Jaehyun Chung| Computer Science and Artificial Intelligence | Best Researcher Award

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Mr. Jaehyun Chung| Computer Science and Artificial Intelligence | Best Researcher Award

Computer Science and Artificial Intelligence | Korea University | South Korea

Jaehyun Chung is a highly promising M.S. student at Korea University’s Artificial Intelligence and Mobility Laboratory, specializing in Generative AI, Reinforcement Learning, and Quantum AI applications. His research focuses on autonomous systems, AI-based mobility, defense technologies, and intelligent control, reflected in his involvement in over ten major R&D projects funded by prestigious Korean institutions. He has co-authored several high-impact journal articles and conference papers, including works published or under review in IEEE Transactions and ACM venues, and has earned multiple student paper awards, such as the IEEE Seoul Section Bronze Paper Award. Jaehyun demonstrates strong interdisciplinary capability, applying advanced AI techniques to fields as diverse as torpedo evasion, space rocket stabilization, and stock market prediction. Although early in his academic career, his rapid research output, national recognition, and contributions to innovative, real-world AI applications position him as an outstanding young researcher with exceptional potential for future impact.

Professional Profile 

Educational 

Jaehyun Chung pursued both his undergraduate and graduate studies at Korea University, one of South Korea’s leading institutions. He earned his Bachelor of Science (B.S.) in Electrical and Computer Engineering from the College of Engineering, completing the program between March 2017 and August 2023. Following his undergraduate success, he continued at Korea University to pursue a Master of Science (M.S.) in Electrical and Computer Engineering, starting in September 2023, where he is currently engaged in advanced research in Artificial Intelligence and Mobility. His academic path reflects a strong and consistent focus on engineering and cutting-edge AI technologies.

Professional Experience 

Jaehyun Chung is currently serving as a Research Assistant at the Artificial Intelligence and Mobility Laboratory at Korea University since September 2023, under the guidance of Professor Joongheon Kim. In this role, he actively contributes to a wide range of advanced R&D projects focused on AI-based autonomous systems, reinforcement learning, and quantum AI technologies. His professional experience includes hands-on involvement in nationally funded initiatives such as the Quantum Hyper-Driving Project, AI Bots Collaborative Platform, and Learning-Based Swarm Mission Planning Algorithms, among others. Jaehyun’s work spans across various sectors including defense, mobility, construction, and education, highlighting his ability to apply AI innovations to real-world challenges through practical, cross-disciplinary research collaborations.

Research Interests 

Jaehyun Chung’s research interests lie at the intersection of Artificial Intelligence, Autonomous Systems, and Quantum Computing. He is particularly focused on Generative AI technologies, including Transformer-based architectures, and their application in dynamic environments. A key area of his work involves AI-based Autonomous Control, where he utilizes advanced Reinforcement Learning techniques to optimize decision-making in systems such as autonomous vehicles, robotic platforms, and defense mechanisms. Additionally, his growing involvement in Quantum Reinforcement Learning and Federated Learning reflects a forward-looking approach to building scalable and intelligent systems. His research is deeply interdisciplinary, targeting real-world problems in mobility, finance, aerospace, and military applications through the lens of cutting-edge AI innovation.

Awards and Honors 

Jaehyun Chung has received several prestigious awards recognizing his innovation and excellence in research at an early stage in his academic career. In December 2024, he was honored with the IEEE Seoul Section Best Student Bronze Paper Award for his impactful work on stock prediction using correlation graph-based proximal policy optimization. In November 2024, he received the Outstanding Paper Award from the Korean Institute of Communications and Information Sciences (KICS) for his research on reinforcement learning-based countermeasure tactics against torpedo threats. Additionally, he earned another Bronze Paper Award at the IEEE Seoul Section Student Paper Contest in December 2023 for developing reinforcement learning strategies for aircraft taxi routing. These accolades reflect Jaehyun’s strong analytical skills, innovative thinking, and significant contributions to the fields of AI and autonomous control.

 Publications 

Title: Joint Quantum Reinforcement Learning and Stabilized Control for Spatio-Temporal Coordination in Metaverse
Authors: S. Park, J. Chung, C. Park, S. Jung, M. Choi, S. Cho, J. Kim
Year: 2024
Cited by: 19

Title: Realizing Stabilized Landing for Computation-Limited Reusable Rockets: A Quantum Reinforcement Learning Approach
Year: 2024
Cited by: 17

Title: Quantum Multi-Agent Reinforcement Learning for Cooperative Mobile Access in Space-Air-Ground Integrated Networks
Authors: G. S. Kim, Y. Cho, J. Chung, S. Park, S. Jung, Z. Han, J. Kim
Year: 2024
Cited by: 4

Title: DDPG-based Deep Reinforcement Learning Tactics for Defending Torpedo Attacks
Authors: J. Chung, C. Im, J. Choi, Y. Yoon, S. Park
Year: 2024
Cited by: 1

Title: Correlation-Assisted Spatio-Temporal Reinforcement Learning for Stock Revenue Maximization
Year: 2025

Title: Multi-Modal LLM-Based Fully-Automated Training Dataset Generation Software Platform for Mathematics Education
Year: 2025

Title: Trends in Reinforcement Learning Methods for Stock Prediction
Year: 2024

Conclusion 

Jaehyun Chung is an exceptionally strong early-career researcher who demonstrates intellectual depth, research versatility, and practical relevance across AI domains. He possesses all the qualities sought in a Best Researcher Award.

Anuradha Choudhury | Computer Science and Artificial Intelligence | Women Researcher Award

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Ms. Anuradha Choudhury | Computer Science and Artificial Intelligence | Women Researcher Award

Student at OUTR, india

Anuradha Rani Choudhury is a dedicated and aspiring researcher currently pursuing her Master of Technology at OUTR, Bhubaneswar, with an impressive CGPA of 9.20. She holds a Bachelor’s degree in Technology from ITER, Bhubaneswar, and has demonstrated strong technical acumen through impactful projects in machine learning, including sentiment analysis and disease prediction models, both achieving high accuracy. With certifications in machine learning, web development, and Android development, she exhibits a strong foundation in diverse technological domains. Anuradha has actively participated in seminars and workshops, showcasing her commitment to continuous learning. Her proficiency in programming languages such as Python, Java, and C, along with web technologies, complements her research skills. Additionally, her involvement in extracurricular activities like sports, NCC, and student leadership reflects a well-rounded personality. While she is at an early stage in her research journey, Anuradha shows promising potential for future contributions to the field of technology and applied sciences.

