Arifur Rahman | Machine Learning | Best Researcher Award

Arifur Rahman | Machine Learning | Best Researcher Award

Mr. Arifur Rahman, NAGAD Digital Financial Service, Bangladesh

Arifur Rahman ๐ŸŽ“ is a passionate researcher and software engineer from Bangladesh ๐Ÿ‡ง๐Ÿ‡ฉ, specializing in Machine Learning ๐Ÿค–, Deep Learning ๐Ÿง , NLP ๐Ÿ“š, and Bioinformatics ๐Ÿงฌ. A graduate of KUET in Computer Science and Engineering ๐Ÿ’ป, he has excelled in both academia and industry. Currently, he serves as a Full Stack Developer ๐Ÿง‘โ€๐Ÿ’ป at NAGAD Digital Financial Service, contributing to innovative supply chain projects. Arifur is also an active researcher with several IEEE and Elsevier publications ๐Ÿ“, and has earned recognition in programming contests ๐Ÿ†. His dedication to applied AI and system development showcases a unique blend of technical and research excellence ๐Ÿš€.

๐ŸŒย Professional Profile

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๐ŸŽ“ Education

  • ๐ŸŽ“ B.Sc. in Computer Science and Engineering, KUET (2018 โ€“ 2023)

    • ๐Ÿ“Š CGPA: 3.35/4.00; Final Two Years CGPA: 3.73/4.00

  • ๐Ÿซ Noakhali Govt. College (2015 โ€“ 2017)

    • ๐ŸŒŸ GPA: 5.00/5.00 (Cumilla Board Scholarship Winner)

๐Ÿ‘จโ€๐Ÿ’ผ Experience

  • ๐Ÿง‘โ€๐Ÿ’ป Software Engineer, NAGAD Digital Financial Service (Feb 2024 โ€“ Present)

    • ๐Ÿ’ผ Full Stack Developer in PRISM (Supply Chain Management) using Flutter, Java Spring Boot, PHP

  • ๐Ÿ”ฌ Research Engineer (NLP), AIMS Lab, United International University (Oct 2023 โ€“ Feb 2024)

    • ๐Ÿ“š Worked on Recommender Systems and published in IEEE Access

  • ๐Ÿ‘จโ€๐Ÿ’ป Software Engineer, Nazihar IT Solution Ltd. (May 2023 โ€“ Sep 2023)

    • ๐Ÿ’ป Developed subroutines using Temenos Java Framework for banking solutions

๐Ÿ† Suitability for Best Researcher Award

Mr. Arifur Rahman is an exceptional candidate for the Best Researcher Award, demonstrating strong potential and proven excellence in research and innovation across emerging domains such as Machine Learning, Deep Learning, Natural Language Processing (NLP), Health Informatics, and Biomedical Engineering. His impactful research, hands-on development skills, and academic contributions distinguish him as a rising leader in computational science and applied AI.

๐Ÿ”น Professional Developmentย 

Arifur Rahman ๐Ÿš€ is actively involved in both industry-driven software engineering and cutting-edge academic research ๐Ÿ“–. His journey has been marked by continuous professional growth, serving in roles that merge development and innovation ๐Ÿ’ผ. At NAGAD, he contributes as a Full Stack Developer ๐ŸŒ, while his time at AIMS Lab sharpened his NLP and recommender system expertise ๐Ÿง . He has also contributed as a reviewer in IEEE conferences ๐Ÿ“‘, showcasing his engagement with the global research community. Arifurโ€™s hands-on experience with technologies like Flutter, Java Spring Boot, ReactJS, and blockchain ๐Ÿ”— highlights his dynamic skill set and commitment to excellence โญ.

๐Ÿ” Research Focus

Arifur Rahmanโ€™s research focuses on a diverse range of AI-powered technologies ๐Ÿง , with core interests in Machine Learning, Deep Learning, and Natural Language Processing ๐Ÿค–๐Ÿ“š. His work explores real-world applications such as health informatics ๐Ÿฅ, bioinformatics ๐Ÿงฌ, fake news detection, and blockchain security ๐Ÿ”. Through his IEEE and Elsevier publications, he has addressed critical problems in diabetic retinopathy diagnosis, DNA sequence classification, and higher education recommendation systems ๐ŸŽ“. His blend of theoretical innovation and practical solutions ensures his research contributes to both scientific progress and societal impact ๐ŸŒ.

