Ji Xu | Big Data Analytics | Best Researcher Award

Prof. Ji Xu | Big Data Analytics | Best Researcher Award

Prof. Ji Xu, Guizhou University, China

Ji Xu (M’22) is an associate professor at the State Key Laboratory of Public Big Data, Guizhou University, China. He obtained his B.S. in Computer Science from Beijing Jiaotong University in 2004 and earned his Ph.D. in Computer Science from Southwest Jiaotong University in 2017. With expertise in data mining, granular computing, and machine learning, he has significantly contributed to the field through extensive research and publications. Dr. Xu has authored and co-authored over 30 papers in prestigious international journals, including IEEE TFS, IEEE TCYB, and Information Sciences. He also serves as a reviewer for top-tier journals like IEEE TNNLS, IEEE TFS, and Pattern Recognition. As an active member of IEEE, CCF, and CAAI, he remains at the forefront of technological advancements in artificial intelligence and big data analytics. His work continues to shape the future of intelligent computing and large-scale data processing.

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Summary of Suitability for the Research for Best Researcher Award

Ji Xu is highly suitable for the “Research for Best Researcher Award” due to his impressive academic and professional achievements in the field of computer science, with a particular focus on data mining, granular computing, and machine learning. His educational background includes a Bachelor’s degree from Beijing Jiaotong University and a Ph.D. from Southwest Jiaotong University, which demonstrate his foundational expertise in these critical fields. As an associate professor at the State Key Laboratory of Public Big Data at Guizhou University, Xu has a clear commitment to advancing research in his area of specialization.

Xu’s research productivity further demonstrates his suitability for the award. He has authored over 30 peer-reviewed papers in prestigious international journals such as IEEE TFS, IEEE TCYB, IEEE JIoT, Information Sciences, and others. His contributions to these journals reflect his high-level expertise and ability to make significant advancements in his field. Furthermore, Xu has co-authored a book, showcasing his ability to synthesize and communicate complex ideas to a broader audience.

🎓 Education 

Ji Xu’s academic journey began at Beijing Jiaotong University, where he obtained his Bachelor of Science (B.S.) in Computer Science in 2004. He later pursued advanced studies at Southwest Jiaotong University, earning his Doctor of Philosophy (Ph.D.) in Computer Science in 2017. His doctoral research focused on artificial intelligence, data mining, and computational intelligence, laying a strong foundation for his contributions to big data analytics. Throughout his academic career, he demonstrated exceptional analytical skills and a deep understanding of machine learning techniques. His education provided him with the technical expertise required to explore complex datasets and develop intelligent computing models. Additionally, his training at two leading Chinese universities equipped him with interdisciplinary knowledge in software engineering, algorithms, and large-scale data processing. His academic background remains a cornerstone of his professional research, guiding his work in advanced computational methods and innovative AI applications.

💼 Professional Experience

Dr. Ji Xu is currently an associate professor at the State Key Laboratory of Public Big Data, Guizhou University. In this role, he leads research in big data analytics, machine learning, and granular computing. His professional experience spans academia and research, with a focus on developing intelligent algorithms for large-scale data processing. Over the years, he has collaborated with industry and academia on high-impact projects related to artificial intelligence and computational intelligence. As an active member of IEEE, CCF, and CAAI, he contributes to the global research community through technical publications, conference presentations, and journal reviews. In addition to his research, he mentors graduate students, guiding them in innovative AI and data science projects. His expertise in handling complex data-driven challenges has established him as a prominent researcher in the field. Dr. Xu’s work continues to influence advancements in big data and artificial intelligence applications.

🏅 Awards and Recognition

Dr. Ji Xu has received multiple accolades for his contributions to computer science, particularly in big data analytics, machine learning, and granular computing. He has been recognized for his research excellence through numerous best paper awards at international conferences. His extensive publication record in prestigious journals such as IEEE TFS, IEEE TCYB, and Neurocomputing has earned him a reputation as a leading researcher in artificial intelligence. Additionally, he serves as a reviewer for top-tier journals, including IEEE TNNLS, IEEE TFS, and Pattern Recognition, demonstrating his influence in shaping the field. As a distinguished member of IEEE, CCF, and CAAI, he actively participates in research communities and contributes to major advancements in computational intelligence. His innovative work in data science and AI continues to garner international recognition, positioning him among the top researchers driving the future of intelligent data processing and analytics.

