Andrea Tri Rian Dani | Statistics | Research Excellence Award

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Mr. Andrea Tri Rian Dani | Statistics  | Research Excellence Award

Statistics Study Program at Mulawarman University, Indonesia

Mr. Andrea Tri Rian Dani is an academic and lecturer at Mulawarman University since 2022, with a strong background in statistics. He is currently pursuing a Doctorate in Statistics (MIPA) at Airlangga University (2025–present), after completing his Master’s degree in Statistics at the Sepuluh Nopember Institute of Technology and his undergraduate degree in Statistics at Mulawarman University. Over the last five years, he has been actively involved in applied research and development projects with significant industry collaboration. His work includes the Samarinda City Price Monitoring Survey (2022–present) and the Strategic Food Price Information Center Survey (2022–present), both conducted in partnership with Bank Indonesia. Additionally, he contributed to the Survey of Public Reading Enthusiasm and Literacy Levels  in collaboration with the East Kalimantan Provincial Library, reflecting his engagement in data-driven policy support and socio-economic development initiatives.

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Featured Publications


Nonparametric Regression Mixed Estimators of Truncated Spline and Gaussian Kernel Based on CV, GCV, and UBR Methods

– International Journal on Advanced Science, Engineering and Information Technology, 2021

 

Kun He | Computer Science | Research Excellence Award

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Assoc Prof Dr. Kun He | Computer Science | Research Excellence Award 

Renmin University | China

Dr. Kun He is an accomplished computer scientist and currently serves as an Associate Professor at Renmin University of China (since January 2023). His academic journey reflects a strong foundation in theoretical computer science, backed by extensive research experience across leading Chinese institutions. Before joining Renmin University, he worked at the Institute of Computing Technology (ICT), Chinese Academy of Sciences (CAS), first as an Assistant Researcher (2021–2022) and later as an Associate Researcher (2022). He also completed a postdoctoral fellowship at Shenzhen University between 2019 and 2021. Dr. He earned his Ph.D. in Computer Science from ICT, CAS in 2019 under the supervision of Prof. Xiaoming Sun. He also holds a Master’s degree from ICT, CAS and a Bachelor of Engineering in Computer Science from Wuhan University. His research centers on the theory of computing, with particular emphasis on probabilistic methods, sampling algorithms, quantum computing, combinatorial structures, and theoretical machine learning. His work has significantly advanced algorithmic techniques related to the Lovász Local Lemma (LLL), Holant problems, and random constraint satisfaction. Over the years, Dr. He has received numerous prestigious awards recognizing the impact and quality of his research. These include the New Hundred Stars of ICT (2021), the Outstanding Doctoral Dissertation Award of the China Computer Federation (2020), the Special Award for the President of CAS (2019), and the National Scholarship of China (2018). These honors highlight his early and sustained contributions to theoretical computer science. Dr. He has published extensively in top-tier venues such as SODA, STOC, FOCS, ITCS, and Random Structures & Algorithms. His notable works include breakthroughs on the Moser–Tardos algorithm, deterministic counting versions of the Lovász Local Lemma, sampling solutions to random CNF formulas, and quantum extensions of classical combinatorial frameworks. Several of his papers have been widely cited and recognized, including a top-downloaded publication in Random Structures & Algorithms (2020). Recently, his research continues to push theoretical boundaries, with upcoming papers on the phase transition of the Sinkhorn–Knopp algorithm and efficient approximation schemes for Holant problems. Dr. He also actively works on emerging topics involving perfect sampling and permutation constraints within the Lopsided LLL regime, with multiple manuscripts currently under submission. With strong expertise, a prolific publication record, and multiple high-impact contributions, Dr. Kun He stands as a leading figure in modern theoretical computer science.

Profiles: Scopus | Google Scholar

Featured Publications

He, K., Li, L., Liu, X., Wang, Y., & Xia, M. (2025). Variable version Lovász Local Lemma: A tale of two boundaries. Information and Computation, 105386.

He, K. (2025). Phase transition of the Sinkhorn-Knopp algorithm. arXiv preprint arXiv:2507.09711.

He, K., Li, Z., Qiu, G., & Zhang, C. (2025). FPTAS for Holant problems with log-concave signatures. In Proceedings of the 2025 Annual ACM–SIAM Symposium on Discrete Algorithms (SODA).

