Hafiz Mohammad Hasan Babu | Computer Science | Lifetime Achievement in Books Award

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Prof. Hafiz Mohammad Hasan Babu | Computer Science | Lifetime Achievement in Books Award

University of Dhaka | Bangladesh

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Early Academic Pursuits

Prof. Hafiz Mohammad Hasan Babu began his academic journey in the realm of computer science and engineering with a strong foundation from the Brno University of Technology, Czech Republic, where he completed his M.Sc. with a focus on logic network automation. His curiosity for advanced computational systems took him to the Kyushu Institute of Technology in Japan, where he earned his Ph.D. in Computer Science and Electronics. His doctoral work concentrated on data structures for multiple-output functions and their applications in VLSI CAD, under the guidance of Prof. Dr. Tsutomu Sasao. These formative years laid the groundwork for his future innovations in quantum computing, reversible logic, and nanotechnology.

Professional Endeavors

Prof. Hasan Babu's academic career spans several decades and institutions, notably the University of Dhaka, where he served in various capacities, including as professor in the departments of Computer Science and Engineering, and Robotics and Mechatronics Engineering. His early academic roles also included positions at Khulna University. He has been deeply involved in curriculum development, student mentorship, and departmental leadership. Beyond teaching, he also contributed significantly as a research supervisor and played a critical role in developing the academic and research culture of computer science in Bangladesh.

Contributions and Research Focus

A prolific researcher, Prof. Hasan Babu has made groundbreaking contributions in the fields of quantum computing, reversible logic design, DNA computing, and machine learning applications in healthcare and agriculture. His interdisciplinary research integrates electronics, artificial intelligence, and biological systems. His most recent works delve into quantum biocomputing and nanotechnology, as evidenced by his multi-volume publications with Springer Nature and CRC Press. He has also authored numerous peer-reviewed articles on topics such as cardiovascular disease detection using mobile AI, air quality forecasting, and toxic substance identification in fruits through deep learning.

Accolades and Recognition

Prof. Hasan Babu has received numerous prestigious awards recognizing his excellence in research and scholarly contributions. These include the Dhaka University Research Excellence Recognition, the UGC Gold Medal, and the Dr. M. O. Ghani Memorial Gold Medal from the Bangladesh Academy of Sciences. His biography has been featured in “Who's Who in the World, USA.” He has also received international fellowships such as the Japanese Government Scholarship, the DAAD Fellowship from Germany, and a Czechoslovakian Government Scholarship, marking his global academic influence.

Impact and Influence

Throughout his academic life, Prof. Hasan Babu has significantly influenced the fields of computer science, electronics, and artificial intelligence. His innovations in reversible logic and DNA computing have shaped research methodologies and applications in both academia and industry. He has been instrumental in advancing computational methods that address real-world problems, particularly in environmental monitoring, biomedical diagnostics, and agricultural automation. His role as a mentor to doctoral and master’s students further amplifies his impact on the next generation of scholars.

Legacy and Future Contributions

Prof. Hasan Babu’s extensive scholarly contributions, particularly in the emerging domains of quantum AI and biocomputing, position him as a thought leader in futuristic technologies. His upcoming publications promise to offer new paradigms in nanotechnology and molecular-level computing. As he continues to mentor new researchers and expand the boundaries of interdisciplinary science, his legacy will be defined by his relentless pursuit of innovation and his dedication to fostering a globally relevant research ecosystem.

List of Book Publications

Books Published in 2025:

1. Quantum AI Emerging Technologies: Driving Innovation and Shaping the Future of Nanotechnology, Volume I, Springer Nature, Singapore.

2. Quantum AI Emerging Technologies: Driving Innovation and Shaping the Future of Nanotechnology, Volume II, Springer Nature, Singapore.

3. Quantum Biocomputing in Quantum Biology, Volume I, Springer Nature, Singapore.

4. Quantum Biocomputing in Quantum Biology, Volume II, Springer Nature, Singapore.

Book Published in 2024:
5. DNA Logic Design: Computing with DNA, World Scientific Publishing Co Pte Ltd., Singapore.