🌍 Research Skills On Big Data Analytics

Dr. Ji Xu’s research expertise encompasses data mining, granular computing, and machine learning. His ability to analyze large-scale datasets and develop intelligent algorithms has led to groundbreaking contributions in big data analytics. He specializes in computational intelligence, predictive modeling, and pattern recognition, applying advanced AI techniques to solve complex real-world problems. His skills extend to deep learning, natural language processing (NLP), and algorithm optimization, enabling him to create efficient data-driven solutions. With a strong foundation in mathematical modeling and statistical analysis, he excels in deriving meaningful insights from high-dimensional data. His role as a reviewer for IEEE TFS, IEEE TNNLS, and Pattern Recognition reflects his deep understanding of AI methodologies. Additionally, he collaborates on interdisciplinary projects, integrating AI with emerging technologies such as IoT and edge computing. His research continues to push the boundaries of artificial intelligence, transforming data analytics and intelligent systems.

📖 Publication Top Notes

  • DenPEHC: Density peak based efficient hierarchical clustering
    Authors: J Xu, G Wang, W Deng
    Journal: Information Sciences, 373, 200-218
    Citations: 142
    Year: 2016

  • A survey of smart water quality monitoring system
    Authors: J Dong, G Wang, H Yan, J Xu, X Zhang
    Journal: Environmental Science and Pollution Research, 22(7), 4893-4906
    Citations: 139
    Year: 2015

  • Granular computing: from granularity optimization to multi-granularity joint problem solving
    Authors: G Wang, J Yang, J Xu
    Journal: Granular Computing, 2(3), 105-120
    Citations: 138
    Year: 2017

  • Self-training semi-supervised classification based on density peaks of data
    Authors: D Wu, M Shang, X Luo, J Xu, H Yan, W Deng, G Wang
    Journal: Neurocomputing, 275, 180-191
    Citations: 130
    Year: 2018

  • Review of big data processing based on granular computing
    Authors: J Xu, GY Wang, H Yu
    Journal: Chinese Journal of Computers, 38(8), 1497-1517
    Citations: 59
    Year: 2015

  • 基于粒计算的大数据处理 (Big Data Processing Based on Granular Computing)
    Authors: 徐计 (J Xu), 王国胤 (G Wang), 于洪 (H Yu)
    Journal: 计算机学报 (Chinese Journal of Computers), 38(8), 1497-1517
    Citations: 50
    Year: 2015

  • Fat node leading tree for data stream clustering with density peaks
    Authors: J Xu, G Wang, T Li, W Deng, G Gou
    Journal: Knowledge-Based Systems, 120, 99-117
    Citations: 44
    Year: 2017

  • Piecewise two-dimensional normal cloud representation for time-series data mining
    Authors: W Deng, G Wang, J Xu
    Journal: Information Sciences, 374, 32-50
    Citations: 40
    Year: 2016

  • A multi-granularity combined prediction model based on fuzzy trend forecasting and particle swarm techniques
    Authors: W Deng, G Wang, X Zhang, J Xu, G Li
    Journal: Neurocomputing, 173, 1671-1682
    Citations: 37
    Year: 2016

  • Local-Density-Based Optimal Granulation and Manifold Information Granule Description
    Authors: J Xu, G Wang, T Li, W Pedrycz
    Journal: IEEE Transactions on Cybernetics
    Citations: 28
    Year: 2017

Alimul Rajee | Computer Science | Young Scientist Award

Mr. Alimul Rajee | Computer Science | Young Scientist Award

Mr. Alimul Rajee, Dept. of ICT, Comilla University, Kotbari, Bangladesh

Alimul Rajee is a Lecturer at the Department of Information and Communication Technology, Comilla University. His academic journey includes a stellar performance with a CGPA of 3.69 in his M.Sc. in Information Technology from Jahangirnagar University. Rajee’s research interests span Machine Learning, Data Science, Artificial Intelligence, Cyber Security, and Robotics, with a focus on real-world applications such as traffic accident data analysis and smart waste management. He has contributed significantly to several research projects, and his work has been published in prestigious journals, such as Knowledge-Based Systems and Heliyon. In addition to his research, Rajee is an active educator, mentoring students and supervising projects in areas like IoT and deep learning. His dedication extends beyond the classroom to extracurricular activities, where he has received multiple awards and recognitions, including an international award for his project at Fujitsu Research Institute in Tokyo.