He, K., Qiu, G., & Sun, X. (2024). Sampling permutations satisfying constraints within the lopsided local lemma regime. arXiv preprint arXiv:2411.02750.

He, K., Qiu, G., & Sun, X. (2024). Sampling permutations satisfying constraints within and beyond the local lemma regime. arXiv e-prints, arXiv:2411.02750.

He, K., Li, Q., & Sun, X. (2023). Moser-Tardos algorithm: Beyond Shearer’s bound. In Proceedings of the 2023 Annual ACM–SIAM Symposium on Discrete Algorithms (SODA).

He, K., Wang, C., & Yin, Y. (2023). Deterministic counting Lovász Local Lemma beyond linear programming. In Proceedings of the 2023 Annual ACM–SIAM Symposium on Discrete Algorithms (SODA).

He, K., Wu, K., & Yang, K. (2023). Improved bounds for sampling solutions of random CNF formulas. In Proceedings of the 2023 Annual ACM–SIAM Symposium on Discrete Algorithms (SODA).

He, K., Wang, C., & Yin, Y. (2022). Sampling Lovász Local Lemma for general constraint satisfaction solutions in near-linear time. In 2022 IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS).

Hafiz Muhammad Raza ur Rehman | Data Science | Best Researcher Award 

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Assist. Prof. Dr. Hafiz Muhammad Raza ur Rehman | Data Science | Best Researcher Award 

Assist. Prof. Dr. Hafiz Muhammad Raza ur Rehman | Yeungnam University | South Korea

Author Profiles

Scopus

Orcid

Google Scholar

Early Academic Pursuits

Dr. Hafiz Muhammad Raza ur Rehman began his academic journey with a strong foundation in information and communication engineering, culminating in a PhD from Yeungnam University, Korea. His doctoral research laid the groundwork for his later contributions in machine learning, multi-agent reinforcement learning (MARL), and data-science. His academic excellence and early engagement with algorithmic design and optimization established his trajectory as a dedicated researcher and educator in computational intelligence.

Professional Endeavors

Following his doctoral studies, Dr. Raza ur Rehman pursued a postdoctoral research position in Korea, focusing on sensor calibration for autonomous vehicles (AVs). Over 5.5 months, he conducted high-level interdisciplinary work aimed at improving the precision and reliability of AV sensor systems. He also gained substantial teaching experience 9 months as an Assistant Professor where he taught undergraduate and graduate courses in machine learning, deep learning, reinforcement learning, and data-science. In addition, his collaboration with the Electronics and Telecommunications Research Institute (ETRI), Korea, on a US Air Force–funded project, exemplified his ability to contribute to large-scale international research efforts.

Contributions and Research Focus

Dr. Raza ur Rehman’s research portfolio reflects a deep commitment to innovation and interdisciplinary integration. His primary focus areas include multi-agent reinforcement learning (MARL), autonomous vehicle systems, natural language processing (NLP), and optimization algorithms. He has authored a patent centered on MARL techniques and published several impactful journal and conference papers. Key publications include “QsOD: MARL-based QMIX with Grey Wolf Optimization” and “Prediction-Based Model for Chemical Compounds.” Moreover, he has presented research such as “Camera Calibration with CNN” at IEEE conferences and six additional papers at Korean academic venues. His current research extends to seven articles under review in internationally reputed journals, reinforcing his commitment to advancing data-science and intelligent systems.

Impact and Influence

Dr. Raza ur Rehman’s interdisciplinary research bridges theory and application spanning from algorithmic optimization to real-world technological integration. His MARL-related patent and publications contribute significantly to the growing body of knowledge in intelligent agent systems. By integrating data-science with advanced computational models, his work influences emerging fields such as autonomous navigation, machine learning-based control systems, and intelligent automation. As a mentor, he continues to inspire students through hands-on projects, fostering innovation and critical thinking in the next generation of engineers and researchers.

Academic Cites

His scholarly output includes publications in peer-reviewed international journals, conference presentations, and ongoing submissions to high-impact outlets. The QsOD study and the chemical compound prediction model have attracted interest in computational optimization and artificial intelligence research circles. His IEEE presentation on CNN-based camera calibration further strengthened his academic visibility and recognition within the AI research community.