Books Published in 2023:
6. Multiple-Valued Computing in Quantum Molecular Biology, Volume I, CRC Press, USA.
7. Multiple-Valued Computing in Quantum Molecular Biology, Volume II, CRC Press, USA.

Books Published in 2022:
8. VLSI Circuits and Embedded Systems, CRC Press, USA.
9. Control Engineering Theory and Applications (Co-authored with Md. Jahangir Alam, Guoqing Hu, and Huazhong Xu), CRC Press, USA.

Books Published in 2020:
10. Quantum Computing: A Pathway to Quantum Logic Design, 2nd Edition, IOP Publishers, Bristol, UK.
11. Reversible and DNA Computing, Wiley Publishers, UK.

Journal Publications

Analyzing infant cry to detect birth asphyxia using a hybrid CNN and feature extraction approach
Authors: Samrat Kumar Dey, Khandaker Mohammad Mohi Uddin, Arpita Howlader, Md Mahbubur Rahman, Hafiz Md Hasan Babu, Nitish Biswas, Umme Raihan Siddiqi, Badhan Mazumder
Journal: Neuroscience Informatics (Elsevier)
Year: 2025

Empowering early detection: A web-based machine learning approach for PCOS prediction
Authors: Md. Mahbubur Rahman, Ashikul Islam, Forhadul Islam, Mashruba Zaman, Md Rafiul Islam, Md Shahriar Alam Sakib, Hafiz Md Hasan Babu
Journal: Journal of Informatics in Medicine (Elsevier)
Year: 2024

Computer vision based deep learning approach for toxic and harmful substances detection in fruits
Authors: Abdus Sattar, Md. Asif Mahmud Ridoy, Aloke Kumar Saha, Hafiz Md. Hasan Babu, Mohammad Nurul Huda
Journal: Heliyon (Cell Press)
Year: 2024

A Comprehensive Approach to Detecting Chemical Adulteration in Fruits Using Computer Vision, Deep Learning, and Chemical Sensors
Authors: Abdus Sattar, Md. Asif Mahmud Ridoy, Aloke Kumar Saha, Hafiz Md. Hasan Babu, Mohammad Nurul Huda
Journal: Journal of Intelligent Systems with Applications (Elsevier)
Year: 2024

A Voice assistive mobile application tool to detect cardiovascular disease using machine learning approach
Authors: Khandaker Mohammad Mohi Uddin, Samrat Kumar Dey, Hafiz Md Hasan Babu
Journal: Biomedical Materials & Devices (Springer US)
Year: 2024

Conclusion

Prof. Hafiz Mohammad Hasan Babu embodies the spirit of academic excellence and innovation in computer science. With a career rich in scholarly output, international collaborations, and student mentorship, he has become a beacon of transformative research and a visionary in integrating quantum theory with computational systems. His work continues to influence the scientific community both in Bangladesh and globally, promising continued advancements in technology and applied sciences.

Luis Cavique | Computer Science | Best Research Award

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Prof. Luis Cavique | Computer Science | Best Research Award

Universidade Aberta | Portugal

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Early Academic Pursuits 🎓

Prof. Luís Cavique began his academic journey with a strong foundation in Computer Science, earning a degree in Computer Science Engineering in 1988 from the Faculty of Science and Technology at the New University of Lisbon. His pursuit of advanced knowledge continued with a Master’s in Operational Research and Systems Engineering in 1994 from the Instituto Superior Técnico, Technical University of Lisbon, where he focused on complex problems like crew scheduling. His academic commitment culminated in 2002 with a PhD in Engineering Systems, where he explored meta-heuristics for the Maximum Clique Problem, emphasizing applications in market basket analysis. This robust educational background set the stage for a career marked by analytical depth and academic rigor.