Professional Profile

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Orcid

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Suitability Summary of Young Scientist Awards

Alimul Rajee stands out as an excellent candidate for the Research for Young Scientist Award due to his impressive academic achievements, significant research contributions, and commitment to advancing in the fields of Machine Learning, Data Science, Artificial Intelligence, Cyber Security, and IoT. He has a strong educational background, earning his M.Sc. and B.Sc. with high CGPA rankings from Jahangirnagar University, which reflects his deep knowledge and dedication to his field.

Rajee’s research work is highly commendable, with several publications in reputable, Scopus-indexed journals such as Knowledge-Based Systems and Heliyon, where he has contributed to the development of novel algorithms and methodologies, especially in big data analysis, sentiment analysis, and AI-based applications. His ongoing and completed research projects, including a hybrid smart waste management system and aspect-based sentiment analysis for Bengali text, further showcase his innovative thinking and practical application of emerging technologies to address real-world problems. Additionally, his leadership in supervising over 40 academic projects and his participation in global training programs, like those held at the Fujitsu Research Institute in Japan, illustrate his proactive approach to both learning and teaching.

🎓  Education

Alimul Rajee completed his M.Sc. in Information Technology from Jahangirnagar University, securing a CGPA of 3.69 out of 4, ranking 6th in his batch. Before this, he earned his B.Sc. (Hons.) in the same field, also from Jahangirnagar University, with a CGPA of 3.71, again securing the 6th position. Rajee’s academic excellence dates back to his secondary education, where he achieved the highest CGPA of 5.00 in both his HSC and SSC exams from Govt. Ananadamohan College and Islamnagar Sailampur High School. His continuous pursuit of academic excellence earned him merit-based scholarships throughout his education. His academic prowess has laid a strong foundation for his research and professional career, as he continues to excel in his field with a focus on cutting-edge technologies such as AI and IoT.

💼 Professional Experience

Alimul Rajee’s professional career began as a Junior Data Scientist at Oculin Tech BD Ltd., where he worked from March 2020 to May 2021. He then served as a Senior Officer (ICT) at Sonali Bank PLC for a brief period before becoming a Lecturer at Comilla University in November 2021, where he currently teaches. Rajee’s teaching journey includes roles at Bangladesh University of Business and Technology (BUBT) and Jahangirnagar University (IIT-JU), where he was a Teacher Assistant. His extensive experience also includes supervising over 40 academic projects focused on machine learning, deep learning, and IoT. As an educator, he fosters a positive learning environment, guiding students through complex technical concepts while contributing to the development of innovative research and real-world applications.

🏅  Awards and Recognition

Alimul Rajee’s achievements have been recognized at both national and international levels. He has received several awards, including the UGC Research Grant from Comilla University for consecutive fiscal years, which is a testament to his research capabilities. Rajee’s work has been recognized by prestigious institutions such as Fujitsu Research Institute (FRI) in Tokyo, where his final project won 1st prize. He has also been a reviewer for the International Conference on Embracing Industry 4.0 for Sustainable Business Growth. His consistent academic and research excellence has earned him regular merit-based scholarships and fellowships, such as the National Science & Technology Fellowship from the ICT Division of Bangladesh.

🌍 Research Skills On Computer Science

Alimul Rajee specializes in the application of cutting-edge technologies such as Machine Learning, Artificial Intelligence, Cyber Security, and IoT. His research includes a diverse range of topics like traffic accident data analysis, sentiment analysis of Bengali text, and smart waste management. Rajee has honed his expertise in Data Science and deep learning methods, contributing to several high-impact publications in renowned journals such as Knowledge-Based Systems and Heliyon. His current research projects include Aspect-Category-Opinion-Sentiment Quad Extraction for Bengali Text and a Hybrid Smart Waste Management Technique using Deep Learning and IoT. Rajee’s proficiency in data analysis, algorithm design, and system integration showcases his strong research skills and his commitment to advancing technology for societal benefit.