Legacy and Future Contributions

Looking ahead, Dr. Hafiz Muhammad Raza ur Rehman aims to expand his research on multi-agent reinforcement learning, autonomous systems, and optimization-driven AI architectures. His future work is poised to contribute substantially to global research in data-science, particularly in developing adaptive, intelligent algorithms for complex real-world problems. Through continued teaching, mentorship, and publication, he aspires to leave a lasting legacy in both academia and applied research bridging the gap between theoretical innovation and practical technological advancement.

Featured Publications

Raza, S. N., ur Rehman, H. M., Lee, S. G., & Choi, G. S. (2019). Artificial intelligence-based camera calibration. 2019 15th International Wireless Communications & Mobile Computing Conference (IWCMC), 32. IEEE.

Nagulapati, V. M., ur Rehman, H. M. R., Haider, J., Qyyum, M. A., Choi, G. S., & Lim, H. (2022). Hybrid machine learning-based model for solubilities prediction of various gases in deep eutectic solvent for rigorous process design of hydrogen purification. Separation and Purification Technology, 298, 121651.

ur Rehman, H. M. R., On, B. W., Ningombam, D. D., Yi, S., & Choi, G. S. (2021). QSOD: Hybrid policy gradient for deep multi-agent reinforcement learning. IEEE Access, 9, 129728–129741.

ur Rehman, H. M. R., Saleem, M., Jhandir, M. Z., & Hafiz, H. G. I. A. (2025). Detecting hate in diversity: A survey of multilingual code-mixed image and video analysis. Journal of Big Data, 12(1), Article 5.

Younas, R., ur Rehman, H. M. R., Lee, I., On, B. W., Yi, S., & Choi, G. S. (2025). Sa-MARL: Novel self-attention-based multi-agent reinforcement learning with stochastic gradient descent. IEEE Access, 13, Article 5.

Khan, N. U., & ur Rehman, H. M. R. (2025). Real time signal decoding in closed loop brain computer interface for cognitive modulation. Ubiquitous Technology Journal, 1(1), 32–39.

ur Rehman, H. M. R., Haider, S. A., Faisal, H., Yoo, K. Y., Jhandir, M. Z., & Choi, G. S. (2025). A novel framework for Saraiki script recognition using advanced machine learning models (YOLOv8 and CNN). IEEE Access, 13, Article 2.

Hussein Alabdally | Computer Science | Best Researcher Award

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Mr. Hussein Alabdally | Computer Science | Best Researcher Award

Mr. Hussein Alabdally | University of Southern Queensland | Australia

Mr. Hussein Alabdally is a talented computer scientist, software engineer, and telecommunications specialist with diverse professional expertise spanning Australia and Iraq. With a foundation in mathematics, web development, and programming, he has contributed significantly to education, technology, and translation services. Hussein’s journey reflects his adaptability and passion for learning, from tutoring students in mathematics and English to working in IT, telecommunications, and software engineering roles. His bilingual communication skills in English and Arabic have enabled him to serve communities as an interpreter and translator, while his technical creativity continues to drive his work in coding, software design, and network systems.

Profiles

Scopus
Google Scholar

Education

Mr. Hussein’s educational path is marked by academic excellence in mathematics, computer science, and engineering studies. He earned his Bachelor of Science degree in Toowoomba, Australia, achieving outstanding results in advanced courses including operations research, numerical computing, experimental design, and web technologies. His solid foundation in mathematics and computing equipped him with analytical and problem-solving skills crucial for tackling real-world technical challenges. Alongside formal studies, he pursued professional training in web development and programming, mastering coding languages such as HTML, CSS, Python, JavaScript, and C++. Hussein also gained practical experience in website design and database management, complementing his academic knowledge with hands-on projects.

Experience

Mr. Hussein’s professional experience covers a wide range of roles across education, IT, translation, and engineering. He worked as a website developer with leading companies in Toowoomba, building digital platforms and enhancing user experience. His teaching journey as an English and mathematics tutor demonstrated his ability to simplify complex concepts for students, helping many succeed in academic pursuits. Hussein’s bilingual expertise was recognized in his work as an interpreter, supporting communication in medical, legal, and educational contexts. Transitioning into engineering roles, he contributed as an IT specialist at Dar Al-Auloom Private High School and later advanced to software engineering and telecommunications positions in Kirkuk. His diverse portfolio reflects both technical mastery and cultural adaptability.