Professional Endeavors 👨‍🏫

Prof. Cavique’s teaching career spans several decades, beginning in 1991 in the Polytechnic Education System in Portugal, where he held adjunct positions at Setúbal and Lisbon Polytechnic Institutes until 2008. Since then, he has served as an Assistant Professor with tenure at the Universidade Aberta, focusing on computer science within the Department of Sciences and Technology. His dedication to fostering knowledge extends to graduate and doctoral levels, where he teaches courses such as Data Mining, Social Network Analysis, and Optimization. Beyond academia, Prof. Cavique also gained hands-on experience in the banking sector as a Systems Engineer at Banco Pinto & Sotto Mayor and through internships at prominent institutions like Banco Espírito Santo and the National Laboratory of Civil Engineering.

Contributions and Research Focus 🔍

With a strong interdisciplinary approach, Prof. Cavique’s research bridges Computer Science and Engineering Systems, focusing primarily on heuristic optimization and data mining. His work has addressed three core data mining challenges: classification, association, and segmentation. Notable publications include groundbreaking algorithms and tools, such as the LAID algorithm for classification, Ramex for association in financial product analysis, and ComDetection for community detection in social networks. These contributions have positioned Prof. Cavique at the forefront of data-driven research, and his methods are applied widely in sectors requiring complex data analysis.

Accolades and Recognition 🏆

Prof. Cavique's scholarly work has been recognized internationally, with several of his papers published in prestigious journals. His 1999 paper on crew scheduling received the IFORS-Lisbon Prize in 2000 from the Association of Operational Research in Portugal (APDIO). Many of his publications are highly cited, with articles featured in Q1-ranked journals, illustrating the high impact and quality of his research. His dedication to advancing data mining and optimization has earned him both peer recognition and a strong citation record, showcasing his influence in these fields.

Impact and Influence 🌍

Throughout his career, Prof. Cavique has made a lasting impact on the fields of data mining and heuristic optimization. His research has influenced approaches in financial analytics, community detection in social networks, and data reduction techniques, providing foundational tools and algorithms that are utilized in academia and industry alike. His methodologies have empowered researchers and practitioners in various domains to make informed, data-driven decisions, underscoring his role as a pioneer in computational research.

Legacy and Future Contributions 🌟

As a leading academic and researcher, Prof. Cavique’s legacy is defined by his contributions to both knowledge and education in computer science. His focus on heuristic optimization and data mining continues to inspire new research, particularly in emerging fields such as bioinformatics and social network analysis. His commitment to teaching and mentoring the next generation of scientists ensures that his impact will extend well into the future, enriching the scientific community and driving innovation in computational methods.

 

Publications

  • 📝 Mitigating false negatives in imbalanced datasets: An ensemble approach
    Authors: Marcelo Vasconcelos; Luís Cavique
    Journal: Expert Systems with Applications
    Year: 2024
  • 📝 Assessment in Collaborative Learning
    Authors: Luis Cavique; M. Rosário Ramos
    Journal: Revista de Educación a Distancia (RED)
    Year: 2024

 

Dimitrios Karapiperis | Computer Science | Best Research Award

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Dr. Dimitrios Karapiperis | Computer Science | Best Research Award

International Hellenic University | Greece

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🎓 Early Academic Pursuits

Dr. Dimitrios Karapiperis embarked on his academic journey with a BSc degree in Information Technology from the Technological Educational Institute of Thessaloniki, Greece, where he developed a strong foundation in applied technology. His passion for computer science led him to pursue an MSc degree in Software Engineering at the University of York, UK, funded by the State Scholarships Foundation of Greece (ΙΚΥ). During this time, he honed his skills in software engineering and expanded his knowledge in computer science.

Furthering his academic aspirations, Dr. Karapiperis earned a PhD in Computer Science from the Hellenic Open University, Greece. His research during this period focused on the field of Entity Resolution (Record Linkage), where he developed similarity algorithms, data structures, approximation schemes, and scalable distributed solutions. This phase of his education laid the groundwork for his future contributions to the field of computer science.