📖 Publication Top Notes

  • “Aspect-based sentiment analysis for Bengali text using bidirectional encoder representations from transformers (BERT)”
    • Authors: MM Samia, A Rajee, MR Hasan, MO Faruq, PC Paul
    • Citation: International Journal of Advanced Computer Science and Applications, 13(12)
    • Year: 2022
  • “Detecting the provenance of price hike in agri-food supply chain using private Ethereum blockchain network”
    • Authors: MH Sayma, MR Hasan, M Khatun, A Rajee, A Begum
    • Citation: Heliyon, 10(11)
    • Year: 2024
  • “Analyzing depression on social media utilizing machine learning and deep learning methods”
    • Authors: PC Paul, MT Ahmed, MR Hasan, A Rajee, K Sultana
    • Citation: Indian Journal of Computer Science and Engineering, 14(5), 740-746
    • Year: 2023
  • “WFFS—An ensemble feature selection algorithm for heterogeneous traffic accident data analysis”
    • Authors: A Rajee, MS Satu, MZ Abedin, KMA Ali, S Aloteibi, MA Moni
    • Citation: Knowledge-Based Systems, 113089
    • Year: 2025

Phong Lam Nguyen Duy | Computer Science | Best Researcher Award

Mr. Phong Lam Nguyen Duy | Computer Science | Best Researcher Award

👤 Mr. Phong Lam Nguyen Duy, University of Engineering and Technology – Vietnam National University, Vietnam

Phong Lam Nguyen Duy is a motivated undergraduate student in the Computer Science Department at the University of Engineering and Technology, Vietnam National University, Hanoi. Born on July 6, 2004, in Ha Dong, Hanoi, Phong Lam is passionate about exploring cutting-edge technologies in data science and artificial intelligence. His primary research interests include automated data quality assurance, machine learning algorithms, and advancements in large language models. Apart from academics, Phong Lam is actively involved in volunteering, demonstrating a commitment to fostering community development through initiatives like the ICPC Asia Pacific Championship and Hanoi Green Summer programs. A proactive learner and aspiring researcher, Phong Lam has already contributed as a university research assistant at the Intelligence Software Engineering Laboratory, where he leverages his problem-solving skills and technical expertise. Phong Lam aspires to contribute significantly to the field of Computer Science and aims to bridge gaps between theoretical concepts and real-world applications.

Professional Profile

Orcid

Suitability for the “Research for Best Researcher Award”

Summary of Suitability:
Phong Lam Nguyen Duy demonstrates remarkable potential as a candidate for the “Research for Best Researcher Award.” Currently pursuing undergraduate studies in the Computer Science Department at Vietnam National University, Hanoi, Phong has already begun contributing to cutting-edge research fields, including automated data quality assurance, machine learning, and large language models. These areas are highly relevant and impactful in today’s rapidly evolving technological landscape, showcasing his alignment with contemporary research priorities.

Phong’s involvement as a university research assistant at the Intelligence Software Engineering Laboratory since February 2024 highlights his active engagement in research at an early stage of his academic career. His recent publication, “Leveraging Local and Global Relationships for Corrupted Label Detection” (2025), reflects his ability to contribute to academic discourse and address challenges in machine learning—a field critical for advancements in artificial intelligence.

🎓 Education 

Phong Lam Nguyen Duy is pursuing his undergraduate degree in Computer Science at the University of Engineering and Technology, Vietnam National University, Hanoi. Since his enrollment in September 2022, he has been immersed in a rigorous academic curriculum focused on Information and Communication Technologies. The program emphasizes critical areas such as software development, data analysis, and systems design, providing him with a robust foundation in computer science. The university’s strong research culture has further fueled his interest in machine learning and automated data quality assurance. Phong Lam has actively engaged in research initiatives and academic projects, allowing him to apply his theoretical knowledge in practical contexts. The vibrant academic environment at Vietnam National University has cultivated his technical skills and problem-solving abilities, enabling him to stay at the forefront of technological advancements. He views his education as the stepping stone to a thriving career in computer science and artificial intelligence.

💼 Professional Experience 

Phong Lam Nguyen Duy is currently a research assistant at the Intelligence Software Engineering Laboratory, located in Hanoi, Vietnam. Since February 2024, he has been collaborating with faculty and fellow researchers to tackle challenges in automated data quality assurance and machine learning. His work primarily involves developing methodologies that improve data accuracy and reliability while optimizing machine learning models for large-scale datasets. Phong Lam’s role includes conducting literature reviews, designing experiments, and implementing cutting-edge algorithms to solve complex problems. His contributions are instrumental in advancing projects that integrate theoretical computer science with practical applications. As a research assistant, he has honed his analytical, programming, and communication skills, fostering his growth as a budding researcher. This professional experience has not only solidified his technical expertise but also instilled a passion for lifelong learning and innovation, preparing him for future endeavors in the rapidly evolving field of artificial intelligence.