Research Interests

Mr. Hussein’s research interests are deeply rooted in the intersection of mathematics, programming, and technology innovation. He is passionate about computational methods, web technologies, and advanced applications of mathematical modeling in computer engineering. His curiosity extends to artificial intelligence, game programming, and database systems, where he enjoys creating applications that merge creativity with technical precision. Hussein is particularly enthusiastic about designing intelligent software solutions, including document readers and chess games with AI capabilities. He also explores optimization techniques and performance computing, driven by a desire to apply theoretical knowledge to practical systems. His long-term vision is to bridge mathematics with next-generation software solutions.

Awards

Mr. Hussein’s achievements highlight his academic dedication and community engagement. He earned recognition in national and international competitions, including the Australian Statistics Competition, where he won the Queensland prize. He also secured credits in the UNSW ICAS Science and Mathematics contests, demonstrating excellence across STEM disciplines. At the University of Southern Queensland, he was actively involved in science and engineering challenges, achieving commendable rankings. Beyond academics, Hussein received awards for both academic excellence and school community participation, showcasing his commitment to leadership and service. These honors underline his consistent performance, strong analytical skills, and ability to contribute meaningfully both inside and outside the classroom.

Publication Top Notes

Empirical curvelet transform based deep DenseNet model to predict NDVI using RGB drone imagery data
Journal: Computers and Electronics in Agriculture, 
Authors: M. Diykh, M. Ali, M. Jamei, S. Abdulla, M.P. Uddin, A.A. Farooque, A.H. Labban, H. Alabdally, et al.

Improving Dry-Bulb Air Temperature Prediction Using a Hybrid Model Integrating Genetic Algorithms with a Fourier–Bessel Series Expansion-Based LSTM Model
Journal: Forecasting, 
Authors: H. Alabdally, M. Ali, M. Diykh, R.C. Deo, A.A. Aldhafeeri, S. Abdulla, et al.

ECT-DLM: Deep Learning Based Empirical Curvelet Transform Approach for Thoracic Disease Diagnosis from X-RAY Images
Conference: ICTIS
Authors: S. Abdulla, S.K. Alkhafaji, H. Marhoon, M. Diykh, M.A. Majed, J. Sadiq, H. Alabdally, et al.

Physical Human Activity Recognition Based on Spectral Graph Wavelet Transforms Integrated with Machine Learning Model
Conference: International Conference on Health Information Science,
Authors: S. Abdulla, A.S. Majeed, A.B. Al-Khafaji, W. Alsalman, M. Diykh, A. Sahi, H. Alabdally, et al.

Robust Approach for Human Activity Recognition Using Decomposing Technique Based Machine Learning Models
Conference: International Conference on Health Information Science,
Authors: S.Z. Hmoud, M. Diykh, S. Abdulla, H. Alabdally, A. Sahi

Conclusion

Mr. Hussein Alabdally represents a professional who blends education, technical skill, and cultural versatility. His journey reflects resilience, adaptability, and a deep passion for mathematics and technology. Whether teaching students, translating across languages, or designing digital systems, Hussein demonstrates excellence in every role he undertakes. His dual citizenship in Australia and Iraq positions him as a global professional with a multicultural perspective. With his diverse experience in tutoring, web development, software engineering, and telecommunications, Hussein continues to grow as a researcher and practitioner in the field of computer science. His career trajectory shows promise for future contributions to both academia and industry.

Sumit Kumar | Data Science | Young Scientist Award

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🌟Dr. Sumit Kumar, Data Science, Young Scientist Award🏆

Doctorate at Banshal Alliance University, India

Dr. Sumit Kumar Banshal, a Bangladeshi national, is an Assistant Professor in the Department of Computer Science & Engineering at Alliance University, Bangalore, India. With a PhD in Computer Science from South Asian University, New Delhi, India, Sumit has a strong foundation in academia and research. He is fluent in Bengali, English, Hindi, and Marwari. Sumit’s academic journey has seen him hold various teaching and research positions, including stints as an Assistant Professor and Senior Lecturer at Daffodil International University in Dhaka, Bangladesh. His research interests lie in altmetrics, scientometrics, information retrieval, and text mining.