💼 Professional Endeavors

Dr. Karapiperis' professional career is marked by his dedication to both teaching and research. He has held various academic positions, including his current role as a lecturer at the Hellenic Open University, where he teaches courses on Data Mining and Machine Learning techniques. He also serves as an adjunct lecturer at the International Hellenic University, Greece, where he imparts knowledge on subjects such as Knowledge Management in the Web, Big Data and Cloud Computing, and Exploratory Data Analysis and Visualization. His previous roles include an adjunct lecturer position at the University of Western Macedonia, Greece, where he taught courses in Data Technologies and Database Management. Additionally, Dr. Karapiperis has experience as a research intern at the University of York, UK, and as a research assistant at the University of Macedonia, Greece, where he developed web and database applications.

🔬 Contributions and Research Focus

Dr. Karapiperis has made significant contributions to the field of computer science, particularly in the area of privacy-preserving record linkage. His research work includes the design of similarity algorithms, data structures, and approximation schemes that enable large-scale systems to perform record linkage while preserving privacy. His innovative use of randomization schemes, such as Locality-Sensitive Hashing (LSH) and count-min sketches, has advanced the field and provided practical solutions for handling voluminous data. In addition to his research, Dr. Karapiperis has supervised over 30 post-graduate theses at the International Hellenic University and Hellenic Open University, guiding students in topics related to Big Data management and the design of efficient algorithms.

🏆 Accolades and Recognition

Throughout his career, Dr. Karapiperis has earned recognition for his contributions to academia and research. His dedication to teaching, research, and the development of innovative algorithms has positioned him as a respected figure in the field of computer science. His expertise and commitment to advancing knowledge have garnered him the respect of his peers and students alike.

🌍 Impact and Influence

Dr. Karapiperis' work has had a profound impact on the field of computer science, particularly in the areas of data management and privacy-preserving technologies. His research on scalable and distributed solutions for Entity Resolution has influenced the development of more secure and efficient systems for handling large datasets. Moreover, his role as an educator has enabled him to shape the minds of future computer scientists, ensuring that his influence extends beyond his own research.

🚀 Legacy and Future Contributions

As Dr. Karapiperis continues his academic and research endeavors, his legacy is one of innovation, dedication, and impact. His ongoing work in developing cutting-edge algorithms and scalable solutions positions him as a leader in the field. With a strong foundation in both education and research, Dr. Karapiperis is poised to make even greater contributions to computer science in the years to come.

 

Publications

  • 📝Predicting Football Match Results Using a Poisson Regression Model
    Authors: Konstantinos Loukas, Dimitrios Karapiperis, Georgios Feretzakis, Vassilios S. Verykios
    Journal: Applied Sciences
    Year: 2024
  • 📝A Suite of Efficient Randomized Algorithms for Streaming Record Linkage
    Authors: Dimitrios Karapiperis, Christos Tjortjis, Vassilios S. Verykios
    Journal: IEEE Transactions on Knowledge and Data Engineering
    Year: 2024
  • 📝Machine Learning in Medical Triage: A Predictive Model for Emergency Department Disposition
    Authors: Georgios Feretzakis, Aikaterini Sakagianni, Athanasios Anastasiou, Ioanna Kapogianni, Rozita Tsoni, Christina Koufopoulou, Dimitrios Karapiperis, Vasileios Kaldis, Dimitris Kalles, Vassilios S. Verykios
    Journal: Applied Sciences
    Year: 2024
  • 📝Tracing Student Activity Patterns in E-Learning Environments: Insights into Academic Performance
    Authors: Evgenia Paxinou, Georgios Feretzakis, Rozita Tsoni, Dimitrios Karapiperis, Dimitrios Kalles, Vassilios S. Verykios
    Journal: Future Internet
    Year: 2024

 

Kalyanapu Srinivas | Computer Science | Best Researcher Award

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Dr. Kalyanapu Srinivas | Computer Science | Best Researcher Award

Vaagdevi Engineering College | India

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Early Academic Pursuits 🎓

Dr. Kalyanapu Srinivas embarked on his academic journey with a Bachelor of Technology (B.Tech) in Computer Science Engineering from Vidya Bharathi Institute of Technology, graduating in 2006 with First Division honors. He continued to advance his studies with a Master of Technology (M.Tech) in Software Engineering from Ramappa Engineering College in 2010, where he achieved Distinction with a 78.2% score. Further solidifying his academic prowess, Dr. Srinivas completed his Ph.D. in Cryptography & Network Security at JNTU, Hyderabad in 2020.