Professional Profile 

🎓 Education of Anuradha Rani Choudhury

Anuradha Rani Choudhury has built a strong academic foundation in the field of technology and engineering. She is currently pursuing her Master of Technology (M.Tech) at Odisha University of Technology and Research (OUTR), Bhubaneswar, maintaining an excellent CGPA of 9.20 (2023–2025). She previously earned her Bachelor of Technology (B.Tech) from ITER, Bhubaneswar, graduating with a CGPA of 7.73 in 2022. Her earlier academic journey includes completing 12th grade (Science) from Stewart Science College, Cuttack under the CHSE Board, scoring 57.5%, and her 10th grade from D.A.V. Public School, Berhampur under the CBSE Board, where she achieved a commendable 83.6%. Her academic progression highlights her consistent dedication and growth in technical education.

💼 Professional Experience of Anuradha Rani Choudhury

Anuradha Rani Choudhury has gained valuable hands-on experience through academic projects and certified training programs in the fields of machine learning, data science, and software development. She successfully led a Sentiment Analysis project in 2024, where she implemented advanced models such as Naïve Bayes, Logistic Regression, SVM, and Neural Networks, achieving an outstanding . In 2023, she developed a Disease Prediction Model using patient physiological data, which delivered an impressive . Additionally, Anuradha has completed certification-based training in Machine Learning (Project Mantra), Web Development (Verzeo), and Android Development (Pixaflip Technologies). Her participation in workshops and seminars, along with her technical proficiency in languages like Python, Java, and SQL, further reflects her readiness for research and real-world problem-solving in the tech industry.

🔬 Research Interest of Anuradha Rani Choudhury

Anuradha Rani Choudhury’s research interests lie primarily in the dynamic fields of Machine Learning, Artificial Intelligence, and Data Science, with a strong inclination toward applying these technologies in healthcare and human-centered applications. She is passionate about exploring predictive modeling, sentiment analysis, and disease diagnosis systems that leverage advanced algorithms to generate actionable insights from complex data. Her academic projects reflect her enthusiasm for building intelligent systems capable of improving decision-making and automation. Anuradha is also interested in the integration of deep learning and neural networks to enhance model accuracy and efficiency. As she progresses in her academic and professional journey, she aims to contribute to impactful, real-world solutions through innovative and ethically grounded research in intelligent technologies.

🏅 Awards and Honors of Anuradha Rani Choudhury

Anuradha Rani Choudhury has been recognized for her diverse talents and active participation in both academic and extracurricular arenas. She earned the 2nd prize in poem writing at the Ganjam Kalaparishad in 2017, showcasing her creative expression and literary flair. In the same year, she also secured the 2nd prize in athletics at D.A.V. Public School, reflecting her athletic spirit and commitment to physical excellence. Additionally, she holds the prestigious NCC “A” Certificate (2013–2015), highlighting her discipline, leadership, and dedication to national service. These honors demonstrate her well-rounded personality, balancing academic rigor with artistic and physical achievements.

Conclusion

Anuradha Rani Choudhury is a promising emerging researcher with a solid academic background, project experience in machine learning, and proactive engagement in technical skill development. However, to be highly competitive for the Best Researcher Award, particularly at national or international levels, she would benefit from Publishing research papers. Involving in long-term, original research with measurable impact. Demonstrating broader research influence and leadership.

📚 Publications Top Noted

  1. Title: Real-time Face Mask Detection in Nuclear Power Plants: A Deep Learning Framework Using Hybrid CNN-MobileNetV2 Architecture
    Authors: S.R. Panda, A.R. Choudhury, A.K. Mishra, S. Mohanty, S. Mishra
    Year: 2025
    Citation: 0
    Published In: Intelligent Computing Techniques and Applications, pp. 87–91

  2. Title: A Comparative Analysis of Deep Learning Techniques for Face Mask Detection System in Nuclear Power Plant
    Authors: S.R. Panda, A.R. Choudhury, A.K. Mishra
    Year: 2025
    Citation: 0
    Published In: 2025 10th International Conference on Signal Processing and Communication

  3. Title: Enhancing Lung Cancer Detection by Leveraging Machine Learning Algorithms
    Authors: A.R. Choudhury, S.R. Panda, A.K. Mishra, J. Routray
    Year: 2025
    Citation: 0
    Published In: 2025 10th International Conference on Signal Processing and Communication

  4. Title: Deep Learning Based Automated Lung Cancer Detection from CT Scan Leveraging Transfer Learning
    Authors: A.R. Choudhury, J. Rautray, P. Mishra, M. Kandpal, S.S. Dalai
    Year: 2025
    Citation: 0
    Published In: Procedia Computer Science, Volume 258, Pages 2748–2759

  5. Title: Face Mask Detection System for Safety Assurance in Nuclear Power Facilities from Harmful and Hazardous Substance Using Convolutional Neural Network and Image Processing
    Authors: S.R. Panda, A.R. Choudhury, A.K. Mishra
    Year: 2025
    Citation: 0
    Published In: International Journal of Computer Applications 975, 8887

 

 

 

 

 

 

Maksym Koghut | Computer Science and Artificial Intelligence | United Kingdom

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Dr. Maksym Koghut | Computer Science and Artificial Intelligence | United Kingdom

Lecturer at Manchester Metropolitan University, United Kingdom

Dr. Maksym Koghut is an accomplished academic and researcher at Manchester Metropolitan University Business School, UK, with a robust interdisciplinary background spanning management, engineering, and financial sciences. He holds a PhD in Management from the University of Kent and has taught at several leading UK institutions, delivering modules in digital transformation, blockchain, strategy, and innovation. His research focuses on the strategic implications of digital technologies, inter-organisational trust, and AI in business contexts, with publications in high-quality journals and presentations at prominent international conferences. In addition to his academic credentials, Dr. Koghut brings substantial industry experience through leadership roles in multiple startups across the UK and Ukraine. He is a Fellow of the Higher Education Academy and has been recognized with several academic and teaching awards, reflecting his excellence in both research and pedagogy.

Professional Profile 

🎓 Education of Dr. Maksym Koghut

Dr. Maksym Koghut has pursued a dynamic and interdisciplinary educational journey across the UK and Ukraine. He earned his PhD in Management from the University of Kent (2018–2021), where he developed a strong foundation in strategic management and digital transformation. Prior to that, he completed a BA (Hons) in Business Information Management at the University of Huddersfield (2014–2017), and a BA (Hons) in Financial Management from the Inter-Regional Academy of Personnel Management, Ukraine (2010–2012), highlighting his grounding in both information systems and finance. His academic path began with a BEng (Hons) in Mechanical Engineering from Cherkassy Engineering and Technological Institute, Ukraine (1995–2000), demonstrating a solid technical and analytical base. This unique combination of disciplines enhances his expertise in digital business, innovation, and organizational strategy.