🏅 Awards and Recognition 

Phong Lam Nguyen Duy has been recognized for his academic excellence, volunteer contributions, and research potential. His participation as a volunteer for the prestigious ICPC Asia Pacific Championship 2024 earned him commendations for his organizational skills and dedication to promoting computer science education. Additionally, his involvement in the Hanoi Green Summer 2023 showcased his commitment to community service, where he actively participated in environmental sustainability initiatives. Phong Lam’s academic achievements at Vietnam National University include consistent top performance in his courses, particularly in areas related to machine learning and data science. His appointment as a research assistant at the Intelligence Software Engineering Laboratory further highlights his aptitude and potential for innovation in the field. Through these accolades, Phong Lam has established himself as a well-rounded individual, excelling academically while contributing to society and pursuing impactful research in computer science.

🌍 Research Skills On Computer Science

Phong Lam Nguyen Duy possesses a strong skill set in computational research and data science. His expertise includes automated data quality assurance, where he develops methodologies to identify and correct errors in datasets, ensuring reliability for machine learning applications. Phong Lam has a keen understanding of machine learning algorithms and their optimization, with experience in designing and training models for diverse applications. His research focus also encompasses advancements in large language models, where he explores their capabilities for natural language processing tasks. As a research assistant, he has gained hands-on experience in experimental design, data preprocessing, and implementing scalable solutions. Proficient in programming languages like Python and R, Phong Lam is adept at leveraging tools such as TensorFlow and PyTorch for deep learning projects. His analytical mindset and problem-solving abilities make him an invaluable contributor to the ever-evolving landscape of artificial intelligence and computer science research.

📖 Publication Top Notes

Title: Leveraging local and global relationships for corrupted label detection
  • Journal: Future Generation Computer Systems
  • Year: 2025

Tariq Jamil | Machine Learning Award | Best Researcher Award

Mr. Tariq Jamil | Machine Learning Award | Best Researcher Award

Lead multilingual education at TensorDot Solutions, Pakistan🎓

Mr. Tariq Jamil is an accomplished AI/ML engineer and data scientist with a rich background in both academia and industry. His expertise spans a wide range of AI and machine learning domains, including deep learning, natural language processing, computer vision, and large language models. With a career marked by successful project management, innovative AI applications, and educational contributions, Mr. Jamil has consistently demonstrated his capacity for leadership and technical excellence. His experience as a project leader in various AI challenges and his role in training the next generation of AI professionals highlight his commitment to advancing the field.

Professional Profile 

🎓Education

Mr. Tariq Jamil holds a Post-Graduate Diploma in Data Science with Artificial Intelligence from NED University of Engineering and Technology, Pakistan, completed between December 2021 and June 2023. His coursework included an in-depth study of Python, data visualization, machine learning, deep learning, and computer vision. His capstone project involved the development of a chatbot using deep learning, specifically fine-tuning the Falcon large language model for customer service applications. Prior to this, Mr. Jamil earned a Bachelor of Engineering in Aviation Electronics with a specialization in Aerospace Technology from the same institution, graduating in December 1991. His academic foundation in digital electronics, communications, and quality systems, combined with his later specialization in AI, has provided him with a strong interdisciplinary background, enabling him to excel in both the engineering and data science fields.

💼Work Experience

Mr. Tariq Jamil has amassed a diverse and impactful work experience that spans multiple domains in the fields of AI, machine learning, and data science. Since January 2021, he has been working as a freelance AI/ML Engineer and Data Scientist in Karachi, Pakistan. In this role, Mr. Jamil has successfully managed multiple customer projects on platforms like Upwork and Freelancer.com, as well as with private clients. His work has involved a comprehensive range of AI technologies, including computer vision, video action detection, deep learning, natural language processing, and large language models. Notably, he contributed to the success of a pioneering marketing startup, True Insights, and developed advanced AI models for video crime scene detection and sign language recognition. In addition to his freelance work, Mr. Jamil served as an AI Trainer at NED University in Karachi from October 2023 to March 2024. He designed and taught graduate-level courses in Artificial Intelligence, focusing on deep learning, LLMs, Python, and computer vision. His teaching played a pivotal role in shaping the university’s Post Graduate Diploma program in Generative AI and the “DS & AI” program, where he taught classes on foundational and advanced AI concepts. Furthermore, Mr. Jamil has been an active contributor to Omdena, a global AI community, since July 2023. As the Chapter Lead for the UAE division, he led several innovative AI projects, including the development of a voice-enabled chatbot for Abu Dhabi Open Data Intelligence and an AI application for liver cancer histopathology detection. His role involved coordinating teams of data scientists and overseeing the technical execution of these projects, which led to significant advancements in AI applications for healthcare and data analytics.