๐Ÿ… Awards and Honors

  • ๐ŸŽ–๏ธ Deanโ€™s List Award at KUET for outstanding academic performance (2019โ€“2020)

  • ๐Ÿฅ‡ Intra-KUET Programming Contest 2021 โ€“ 3rd Place ๐Ÿง ๐Ÿ’ก

  • ๐Ÿฅˆ Intra-KUET Programming Contest 2019 โ€“ 6th Place ๐Ÿง 

  • ๐Ÿฅ‰ Divine IT Qualification Round โ€“ Rank 10 (Nov 2023) ๐Ÿ’ป

  • ๐Ÿ† TechnoNext Technical Coding Test 2023 (Fresher) โ€“ Rank 7 ๐Ÿ”ข

๐Ÿ“Š Publication Top Notes

  1. Recommender system in academic choices of higher education โ€“ IEEE Access (2024) ๐Ÿ“š5 ๐ŸŽ“๐Ÿค–
  2. Advancements in breast cancer diagnosis… with PCA, VIF โ€“ 6th Int. Conf. on Electrical Engineering and Info (2024) ๐Ÿ“š2 ๐Ÿงฌ๐Ÿฉบ๐Ÿ“Š
  3. Optimizing SMS Spam Detection… Voting Ensembles & Bi-LSTM โ€“ 5th Int. Conf. on Data Intelligence and Cognitive (2024) ๐Ÿ“š1 ๐Ÿ“ฑ๐Ÿ“ฉ๐Ÿง 
  4. Cracking the Genetic Codes: DNA Sequence Classification… โ€“ Int. Conf. on Advances in Computing, Communication (2024) ๐Ÿ“š1 ๐Ÿงฌ๐Ÿงช๐Ÿง 
  5. Secure Land Purchasing using… Multi-Party Skyline Queries โ€“ 26th Int. Conf. on Computer and Info Tech (2023) ๐Ÿ“š1 ๐ŸŒ๐Ÿ ๐Ÿ”
  6. Fake News Detection… Soft and Hard Voting Ensemble โ€“ Procedia Computer Science (2025) ๐Ÿ“šโ€“ ๐Ÿ“ฐโŒ๐Ÿ—ณ๏ธ

Prof. Dr. Dongxing Song | Machine Learning | Best Researcher Award-3904

Prof. Dr. Dongxing Song | Machine Learning | Best Researcher Award

Prof. Dr. Dongxing Song, Zhengzhou University, China

Prof. Dr. Dongxing Song is an innovative researcher in power engineering and thermophysics, currently serving as a Research Fellow at Zhengzhou Universityโ€™s School of Mechanics and Safety Engineering. He earned his doctoral degree from Tsinghua University and previously studied at Xiโ€™an Jiaotong University and Central South University. His expertise lies in nanofluid dynamics, ionic thermoelectric conversion, and energy system optimization. Dr. Songโ€™s research integrates machine learning with thermodynamics, pushing boundaries in sustainable energy technologies. His work has been published in top-tier journals such as Joule and Cell Reports Physical Science, gaining recognition for both originality and technical depth. Driven by scientific rigor and curiosity, Dr. Song continues to shape future solutions for clean energy and advanced material systems. โš›๏ธ๐Ÿ”ฌ๐ŸŒฑ

๐ŸŒย Professional Profileย 

Orcid

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๐Ÿ† Suitability for Best Researcher Awardย 

Prof. Dr. Dongxing Song is a standout candidate for the Best Researcher Award due to his cutting-edge work in ionic thermoelectric energy conversion and nanoscale heat transfer. His publications in high-impact journals, including Joule and Cell Reports Physical Science, demonstrate his role in shaping the future of clean and efficient energy generation. Dr. Song has independently led national-level research projects supported by the NSFC and China Postdoctoral Science Foundation, focusing on ion-electron coupling mechanisms and dynamic heat-mass transport. His interdisciplinary approachโ€”blending thermophysics, machine learning, and materials scienceโ€”makes him a trailblazer in green energy innovation. His research not only advances scientific understanding but also offers scalable solutions for low-grade waste heat recovery. ๐Ÿ”‹๐Ÿ…๐ŸŒ