💼 Professional Experience of Dr. Maksym Koghut

Dr. Maksym Koghut brings a wealth of professional experience that bridges academia and industry. He is currently a Lecturer at Manchester Metropolitan University Business School, where he leads and teaches postgraduate and degree apprenticeship modules focused on blockchain, digital transformation, and Industry 4.0. His previous academic roles include lecturing positions at Coventry University London, the University of Kent, and the University of Huddersfield, where he developed and led modules in strategic management, digital information systems, innovation, and entrepreneurship. Beyond academia, Dr. Koghut has a strong entrepreneurial background, having founded and directed several businesses in the UK and Ukraine, including Script Software Ltd (a robotics software company), MotorHood Platform Ltd, and other ventures in automotive services, photography, and industrial equipment. This dual experience in research and real-world business operations uniquely positions him as a thought leader in digital enterprise and innovation.

🔬 Research Interests of Dr. Maksym Koghut

Dr. Maksym Koghut’s research interests lie at the intersection of digital transformation and strategic management in modern business environments. He focuses on the strategic implications of emerging technologies such as blockchain, artificial intelligence, and augmented/extended reality (XR), especially in the context of inter-organisational relationships and digital enterprises. His work explores how social capital, trust, and innovation evolve in digitally networked ecosystems, offering insights into how organisations adapt and thrive amid rapid technological change. Dr. Koghut also investigates consumer behavior in digital settings, including mobile payment discontinuance and AI-generated advertising. His research is both conceptually grounded and practically relevant, contributing to academic scholarship and informing industry practices in the digital age.

🏆 Awards and Honors of Dr. Maksym Koghut

Dr. Maksym Koghut has been recognized multiple times for his outstanding contributions to both research and teaching. He received the “Above & Beyond Award” twice from Kent Business School in 2022 for excellence in teaching at both undergraduate and postgraduate levels. His academic journey has been supported by prestigious scholarships, including the Vice Chancellor’s Research Scholarship from the University of Kent in 2018 and the Vice Chancellor’s Scholarship for PhD Studies from Huddersfield Business School in 2017. Additionally, he was awarded the Strategic Planning Society Prize for being the Best Student in Strategy at Huddersfield Business School in 2017. These honors highlight Dr. Koghut’s consistent excellence, dedication, and impact in the academic and professional communities.

🏁 Conclusion

Dr. Maksym Koghut is a compelling and highly suitable candidate for the Best Researcher Award. He brings together a rich combination of academic excellence, cutting-edge research, teaching innovation, and industry engagement. His interdisciplinary expertise and consistent scholarly output in contemporary digital business themes position him as a thought leader in the digital transformation domain.

📚 Publications Top Noted

  1. Title: A Blockchain-based Inter-organisational Relationships: Social and Innovation Implications
    Authors: Maksym Koghut, Omar Al-Tabbaa, Soo Hee Lee, Martin Meyer
    Year: 2021
    Citation: Academy of Management Proceedings, 2021-08
  2. Title: A Blockchain-based Inter-organisational Relationships: Social and Innovation Implications
    Authors: Maksym Koghut, Omar Al-Tabbaa, Soo Hee Lee, Martin Meyer
    Year: 2021
    Citation: Academy of Management Proceedings, 2021-08
  3. Title: The Effects of Autonomous Contracting on Inter-organisational Relationships: A Process Model of Trust, Social Capital and Value Co-creation
    Authors: Maksym Koghut, Omar Al-Tabbaa, Soo Hee Lee, Martin Meyer
    Year: 2020
    Citation: British Academy of Management Annual Conference, 2020-09-04
  4. Title: The Blockchain-Trust Nexus: A New Era for Inter-organizational Trust Meaning and Formation
    Authors: Maksym Koghut, Omar Al-Tabbaa, Martin Meyer
    Year: 2019
    Citation: Academy of Management Proceedings, 2019-08
  5. Title: Modelling Decentralised Collaboration Between Engineering Teams: A Blockchain-based Solution
    Authors: Maksym Koghut, John Makokha
    Year: 2018
    Citation: VI International Scientific and Technical Conference, 2018-09-01

Raviteja Sista | Computer Science and Artificial Intelligence | Best Researcher Award

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Mr. Raviteja Sista | Computer Science and Artificial Intelligence | Best Researcher Award

Research Scholar at Indian Institute of Technology Kharagpur, India

Raviteja Sista is a dynamic and accomplished researcher specializing in Artificial Intelligence, Deep Learning, and Medical Image Analysis. Currently pursuing his Ph.D. at the Indian Institute of Technology Kharagpur with an outstanding GPA of 9.4, he is a recipient of the prestigious Prime Minister’s Research Fellowship. Raviteja holds an MSc in Signal Processing and Communications from the University of Edinburgh and a Bachelor’s in Electronics and Communication Engineering from Osmania University. His research focuses on developing AI-driven frameworks for surgical planning and outcome prediction, with notable contributions to multimodal graph-based learning and surgical video analysis. He has published extensively in top-tier journals such as Medical Image Analysis and Computers in Biology and Medicine, and has actively contributed to international AI challenges and symposia. His technical expertise, academic excellence, and dedication to solving real-world healthcare problems through AI make him a standout figure in the research community.

Professional Profile 

🎓 Education of Raviteja Sista

Raviteja Sista has pursued a stellar academic path marked by excellence and innovation. He is currently enrolled in a Ph.D. program at the Indian Institute of Technology Kharagpur, specializing in Artificial Intelligence at the Centre of Excellence, where he maintains an impressive GPA of 9.4/10. Prior to this, he earned his Master of Science in Signal Processing and Communications with Distinction from the University of Edinburgh (2019–2020). His foundational engineering training was completed with a Bachelor of Engineering in Electronics and Communication from M.V.S.R. Engineering College, affiliated with Osmania University, where he secured a remarkable 85.34%. Raviteja also boasts an outstanding academic record from his early years, achieving 94.6% in Intermediate studies at Narayana Junior College and a CGPA of 9.8/10 in Class X from Lotus National School, Hyderabad.

💼 Professional Experience of Raviteja Sista

Raviteja Sista has a well-rounded professional background that bridges academia, research, and industry. He is currently a Teaching Assistant at IIT Kharagpur, where he supports academic instruction in AI and deep learning. Over the years, he has held teaching roles at several institutions including SRKR Engineering College, CSI Wesley Institute of Technology, Assam Down Town University, and JNTU Kakinada, demonstrating his commitment to education and knowledge dissemination. Complementing his academic roles, Raviteja also gained valuable industry experience as an Associate Software Developer Intern at Accenture Solutions Pvt. Ltd. and through multiple internships at Defence Research and Development Laboratory (DRDL), Hyderabad. His professional journey reflects a strong blend of research, software development, and teaching expertise, all anchored in the field of artificial intelligence and signal processing.