Professional Endeavors 💼

Dr. Srinivas has accumulated over 16 years of experience in academia. His professional journey includes roles such as Assistant Professor at various institutions, including Vaagdevi Engineering College, Kakatiya Institute of Technology and Science, and SR Engineering College. His tenure in these roles highlights his commitment to advancing the field of computer science and engineering. Notably, he has been involved in teaching, research, and academic administration.

Contributions and Research Focus 🔬

Dr. Srinivas’s research primarily focuses on Cryptography and Network Security, with a keen interest in Data Mining, Cloud Computing, and Quantum Computing. His Ph.D. thesis, titled "Novel Techniques for Image-Based Key Generation using Chinese Remainder Theorem and Chaotic Logistic Maps," reflects his innovative approach to enhancing security protocols. Additionally, his ongoing research guidance includes supervising several Ph.D. students in areas such as Wireless Networks and Cloud Computing.

Accolades and Recognition 🏆

Dr. Srinivas has earned significant recognition throughout his career. His work in machine learning and cryptography has led to the publication of a patent on Alzheimer's prediction using machine learning. He has also been honored as a session chair at the International Conference on Research in Science, Engineering, Technology, and Management (ICRSETM2020) and served as a guest speaker at SAFER INTERNET DAY 2023. His expertise has been acknowledged through editorial and review roles for various conferences and journals.

Impact and Influence 🌍

Dr. Srinivas’s contributions extend beyond his research. His involvement in organizing and participating in short-term training programs (STTP) on IoT simulation and fog computing showcases his dedication to fostering knowledge and innovation in emerging technologies. His role as a primary evaluator for TOYCATHON 2021 further emphasizes his influence in shaping the future of technology education and development.

Legacy and Future Contributions 🚀

Looking ahead, Dr. Srinivas is poised to continue making impactful contributions to the fields of cryptography and network security. His research initiatives and academic leadership are expected to drive advancements in secure computing and innovative technologies. As he mentors the next generation of researchers and contributes to cutting-edge research, his legacy in the academic and professional realms will undoubtedly endure, inspiring future advancements in technology and education.

 

Publications 📚

  • Article: Underground Water Level Prediction in Remote Sensing Images Using Improved Hydro Index Value with Ensemble Classifier
    Authors: Stateczny, A., Narahari, S.C., Vurubindi, P., Guptha, N.S., Srinivas, K.
    Journal: Remote Sensing
    Year: 2023
  • Article: User-segregation based channel estimation in the MIMO system
    Authors: Patra, R.K., Kumar, M.H., Srinivas, K., Sekhar, P.C., Subhashini, S.J.
    Journal: Physical Communication
    Year: 2023
  • Book Chapter: An Enhancement in Crypto Key Generation Using Image Features with CRT
    Authors: Srinivas, K., Kumar, N.S., Sanathkumar, T., Rama Devi, K.
    Book: Cognitive Science and Technology
    Year: 2023
  • Article: Plant disease classification using deep bilinear CNN
    Authors: Rao, D.S., Ramesh Babu, C., Kiran, V.S., Mohan, G.S., Bharadwaj, B.L.
    Journal: Intelligent Automation and Soft Computing
    Year: 2022
  • Article: Symmetric key generation algorithm using image-based chaos logistic maps
    Authors: Srinivas, K., Janaki, V.
    Journal: International Journal of Advanced Intelligence Paradigms 🧠
    Year: 2021

 

Sasank V.V.S | Computer Science | Best Researcher Award

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Assist Prof Dr. Sasank V.V.S | Computer Science | Best Researcher Award