Author Metrics

Google Scholar Profile

Scopus Profile

ORCID Profile

Dr. Sumit Kumar Banshal has made significant contributions to the field of computer science, with notable metrics reflecting his impact. He has published 32 papers indexed in Scopus, accumulating over 330 citations and achieving an h-index of 12. Additionally, Sumit is actively involved in the academic community, serving as an associate editor and reviewer for prestigious journals and conferences.

Sumit’s impact and productivity as a researcher. Citations reflect how often his work has been referenced by other researchers, while the h-index measures both the productivity and impact of his published work. The i10-index indicates the number of publications with at least 10 citations. While there’s a slight decrease in metrics since 2019, Sumit’s overall career metrics demonstrate a strong and impactful research profile.

Education

Sumit completed his PhD in Computer Science from South Asian University, New Delhi, India, with a thesis titled “An Analysis of Metrics for Scholarly Articles Derived from Bibliometric and Social Media Data.” Prior to this, he earned his MSc in Computer Science from the same institution. Sumit’s educational journey also includes a BSc (Hons.) in Information & Communication Engineering from the University of Rajshahi, Bangladesh.

Research Focus

Dr. Sumit Kumar Banshal’s research primarily focuses on altmetrics, scientometrics, information retrieval, and text mining. His doctoral thesis analyzed scholarly data using traditional bibliometric methods and social media metrics, aiming to understand the relationship between conventional impact assessments and social media impact assessments. Sumit’s expertise lies in exploring credible factors for higher social media mentions about scholarly data and developing integrated tools for automated social media mention analysis.

Professional Journey

Sumit’s professional journey includes academic positions such as Assistant Professor and Senior Lecturer at Daffodil International University, Dhaka, Bangladesh, and his current role as Assistant Professor at Alliance University, Bangalore, India. He has also served as a teaching assistant and senior software developer, gaining experience in both academia and industry. Sumit’s diverse roles have contributed to his expertise in areas like data mining, web engineering, and database management systems.

Honors & Awards

Throughout his career, Dr. Sumit Kumar Banshal has received recognition for his academic achievements. He has been awarded travel support for attending prestigious international conferences and workshops, including the INTERNATIONAL CONFERENCE ON SCIENTOMETRICS & INFORMETRICS and the Indo-German Workshop on Information Retrieval, Informetrics & Scientometrics. Sumit has also received fellowships, scholarships, and merit awards in recognition of his research and academic excellence.

Publications Noted & Contributions

Sumit has made significant contributions to the academic literature, with notable publications presented at international conferences and workshops. His research papers cover diverse topics such as sentiment classification, altmetrics, research competitiveness analysis, and characterization of research performance. Sumit’s work has been well-received and cited by peers, contributing to the advancement of knowledge in his field.

Scientometric mapping of research on ‘Big Data’

Cited By: 57

Year: 2015

Designing a Composite Index for research performance evaluation at the national or regional level: ranking Central Universities in India

Cited By: 43

Year: 2016

Research performance of Indian institutes of technology

Cited By: 40

Year: 2017

Quantifying global digital journalism research: a bibliometric landscape

Cited By: 36

Year: 2022

Research performance of central universities in India

Cited By: 34

Year: 2017

Research Timeline

Sumit’s research timeline reflects a progressive journey from his undergraduate studies to his doctoral research and beyond. He began his research journey as a senior software developer, transitioning to roles as a teaching assistant, doctoral research scholar, and ultimately an assistant professor. Along this journey, Sumit has conducted research on various topics, leading to publications, presentations, and collaborations with colleagues and institutions worldwide.

Collaborations and Projects

Dr. Sumit Kumar Banshal has collaborated with researchers and institutions globally on projects related to his research interests. His collaborations have resulted in joint publications, workshops, and conference presentations. Sumit has also supervised master’s and bachelor’s projects, fostering research skills and mentorship among students. His collaborative projects have contributed to the advancement of knowledge and innovation in the field of computer science.