🔬 Research Interests of Raviteja Sista

Raviteja Sista’s research interests lie at the intersection of artificial intelligence and healthcare, with a strong focus on applying deep learning techniques to complex real-world problems. His core areas of interest include Deep Learning, Medical Image Analysis, Digital Signal Processing, Image Processing, Artificial Intelligence, and Design of Algorithms. He is particularly passionate about developing AI-powered systems for surgical planning and automation, leveraging multimodal data, graph neural networks, and computer vision. His work aims to enhance patient safety, improve clinical outcomes, and drive innovation in intelligent medical systems. Raviteja’s commitment to impactful, interdisciplinary research is evident in his projects and publications, which bridge technical depth with healthcare relevance.

🏅 Awards and Honors of Raviteja Sista

Raviteja Sista has been recognized with several prestigious awards and honors that highlight his academic brilliance and research potential. Most notably, he was awarded the Prime Minister’s Research Fellowship (PMRF) in 2022, one of India’s most esteemed research fellowships supporting exceptional doctoral scholars. He also earned a Certificate of Merit for completing the “Advanced Certification in Artificial Intelligence and Machine Learning” from IIIT Hyderabad in 2019. Additionally, Raviteja demonstrated national-level academic excellence by ranking in the Top 3% among over 1 lakh candidates in GATE 2019, a highly competitive examination for engineering graduates in India. These accolades reflect his consistent pursuit of excellence and his growing reputation as a promising researcher in the field of artificial intelligence.

🧾 Conclusion 

Sista Raviteja stands out as a highly qualified, technically accomplished, and visionary researcher in AI for healthcare. With strong academic credentials, impactful projects, respected publications, and active involvement in the scientific community, he demonstrates clear potential for leadership in scientific research.Despite minor areas of potential growth in independent authorship and translational work, his contributions already meet and, in some cases, exceed the typical benchmarks for the Best Researcher Award.

📚 Publications Top Noted

  1. Title: Deep neural hashing for content-based medical image retrieval: A survey
    Authors: A. Manna, R. Sista, D. Sheet
    Journal: Computers in Biology and Medicine, Volume 196, Article 110547
    Year: 2025
    Citations: –
  2. Title: Artificial Intelligence (AI)–Based Model for Prediction of Adversity Outcome Following Laparoscopic Cholecystectomy—a Preliminary Report
    Authors: R. Agrawal, S. Hossain, H. Bisht, R. Sista, P.P. Chakrabarti, D. Sheet, U. De
    Journal: Indian Journal of Surgery, Volume 87 (1), Pages 52–59
    Year: 2025
    Citations: 1
  3. Title: Exploring the Limits of VLMs: A Dataset for Evaluating Text-to-Video Generation
    Authors: A. Srivastava, R. Sista, P.P. Chakrabarti, D. Sheet
    Conference: Indian Conference on Computer Vision Graphics and Image Processing (ICVGIP)
    Year: 2024
    Citations: –
  4. Title: SimCol3D—3D reconstruction during colonoscopy challenge
    Authors: A. Rau, S. Bano, Y. Jin, P. Azagra, J. Morlana, R. Kader, E. Sanderson, …, R. Sista
    Journal: Medical Image Analysis, Volume 96, Article 103195
    Year: 2024
    Citations: 16
  5. Title: CholecTriplet2022: Show me a tool and tell me the triplet—An endoscopic vision challenge for surgical action triplet detection
    Authors: C.I. Nwoye, T. Yu, S. Sharma, A. Murali, D. Alapatt, A. Vardazaryan, K. Yuan, …, R. Sista
    Journal: Medical Image Analysis, Volume 89, Article 102888
    Year: 2023
    Citations: 29
  6. Title: CholecTriplet2021: A benchmark challenge for surgical action triplet recognition
    Authors: C.I. Nwoye, D. Alapatt, T. Yu, A. Vardazaryan, F. Xia, Z. Zhao, T. Xia, F. Jia, …, R. Sista
    Journal: Medical Image Analysis, Volume 86, Article 102803
    Year: 2023
    Citations: 61
  7. Title: CholecTriplet2022: Show me a tool and tell me the triplet—An endoscopic vision challenge for surgical action triplet detection
    Authors: C.I. Nwoye, T. Yu, S. Sharma, A. Murali, D. Alapatt, A. Vardazaryan, …, R. Sista
    Repository: arXiv, arXiv:2302.06294
    Year: 2023
    Citations: –
  8. Title: I’m GROOT: a multi head multi GRaph netwOrk recognizing surgical actiOn Triplets
    Authors: R. Sista, R. Sathish, R. Agrawal, U. De, P.P. Chakrabarti, D. Sheet
    Conference: ICVGIP 2022
    Year: 2022
    Citations: 1
  9. Title: CholecTriplet2021: A benchmark challenge for surgical action triplet recognition
    Authors: C.I. Nwoye, D. Alapatt, T. Yu, A. Vardazaryan, F. Xia, Z. Zhao, …, R. Sista
    Repository: arXiv, arXiv:2204.04746
    Year: 2022
    Citations: 1
  10. Title: I’m GROOT: a multi head multi GRaph netwOrk recognizing surgical actiOn Triplets
    Authors: S. Raviteja, R. Sathish, R. Agrawal, U. De, P.P. Chakrabarti, D. Sheet
    Conference: ICVGIP
    Year: 2022
    Citations: –
  11. Title: Challenges of Decomposing Tools in Surgical Scenes Through Disentangling The Latent Representations
    Authors: S.L. Gorantla, R. Sista, A. Srivastava, U. De, P.P. Chakrabarti, D. Sheet
    Workshop: ICLR Workshop on Challenges in Applied Deep Learning (ICBNB)
    Year: 2025 (Accepted)
    Citations: –

 

Badr Machkour | Artificial Intelligence | Best Researcher Award

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Dr. Badr Machkour | Artificial Intelligence | Best Researcher Award

Professor, Faculty of Legal, Economic and Social Sciences, Morocco 

Dr. Badr Machkour is a Moroccan researcher and academic with deep expertise in economics, finance, and digital transformation. Currently holding a Ph.D. in Economic and Management Sciences, he has contributed to multiple domains including Industry 4.0, financial digitalization, and educational innovation. With a robust blend of academic and consulting experience, Dr. Machkour bridges theory and practice to drive impactful research. 🌐📊