K L University | India

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Early Academic Pursuits

Dr. Sasank V.V.S. exhibited a strong academic foundation from the outset. He completed his secondary education at Jassver English Medium School in 2007 with a First Class distinction, scoring 72.66%. He continued to excel in his Intermediate studies at Mega Junior College, graduating in 2009 with an 84.1% mark, also achieving First Class. His academic journey progressed to higher education at Gitam Institute of Technology, GITAM University, where he obtained his B.Tech in Information Technology in 2013 with a CGPA of 8.15, earning a Distinction. He further advanced his education with an M.Tech in Computer Science and Technology from the same institution, graduating in 2016 with a remarkable 9.11 CGPA, securing the top rank in his department. Dr. Sasank completed his Ph.D. at K.L. University in 2023, marking a significant milestone in his academic career.

Professional Endeavors

Dr. Sasank has a rich professional background in both academia and industry. He began his teaching career as a Teaching Assistant in the CSE Department at Gitam University from October 2015 to April 2016. He then served as an Assistant Professor at the Lendi Institute of Engineering & Technology, VIZIANAGARAM, from June 2016 to April 2017. Following this, he joined Anil Neerukonda Institute of Technology & Sciences (ANITS) as an Assistant Professor and Placement Officer from June 2017 to April 2019. He has been affiliated with K L University since July 2019, initially in the CSE Department and later in the CSIT Department, where he also served as the ERP Registration In-charge. His teaching repertoire includes subjects such as DBMS, Software Engineering, Computer Architecture & Organization, Term Paper, UI/UX Design, and DevOps.

Contributions and Research Focus

Dr. Sasank's research primarily focuses on advanced topics in computer science and engineering. His areas of interest include brain tumor classification, real-time traffic management using IoT and machine learning techniques, and the evolution of modern women in literature. He has published a significant number of papers in reputed journals, including  SCI papers and several Scopus-indexed articles. His notable publications include works on hybrid deep neural networks, automatic tumor growth prediction, and brain tumor classification using modified kernel-based softplus extreme learning machines. Additionally, he has guided numerous B.Tech and M.Tech project batches, contributing to the academic growth of his students.

Accolades and Recognition

Dr. Sasank has received several accolades for his academic and research achievements. He was the top ranker in his M.Tech program at Gitam University in 2016. He has published 18 papers, including SCI, Scopus, and WOS-indexed journals, and has contributed to two book chapters. His innovative research has led to the publication of two patents: one on real-time traffic management using IoT and machine learning techniques, and another on the evolution of modern women in Manju Kapur’s novels. Additionally, he has earned global certifications, including Google Associate Cloud Engineer and AWS Cloud Practitioner, and has presented his research at various international conferences.

Impact and Influence

Dr. Sasank's contributions to the field of computer science and engineering have had a significant impact on both academic and practical applications. His research on brain tumor classification and real-time traffic management has potential real-world implications, advancing the fields of medical imaging and smart city technologies. As an educator, he has influenced many students through his teaching and mentorship, guiding them in their academic and research endeavors.

Legacy and Future Contributions

Dr. Sasank's ongoing research and academic activities are expected to leave a lasting legacy in the field of computer science and engineering. His contributions to brain tumor classification and IoT-based traffic management are poised to influence future research and development in these areas. As he continues to publish and present his work, Dr. Sasank is likely to inspire and mentor the next generation of engineers and researchers, ensuring continued innovation and excellence in his field.

 

Notable Publications

Prostate cancer classification using adaptive swarm Intelligence based deep attention neural network 2024

Effective Segmentation and Brain Tumor Classification Using Sparse Bayesian ELM in MRI Images 2023

Hybrid deep neural network with adaptive rain optimizer algorithm for multi-grade brain tumor classification of MRI images 2022 (14)

An automatic tumour growth prediction based segmentation using full resolution convolutional network for brain tumour 2022 (27)

Hate Speech & Offensive Language Detection Using ML &NLP 2022 (4)