain demonstrates strong academic and professional qualifications, making him a highly suitable candidate for the Research for Best Researcher Award. His dedication to academic excellence and research is reflected in his substantial academic achievements, including a Ph.D. in Computer Science and Engineering from Chittagong University of Engineering & Technology (CUET), and his outstanding undergraduate and postgraduate performance. His consistent recognition, such as the UGC Ph.D. Fellowship and multiple scholarships, underscores his commitment to research and academic growth.

Hossain has made notable contributions to the research community, particularly in the fields of artificial intelligence, machine learning, and environmental science. His extensive publication record includes numerous articles in high-impact journals such as PLoS ONE, Chemosphere, and Annals of Data Science, with a variety of topics ranging from water quality assessments to disease classification and COVID-19 detection using deep learning. His research not only focuses on technological advancements but also addresses pressing societal challenges, such as public health, environmental sustainability, and cybersecurity.

🎓  Education

Syed Mohammod Minhaz Hossain’s academic journey is marked by consistent excellence. He is currently pursuing his Ph.D. in Computer Science & Engineering at Chittagong University of Engineering & Technology (CUET). Prior to that, he completed his M.Sc. in Computer Science & Engineering at CUET in 2022, where he earned a CGPA of 3.42. He also holds a B.Sc. in the same field from CUET, securing a remarkable CGPA of 3.56. His foundation in education started at Chittagong Collegiate School, where he excelled with a GPA of 4.63 in his SSC and later earned a GPA of 4.50 in his HSC at Chittagong College. Throughout his academic career, Hossain has received multiple scholarships, including the UGC PhD Fellowship (2021-2022) and various merit-based awards, underlining his dedication and outstanding performance in the field of Computer Science.

💼 Professional Experience

Syed Mohammod Minhaz Hossain’s professional experience blends academia and industry, underscoring his passion for teaching and research. As a faculty member at Premier University, Bangladesh, Hossain conducts web system and program applications courses, integrating real-world industry skills into the classroom. His expertise is further demonstrated through his role in various research projects, focusing on areas such as artificial intelligence, deep learning, and environmental science. Hossain’s experience includes collaborating with international researchers, contributing to high-impact journals and conferences. His role in designing and developing academic curricula reflects his commitment to fostering future IT professionals who are not only skilled but also socially responsible. Additionally, Hossain’s involvement in the University of Technology, Sydney (UTS) College’s academic programs highlights his global outlook and the application of advanced research in practical teaching settings.

🏅 Awards and Recognitions 

Syed Mohammod Minhaz Hossain’s journey is characterized by numerous academic and research accolades. He received the prestigious UGC PhD Fellowship for 2021-2022, showcasing his commitment to advancing knowledge in Computer Science. Hossain earned the fourth position in his B.Sc. at CUET and was a recipient of the Board Scholarship in his HSC in 2003. He was also honored with the Junior Merit Scholarship in 1998 and the Primary Merit Scholarship in 1995, underlining his consistent academic excellence from an early age. His research contributions have been widely recognized, with multiple publications in high-impact journals such as PLoS ONE, Annals of Data Science, and Chemosphere. Furthermore, Hossain’s work on machine learning models for health-related issues and his involvement in international book chapters reflect his growing influence in the global research community.

🌍 Research Skills On Computer Science

Syed Mohammod Minhaz Hossain possesses a broad range of research skills that span artificial intelligence, machine learning, deep learning, and data science. His expertise includes applying these advanced technologies to solve complex problems in areas like health diagnostics, environmental monitoring, and cybersecurity. Hossain has developed proficiency in using deep neural networks, self-attention mechanisms, and convolutional models, as seen in his research on plant leaf disease recognition and heart disease prediction. Additionally, he has contributed to studies focused on the detection of COVID-19 fake news, Parkinson’s disease classification, and coastal water quality assessment. His research methodology includes leveraging large datasets, conducting statistical analyses, and employing advanced algorithms to create efficient and scalable solutions. Hossain’s ability to integrate interdisciplinary knowledge into his projects further enhances his capability to make impactful contributions to both academic and practical fields.

📖 Publication Top Notes

  • Cyber Intrusion Detection Using Machine Learning Classification Techniques
    • Authors: H Alqahtani, IH Sarker, A Kalim, SMM Hossain, S Ikhlaq, S Hossain
    • Citations: 189
    • Year: 2020
  • A Data-Driven Heart Disease Prediction Model Through K-Means Clustering-Based Anomaly Detection
    • Authors: RC Ripan, IH Sarker, SMM Hossain, MM Anwar, R Nowrozy, MM Hoque
    • Citations: 66
    • Year: 2021
  • Rice Leaf Diseases Recognition Using Convolutional Neural Networks
    • Authors: SMM Hossain, MMM Tanjil, MAB Ali, MZ Islam, MS Islam, S Mobassirin
    • Citations: 49
    • Year: 2021
  • Plant Leaf Disease Recognition Using Depth-Wise Separable Convolution-Based Models
    • Authors: SMM Hossain, K Deb, PK Dhar, T Koshiba
    • Citations: 34
    • Year: 2021
  • Amassing the Covid-19 Driven PPE Wastes in the Dwelling Environment of Chittagong Metropolis and Associated Implications
    • Authors: MJ Abedin, MU Khandaker, MR Uddin, MR Karim, MSU Ahamad
    • Citations: 22
    • Year: 2022
  • Assessment of Coastal River Water Quality in Bangladesh: Implications for Drinking and Irrigation Purposes
    • Authors: MR Uddin, MU Khandaker, S Ahmed, MJ Abedin, SMM Hossain
    • Citations: 13
    • Year: 2024
  • Spam Filtering of Mobile SMS Using CNN–LSTM Based Deep Learning Model
    • Authors: SMM Hossain, JA Sumon, A Sen, MI Alam, KMA Kamal, H Alqahtani
    • Citations: 13
    • Year: 2021
  • Plant Leaf Disease Recognition Using Histogram-Based Gradient Boosting Classifier
    • Authors: SMM Hossain, K Deb
    • Citations: 13
    • Year: 2021
  • Content-Based Spam Email Detection Using an N-gram Machine Learning Approach
    • Authors: NJ Euna, SMM Hossain, MM Anwar, IH Sarker
    • Citations: 9
    • Year: 2023
  • Trash Image Classification Using Transfer Learning-Based Deep Neural Network
    • Authors: D Das, A Sen, SMM Hossain, K Deb
    • Citations: 9
    • Year: 2022