Profile

Scopus

Google Scholar

Orcid

🎓 Education

Dr. Machkour holds a Doctorate in Economic and Management Sciences (2018–2023) from the FSJES of Agadir. His academic foundation includes a degree in Audit and Management Control from ENCG Agadir (2014–2017), post-preparatory classes in Economics and Commerce (2012–2014), and a Mathematics Baccalaureate (2011–2012). His diverse training forms a strong base for multidisciplinary research. 📚🧠

💼 Professional Experience

Dr. Machkour has extensive experience as a financial auditor, consultant, and trainer. He currently serves as a trainer at the Cité des Métiers et des Compétences (OFPPT), delivering finance and management programs. His previous roles span auditing and consulting at prominent firms like Augeco, MAZARS Maroc, and Agadir Conseil, involving sectors from agriculture to banking. 🏢💼📈

🔬 Research Interests

His research explores the intersection of Industry 4.0, digital banking solutions, customer experience, AI in education, and entrepreneurship. Dr. Machkour is particularly interested in how technology transforms economic relationships, pedagogical structures, and corporate strategies. 🤖📱🏫

🏆 Awards & Honors

While specific awards are not listed, Dr. Machkour’s work has been featured in indexed journals and cited internationally — notably his highly cited paper on Industry 4.0’s implications in finance. His academic contributions reflect both quality and influence. 🥇🌍

📑 Publications

Industry 4.0 and its Implications for the Financial Sector, Procedia Computer Science, 2020 — Cited by 151 🏦

The Rise of Artificial Intelligence in Educational Management: A Prospective Analysis on the Role of the Virtual Educational Director, Procedia Computer Science, 2025 🧠

Internet of Things in Education: Transforming Learning Environments, Enhancing Pedagogy, and Optimizing Resource Management, Data and Metadata, 2024 🏫

L’impact de l’adoption des solutions digitales sur la relation banque-client, Revue Française d’Economie et de Gestion, 2024 — Cited by 2 📲

Les facteurs d’adoption des solutions digitales bancaires par les consommateurs marocains, IJAFAME, 2022 — Cited by 1 📱

The Uses of Connected Objects and Their Influence on the Customer Experience, Test Engineering and Management, 2020 — Cited by 1 🌐

Etude exploratoire du développement de l’esprit Entrepreneurial et des compétences Entrepreneuriales auprès des étudiants au Maroc, Alternatives Managériales Economiques, 2024 👨‍🎓

Entrepreneurship 4.0 and Success Factors in the Context of Industry 4.0: A literature review, African Scientific Journal, 2024 🚀

✅ Conclusion

Overall, Dr. Badr Machkour is a promising and accomplished researcher whose work bridges digital innovation and economic practice with scholarly insight. His growing citation record, topical relevance, and interdisciplinary reach make him a strong candidate for the Best Researcher Award. With continued international engagement and broader collaborative networks, his impact is poised to grow even further. 🌍📈

Toktam Akbari Khalaj | Data Science and Analytics | Excellence in Research Award

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Toktam Akbari Khalaj | Data Science and Analytics | Excellence in Research Award

Mrs Toktam Akbari Khalaj, Mashhad University of Medical Sciences, Iran

Mrs. Toktam Akbari Khalaj is a distinguished Iranian biostatistician known for her rigorous research in traffic injury prediction, prehospital emergency care, and health data modeling. With over two decades of professional experience and a dynamic academic career, she has significantly contributed to public health research, especially in North-Eastern Iran. Her publications, presented in reputed journals like Heliyon and BMC Public Health, emphasize the application of advanced statistical and machine learning techniques to address real-world health challenges. She serves as a project manager and biostatistician at Emergency Medical Services, and her proactive approach to forecasting health emergencies during crises like COVID-19 has drawn national attention. Fluent in both Persian and English, Mrs. Akbari Khalaj combines analytical excellence with outstanding communication and leadership skills. Her interdisciplinary approach and practical contributions make her an exceptional nominee for the Excellence in Research Award.

Publication Profile

Google Scholar

Education

Mrs. Akbari Khalaj holds a Master of Science (M.Sc.) in Biostatistics from Mashhad University of Medical Sciences (2017–2021), where she conducted a thesis on forecasting ambulance dispatches for traffic accidents using time series regression models. Prior to that, she earned a Bachelor of Science (B.Sc.) in Statistics from Azad University of Mashhad (2000–2004). Her academic background provided a solid foundation in statistical modeling, data mining, and biostatistical applications in health systems. Her postgraduate training enabled her to develop specialized expertise in predictive analytics and epidemiological modeling, particularly in trauma and emergency settings. Her advanced research skills have led her to publish and collaborate across multiple health domains. She also holds a TOEFL iBT score of 101, reflecting strong English proficiency. These academic credentials, combined with her practical research, reflect her dedication to applying theoretical insights into meaningful public health solutions.

Experience

Mrs. Akbari Khalaj brings a wealth of professional experience in statistical analysis and healthcare research. She began as a statistician at Emergency Medical Services (EMS) in 2007, transitioning into a biostatistician role in 2017. Since 2021, she has served as a project manager at EMS, overseeing data-driven projects in health surveillance, prehospital care, and trauma analytics. She has also worked as a researcher at Azad University (2002–2004) and Mashhad University of Medical Sciences (2018–2022), contributing to both academic and operational research. Her expertise in handling large datasets, implementing time series and logistic regression models, and her proficiency in R, Stata, SPSS, and Power BI, make her a cornerstone in data-informed decision-making. Beyond technical prowess, she is known for her leadership in emergency response analytics and evidence-based planning, especially during mass gatherings and pandemic crises. Her multidisciplinary involvement makes her an ideal candidate for research distinction.

Awards and Honors

While specific awards or formal recognitions are not explicitly listed, Mrs. Akbari Khalaj’s academic and professional contributions reflect honor-worthy distinction. Her co-authored and first-authored publications in high-impact journals such as BMC Public Health and Heliyon indicate peer recognition and scholarly influence. She has presented at prestigious events like the International Congress on Health in Arbaeen and the International Congress on Prehospital Emergency Innovation, signifying academic acknowledgment. Her long-standing role as project manager at EMS and her collaborative research with top Iranian health institutions underscore her leadership and credibility. Notably, her involvement in managing and modeling public health emergencies, such as during COVID-19, highlights the real-world impact of her work. These accomplishments reflect an ongoing trajectory of professional recognition that aligns with the spirit of the Excellence in Research Award.