๐ŸŽ“ Education

Prof. Dr. Dongxing Song holds a robust academic background in power engineering and thermophysics. He completed his Ph.D. at Tsinghua University (2018โ€“2022) under Prof. Weigang Ma, following his Masterโ€™s studies at Xiโ€™an Jiaotong University (2015โ€“2018) under Prof. Dengwei Jing. His foundational education in Thermal Energy and Power Engineering was completed at Central South University (2011โ€“2015), where he was mentored by Dengwei Jing and Jianzhi Zhang. Throughout his academic journey, Dr. Song developed deep expertise in energy conversion, ionic transport, and thermodynamic modeling. His cross-institutional training at Chinaโ€™s most prestigious engineering schools laid the groundwork for his innovative and interdisciplinary research in the clean energy domain. ๐ŸŽ“๐Ÿ“˜โš™๏ธ

๐Ÿ’ผ Experience

Since February 2022, Dr. Dongxing Song has served as a Research Fellow at the School of Mechanics and Safety Engineering, Zhengzhou University, contributing significantly to ionic thermoelectric research. He previously pursued advanced research at Tsinghua University, one of Chinaโ€™s top engineering institutions, from 2018 to 2022. His earlier academic appointments include graduate research at Xiโ€™an Jiaotong University and Central South University, where he gained hands-on experience in power engineering, energy optimization, and thermophysical modeling. In every role, Dr. Song has demonstrated scientific leadership, managing national-level projects and publishing influential research. His experience reflects a well-rounded career rooted in high-impact research and technological innovation in sustainable energy. ๐Ÿง‘โ€๐Ÿ”ฌ๐Ÿ”‹๐Ÿ“ˆ

๐Ÿ… Awards and Honors

Prof. Dr. Dongxing Song has received prestigious grants and recognition from leading national institutions. He is the Principal Investigator of a National Natural Science Foundation of China (NSFC) Original Exploration Program Project, as well as multiple China Postdoctoral Science Foundation awards, including the Innovative Talents Grant (BX20220275). His work on ion thermoelectric conversion received a high recommendation from Joule Preview, marking him as a rising star in energy systems innovation. Dr. Songโ€™s publications in top-impact journals and his ability to secure competitive funding reflect his academic excellence and research potential. These accolades highlight his position as a thought leader in the next generation of thermophysical science and energy innovation. ๐Ÿฅ‡๐Ÿ›๏ธ๐Ÿ“š

๐Ÿ”ฌ Research Focus

Dr. Dongxing Song’s research centers on the optimization of power generation systems for low-grade waste heat recovery, specifically using ion thermoelectric conversion and salt gradient power. He investigates the fundamental coupling between heat and ion transport and has derived a new expression for the ionic Seebeck coefficient, setting the stage for thermoelectric optimization. His studies also integrate nanofluidic heat transfer, solid-state ion battery transport, and machine learning to enhance the performance of sustainable energy devices. His broader focus includes nanoscale heat and mass transfer, where he explores transport mechanisms across interfaces using simulation and experimental validation. Dr. Songโ€™s pioneering models are helping redefine energy recovery systems with enhanced efficiency and low environmental impact. ๐Ÿ”ฌโ™ป๏ธ๐Ÿงช

๐Ÿ“Šย Publication Top Notes

  • Design of Microchannel Heat Sink with Wavy Channel and Its Time-Efficient Optimization with Combined RSM and FVM Methods

    • Citations: 209
    • Year: 2016

  • Optimization of a Circular-Wavy Cavity Filled by Nanofluid under Natural Convection Heat Transfer

    • Citations: 194
    • Year: 2016

  • Optimization of a Lid-Driven T-Shaped Porous Cavity to Improve the Nanofluids Mixed Convection Heat Transfer

    • Citations: 138
    • Year: 2017

  • Prediction of Hydrodynamic and Optical Properties of TiOโ‚‚/Water Suspension Considering Particle Size Distribution

    • Citations: 87
    • Year: 2016

  • A Nitrogenous Pre-Intercalation Strategy for the Synthesis of Nitrogen-Doped Tiโ‚ƒCโ‚‚Tโ‚“ MXene with Enhanced Electrochemical Capacitance

    • Citations: 71
    • Year: 2021