Research Focus

Mrs. Akbari Khalaj’s research is rooted in biostatistics and emergency health systems, with a core focus on time series modeling, logistic regression, and big data analytics in traffic and trauma-related health incidents. She has applied innovative statistical methods to predict ambulance dispatches, assess injury mortality, and evaluate prehospital emergency trends in urban Iran. Her work addresses the intersection of public health, emergency response, and predictive modeling, often exploring the effects of external factors like COVID-19. Additionally, she is engaged in meta-analysis, count data modeling, machine learning, and data visualization for public health monitoring. Her research is both preventive and responsive, aiming to enhance policy decisions and emergency service planning. By integrating advanced computational tools with field data, Mrs. Akbari Khalaj’s work significantly contributes to predictive healthcare and operational efficiency. Her research output supports a data-driven approach to public health crisis management.

Publication Top Notes

Multiple-scale spatial analysis of paediatric, pedestrian road traffic injuries in a major city in North-Eastern Iran 2015–2019

Spatial-time analysis of cardiovascular emergency medical requests: enlightening policy and practice

Comparison of GAP, R-GAP, and new trauma score (NTS) systems in predicting mortality of traffic accidents that injure hospitals at Mashhad University of medical sciences

An exploration of occupational violence among emergency medical staff of a major medical university; 2020

Evaluation of Prehospital Emergency Medical Services before and after COVID-19 in Mashhad

GENERAL WIEW OF COMPARISON BETWEEN SMART BOARD & BLACK BOARD IN GENERAL MATHEMATHICS BOOK 1 & 2 AMONG IRANIAN HIGH SCHOOL

Analysis of the Patterns of Mortality Causes in Traffic Accident Injuries Using Logistic Regression Model in Northeastern Iran

 

Shuai Cao | Computer Science and Artificial Intelligence | Best Researcher Award

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Shuai Cao | Computer Science and Artificial Intelligence | Best Researcher Award

Dr Shuai Cao, School of Automation, Wuhan University of Technology, China

Dr. Shuai Cao is a dynamic researcher in the field of Computational Intelligence, currently pursuing graduate studies at Kunming University of Science and Technology and engaging in joint research at the Guangdong Academy of Sciences. With a focus on enhancing meta-heuristic algorithms, Dr. Cao has contributed significantly to engineering optimization, especially in AGV path planning and offset printing machine design. He is the mind behind the innovative Piranha Foraging Optimization Algorithm (PFOA) and co-author of several impactful SCI/EI publications. His expertise in algorithm improvement, machine learning, and pattern recognition is reflected through funded projects and hands-on roles in top research institutions like the South China Intelligent Robot Innovation Institute. With a remarkable blend of theoretical insight and practical application, Dr. Cao is a promising candidate for the Best Researcher Award, embodying academic rigor and real-world impact.

Publication Profile 

Orcid

Education

Dr. Shuai Cao’s academic journey began at Baotou Rare Earth High-tech No. 1 High School (2014–2017), where he laid a strong foundation in the sciences. He pursued his undergraduate degree in Mechanical and Electronic Engineering at Chongqing University of Humanities, Science and Technology (2017–2021), gaining critical insights into systems design and robotics. Since 2021, he has been a postgraduate student in Electronic Information at Kunming University of Science and Technology, further sharpening his expertise in computational theory and algorithmic systems. Complementing his studies, Dr. Cao has been engaged in a joint training program at the Intelligent Manufacturing Institute of the Guangdong Academy of Sciences since 2022. His coursework includes meta-heuristic algorithms, machine learning, digital signal processing, and pattern recognition, all of which feed directly into his research in Computational Intelligence and engineering optimization. His interdisciplinary background empowers him to tackle complex problems with innovative solutions.

Experience

Dr. Shuai Cao has held impactful roles in prestigious research institutions. From May 2022 to July 2023, he worked at the Intelligent Manufacturing Institute of the Guangdong Academy of Sciences, where he conducted advanced research on AGV handling robots. This included applying improved intelligent algorithms for path planning and optimization scheduling—work closely aligned with his master’s thesis. Since July 2023, he has been with the South China Intelligent Robot Innovation Institute, applying swarm intelligence methods to optimize the structure of high-speed multi-color offset printing machines. Dr. Cao’s work integrates theoretical research with industrial application, setting a benchmark for practical relevance. His involvement in key science and innovation projects also reflects his growing leadership in the field. From optimization algorithms to real-world robotic systems, Dr. Cao’s hands-on approach is shaping the future of intelligent manufacturing.

Awards and Honors

Dr. Shuai Cao has earned distinguished recognition in both academic and research circles for his innovative contributions to engineering optimization. As a lead researcher on multiple government-funded projects—including “Research and Application of Intelligent Scheduling of Mobile Collaborative Robot Clusters for Intelligent Manufacturing” (Project Code: 2130218003022) and the “Foshan Science and Technology Innovation Team Project” (Project Code: FS0AA-KJ919-4402-0060)—he has demonstrated expertise in bridging theory with practical industrial solutions. His pioneering research has been published in high-impact SCI and EI journals and conferences, such as IEEE ACCESS and the International Conference on Robotics and Automation Engineering (ICRAE). A highlight of his work is the development of the Piranha Foraging Optimization Algorithm (PFOA), which has garnered considerable attention in the optimization community for its novelty and effectiveness. Dr. Cao’s sustained dedication to cutting-edge innovation, along with his leadership in collaborative, cross-disciplinary projects, makes him a compelling nominee for the Best Researcher Award.

Research Focus

Dr. Shuai Cao’s research is centered on Computational Intelligence, specifically the improvement and engineering application of swarm intelligence algorithms. His work addresses key challenges in traditional optimization methods, such as premature convergence, low population diversity, and slow optimization speeds. He has successfully designed algorithms that overcome these limitations, notably the Piranha Foraging Optimization Algorithm (PFOA). His research extends to practical applications like automated guided vehicle (AGV) path planning, scheduling in smart factories, and mechanical structure optimization for high-speed printing systems. Through interdisciplinary methods, he combines machine learning, pattern recognition, and digital signal processing to bring theoretical advancements into real-world manufacturing challenges. With a clear aim of enhancing intelligent manufacturing systems, his research contributes to both academic knowledge and industrial innovation. His growing body of work reflects originality, technical rigor, and a strong alignment with modern engineering demands.

Publication Top Notes

Research on the Design and Application of Multi-Port Energy Routers

 

Jiantao Shi | Robotics and Automation | Best Researcher Award

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Jiantao Shi | Robotics and Automation | Best Researcher Award

Mrs Jiayun Nie, chongqing Jiaotong University, China

Jiayun Nie is a distinguished professor at Nanjing Tech University, China, specializing in cooperative control of multi-robot systems, fault diagnosis, and fault-tolerant control of distributed systems. 📡 With a Ph.D. in Control Science and Engineering from Tsinghua University, she has made pioneering contributions to multi-agent systems, UAV adaptive control, and reinforcement learning-based fault diagnosis. ✈️🔍 Her research has led to high-impact publications on fault estimation, bipartite consensus, and deep learning models for system diagnostics. 🤖 She has served as a research fellow at the Nanjing Research Institute of Electronic Technology and has received recognition as an Outstanding Reviewer for the Journal of the Franklin Institute (2017). 📚 Her latest work explores AI-driven fault-tolerant frameworks for autonomous systems and aerospace applications. 🚀 With a stellar academic record and transformative research, she is a deserving recipient of the Best Researcher Award. 🏅

Publication Profile

Orcid

Education

Jiayun Nie’s academic journey is marked by excellence in control science and automation engineering. She earned her Ph.D. in Control Science and Engineering from Tsinghua University (2011-2016), focusing on fault-tolerant systems and adaptive control strategies for multi-robot cooperation. 🤖🔍 Her doctoral research introduced novel iterative learning algorithms for fault estimation and compensation, improving system reliability. Before this, she completed her B.E. in Electrical Engineering and Automation at Beijing Institute of Technology (2007-2011), where she laid the groundwork in robotic control, embedded systems, and automation engineering. 🎛️⚡ During her studies, she was actively involved in research projects on UAV dynamics and cooperative control theory, leading to early publications and innovative designs for fault-resilient robotics. 🚀 Her strong educational foundation, combined with rigorous research, has positioned her as a global leader in fault diagnosis and control engineering. 📚

Experience

Jiayun Nie has an extensive academic and research career, currently serving as a Professor at Nanjing Tech University (2021-present), where she leads groundbreaking work on distributed control and autonomous systems. 🤖🔍 Prior to this, she was a Research Fellow (2019-2021) and Associate Research Fellow (2016-2018) at the Nanjing Research Institute of Electronic Technology, contributing to fault detection models for phased array radar transceivers and advanced control strategies for UAVs. ✈️📡 Her expertise in adaptive control and AI-driven fault detection has been instrumental in developing next-generation intelligent robotic networks. 🚀 Throughout her career, she has collaborated with leading research institutions, advancing the state-of-the-art in reinforcement learning-based fault diagnosis, consensus control, and multi-agent fault-tolerant frameworks. 🏅 Her work continues to influence aerospace, robotics, and autonomous vehicular technologies, making her an authority in the field. 📚

Awards and Honors

Jiayun Nie’s outstanding contributions to robotics and fault-tolerant control have earned her several prestigious accolades. 🎖️ She was recognized as an Outstanding Reviewer for the Journal of the Franklin Institute (2017) 📚, reflecting her expertise in control systems and automation engineering. 🚀 Her innovative research on fault diagnosis in distributed robotic systems has been cited extensively, leading to multiple best paper awards at international IEEE and IFAC conferences. 🏅 She has received multiple grants and funding awards for her pioneering work in multi-agent cooperative control and AI-driven adaptive learning control. 🤖 As a highly regarded professor and researcher, her contributions continue to impact autonomous systems, aviation safety, and smart robotics. ✈️ With her extensive publications and transformative research, she is a deserving recipient of the Best Researcher Award, recognized for her excellence in innovation and scientific advancement. 🏆📡

Research Focus

Jiayun Nie’s research revolves around cooperative control, fault diagnosis, and learning-based fault-tolerant strategies in autonomous systems. 🤖 She has made significant breakthroughs in multi-robot cooperation, bipartite consensus, and AI-driven adaptive fault detection. 📊 Her work in fault-tolerant control enhances resilience in UAVs and aerospace systems, ensuring robustness against unknown disturbances and failures. ✈️ She has developed deep learning and reinforcement learning models for self-healing robotic networks, transforming distributed control frameworks. 🏅 Her studies in event-based control, collision avoidance, and system stability have contributed to advancements in autonomous vehicle technology. 🚀 By integrating data-driven methods with real-time fault estimation, her research provides solutions for smart transportation, defense, and aerospace industries. 📡 With numerous high-impact publications, Jiayun Nie’s pioneering work defines the future of adaptive robotics and autonomous systems. 🎓

Publications Top Notes

  1. “A parallel weighted ADTC-Transformer framework with FUnet fusion and KAN for improved lithium-ion battery SOH prediction” 🔋 (2025)
  2. “Bipartite Fault-Tolerant Consensus Control for Multi-Agent Systems with a Leader of Unknown Input Under a Signed Digraph” 🤖 (2025)
  3. “Iterative learning based fault estimation for stochastic systems with variable pass lengths and data dropouts” 📊 (2025)
  4. “A Two-Stage Fault Diagnosis Method With Rough and Fine Classifiers for Phased Array Radar Transceivers” 📡 (2024)
  5. “An intuitively-derived decoupling and calibration model to the multi-axis force sensor using polynomials basis” 📊 (2024)
  6. “Event-Based Adaptive Fault Tolerant Control and Collision Avoidance of Wheel Mobile Robots With Communication Limits” 🤖 (2024)
  7. “Reinforcement Learning-Based Fault Tolerant Control Design for Aero-Engines With Multiple Types of Faults” ✈️ (2024)

Bhanu Shrestha | Computer Science and Artificial Intelligence | Best Researcher Award

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Bhanu Shrestha | Computer Science and Artificial Intelligence | Best Researcher Award

Prof. Dr Bhanu Shrestha, Kwangwoon University, South Korea

Prof. Dr. Bhanu Shrestha is a distinguished academic in Electronic Engineering, with a Ph.D. from Kwangwoon University, Seoul, Korea. He has been active in various leadership roles, including Chairman of ICT-AES and Editor-in-Chief of the International Journal of Advanced Engineering. Dr. Shrestha has contributed extensively to research, with notable book publications and multiple awards, including the “Achievement Award” from IIBC Korea and “Best Paper Award” at ISSAC 214. His work spans various international conferences, focusing on advanced engineering, nanotechnology, and biosensor applications. 🌍📚🏅💻🧑‍🔬

Publication Profile

Scopus

Education

Prof. Dr. Bhanu Shrestha has an extensive academic background in Electronic Engineering. He completed his Ph.D. in Electronic Engineering at Kwangwoon University, Seoul, Korea (2004-2008), after earning his M.S. in the same field at the same institution (2002-2004). Dr. Shrestha’s journey in engineering began with a B.S. in Electronic Engineering from Kwangwoon University (1994-1998). His years of dedication to education and research have contributed significantly to advancements in the field of electronics. ⚙️🎓📡

Experience

Prof. Dr. Bhanu Shrestha is a distinguished leader in engineering, serving as Chairman of ICT-AES from 2022 to 2024. With a long tenure as the Editor-in-Chief of the International Journal of Advanced Engineering, he has shaped academic discourse in the field. His active involvement with the Nepal Engineering Council (NEC) and Nepal Engineers’ Association (NEA) further cements his influence in Nepal’s engineering community. Prof. Shrestha’s commitment to advancing engineering practices is evident through his leadership roles and active contributions to both national and international engineering platforms. 🛠️📚🔧🌍

Honor & Awards

Prof. Dr. Bhanu Shrestha has received numerous prestigious awards throughout his career. Notably, he was honored with the “Achievement Award” from IIBC Korea (2015) 🏆 and multiple “Best Paper Awards” from ISSAC 214 and ICACT (2014) 📄. He also earned the “Excellent Paper Award” from the Korea Institute of Information Technology (2012) 🏅 and the “Certificate of Honorary Citizenship” from the Mayor of Seong-buk, Seoul (2012) 🏙️. His accolades extend to Nepal, where he received the presidential “Nepal Vidhyabhusan Padak ‘Ka’” Gold Medal (2009) 🥇, and several honors for his contributions to Taekwondo and Hapkido 🥋.

Research Focus

Prof. Dr. Bhanu Shrestha’s research focuses on advanced computational techniques, particularly in the intersection of artificial intelligence (AI) and engineering. He explores areas such as machine learning, metaheuristics, and optimization methods applied to real-world challenges in fields like medical imaging (e.g., SPECT-MPI cardiovascular disease classification), traffic accident prediction, and network security. His work also extends to customer churn prediction in telecom industries and network security improvements. Shrestha’s contributions aim to enhance system efficiency, prediction accuracy, and security across diverse technological and engineering domains. 🧠💻⚙️🩺📡

Editorial and Conference

Prof. Dr. Bhanu Shrestha has made significant contributions to the field of engineering through his active involvement in international conferences like ISGMA 2015 and the International Conference on ICT & Digital Convergence (2018) 🌍📡. His dedication to global collaboration is evident in his participation in these events. Additionally, his editorial roles highlight his commitment to maintaining high-quality research output 📚📝. Prof. Dr. Shrestha continues to play a crucial role in advancing engineering through his global outreach, fostering innovation, and contributing to the growth of academic knowledge in his field. 🌟💡

Publication Top Notes

Multi-Scale Dilated Convolution Network for SPECT-MPI Cardiovascular Disease Classification with Adaptive Denoising and Attenuation

CorrectionSpecial Issue on Data Analysis and Artificial Intelligence for IoT

Correction to: A Proposed Waiting Time Algorithm for a Prediction and Prevention System of Traffic Accidents Using Smart Sensors (Electronics, (2022), 11, 11, (1765), 10.3390/electronics11111765)

Levy Flight-Based Improved Grey Wolf Optimization: A Solution for Various Engineering Problems

Leveraging metaheuristics with artificial intelligence for customer churn prediction in telecom industries

A Study on Improving M2M Network Security through Abnormal Traffic Control

Generative Adversarial Networks with Quantum Optimization Model for Mobile Edge Computing in IoT Big Data

 

Ali Othman Albaji | Computer Science and Artificial Intelligence | Best Researcher Award

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Ali Othman Albaji | Computer Science and Artificial Intelligence | Best Researcher Award

Dr Ali Othman Albaji, Libyan Authority for Scientific Research, Libya

With a Bachelor’s in Electrical Engineering and a Master’s in Electronics & Telecommunications from Universiti Teknologi Malaysia, this accomplished professional has extensive experience in academia and industry. Currently an Assistant Professor at the Higher College of Science and Technology in Libya, they also lead CR Technology System in the MENA region. Their research interests include optical wireless technologies and machine learning applications in environmental monitoring. Fluent in Arabic and English, with a diploma in Italian, they are also the President of the Postgraduate Student Society at UTM. 📡🎓🌍✍️

Publication profile

google scholar

Academic Background 

With a diverse academic journey, the individual holds a Master’s in Public Management and Leadership from the London School of Economics (LSE), UK, completed in 2010. They further pursued a Master in Electronics and Telecommunications at the University Technology Malaysia from 2019 to 2023. Their foundational education includes a Bachelor’s degree in Electrical Engineering, specializing in General Communications, from the Civil Aviation Higher College in Tripoli, Libya, earned in 2007. Additionally, they completed a Diploma in the Italian language during the 2011/2012 academic year. 🎓📡

Experience

Dr. Ali Othman Albaji boasts a diverse work history across reputable organizations. He started as a Sales Advisor at Akida Company (LG) and ZTE/Telecom China, honing his expertise in the telecommunications field. His academic journey includes significant roles as an Assistant Professor and lecturer in Electronics and Telecommunications. In addition to his teaching, he has demonstrated leadership as the Chairman of CR Technology System (CRTS Group) and the President of the Postgraduate Student Society at Universiti Teknologi Malaysia. Dr. Albaji’s commitment to both academia and industry underscores his dedication to advancing technology and education. 📡🎓💼🌟

Main Hard Skills 

Dr. Albaji possesses a robust set of technical skills, including proficiency in CAD Design, MATLAB Simulation Analysis, Python, and data visualization tools like Tableau. His capabilities extend to qualitative and quantitative analysis, SCADA systems, and programming languages like Verilog and HTML. These skills enable him to tackle complex research problems and contribute innovatively to his field. 

Languages 

Fluent in Arabic and English, with an IELTS Band Score of 8.5, Dr. Albaji also has a very good command of Italian. This linguistic proficiency allows him to collaborate with international researchers and disseminate his work to a broader audience. 

Research focus

Ali Othman Albaji’s research focus centers on machine learning applications in environmental noise classification, emphasizing smart cities and mobile communications. His work includes developing algorithms for monitoring and classifying noise pollution using MATLAB, contributing to urban planning and public health. He has also explored traffic noise impacts on residential areas and mobile telecommunications in Libya. His diverse research interests extend to the design and implementation of communication systems, highlighting the integration of technology in environmental studies. Through these contributions, Albaji aims to enhance noise management and promote sustainable urban environments. 🌍📊🔊📡

Publication top notes

Investigation on Machine Learning Approaches for Environmental Noise Classifications

A Machine Learning for Environmental Noise Monitoring and Classification Using Matlab

Machine Learning for Environmental Noise Classification in Smart Cities

Designing the Global System for Mobile Communications GSM-900 Cellular Network up to the Nominal Cell Plan in Tripoli, Libya

Conclusion and Recommendations

A Review of Traffic Highway Noise Towards Residential Area

NOISE POLLUTION DATA REPORTING AND WAREHOUSING USING TABLEAU SOFTWARE

Designing and Implementing a Signed Multiplier Radix-2 Using Booth’s Algorithm