🔍Research Focus 

Mr. Tariq Jamil’s research focus lies at the intersection of artificial intelligence (AI), machine learning (ML), and their practical applications across various domains. His work encompasses deep learning, natural language processing (NLP), computer vision, and large language models (LLMs), with a particular emphasis on developing AI solutions for real-world challenges. He has applied his expertise in projects ranging from video action detection and anomaly detection to chatbot development and healthcare diagnostics, such as histopathology and cervical cytology detection.

Mr. Jamil’s research is characterized by a commitment to innovation and impact. He has led projects that harness cutting-edge AI technologies, such as Transformers, YOLO, and OpenCV, to create applications that enhance automation, accuracy, and efficiency in fields like healthcare, security, and transportation. His work in fine-tuning LLMs for specific tasks, such as customer support and legal document processing, highlights his ability to customize AI models to meet the unique needs of different industries.

🏆Awards and Honors

Mr. Tariq Jamil has been recognized for his outstanding contributions to the fields of artificial intelligence and machine learning through various awards and honors. His leadership and innovation in AI, particularly in areas such as deep learning, natural language processing, and computer vision, have earned him accolades from both academic and professional communities. He has been acknowledged for his exceptional project management skills, notably in AI challenges that addressed critical real-world problems like healthcare diagnostics, vehicle inspection, and road safety.

In addition to his technical achievements, Mr. Jamil’s dedication to education has been celebrated, with honors highlighting his impactful teaching and mentoring roles at NED University. His efforts in training the next generation of AI professionals and his involvement in pioneering AI projects have further solidified his reputation as a leading expert in his field. These recognitions serve as a testament to Mr. Jamil’s commitment to excellence and his significant contributions to advancing the frontiers of AI technology.

Conclusion

Based on Mr. Tariq Jamil’s extensive experience, leadership in AI innovation, and dedication to education, he is a strong candidate for the Best Researcher Award. His ability to apply AI solutions to real-world problems, coupled with his commitment to advancing AI education, makes him a valuable asset to the AI community. With continued focus on publishing and expanding his professional network, Mr. Jamil could further elevate his contributions to the field, making him a highly deserving recipient of this award.

📖Publications : 

  1. Publication: “Fluid Coupled Structural Analysis and Optimization of Expanded Polystyrene-Fiber-Reinforced Composite Wing of an Unmanned Aerial Vehicle”
    • Authors: Jamil, T.; Iqbal, A.; Allauddin, U.; Saleem, S.; Ikhlaq, M.
    • Year: 2024
    • Journal: Mechanics of Composite Materials
    • Citations: 0
  2. Publication: “Effect of Glass Powder on the Compressive Strength and Drying Shrinkage Behavior of OPC- and LC3-50-Based Cementitious Composites of Various Strengths”
    • Authors: Ayub, T.; Jamil, T.; Ayub, A.; Mehmood, E.; Sheikh, M.D.
    • Year: 2024
    • Journal: Advances in Materials Science and Engineering
    • Citations: 0
  3. Publication: “Mechanical and Durability Properties of High-Strength Limestone Calcined Clay Cement (LC3) Concrete Containing Waste Glass Powder”
    • Authors: Ayub, A.; Ayub, T.; Jamil, T.; Khan, A.-U.-R.
    • Year: 2023
    • Journal: Iranian Journal of Science and Technology – Transactions of Civil Engineering
    • Citations: 2
  4. Publication: “Electromechanical characterizations of PEDOT

    and its nanocomposite thin films on a cost-effective polymer substrate for microelectromechanical systems (MEMS) applications”

    • Authors: Khan, S.T.; Mehdi, M.; Jamil, T.
    • Year: 2023
    • Journal: Express Polymer Letters
    • Citations: 1
  5. Publication: “Sustainable cementitious material with ultra-high content partially calcined limestone-calcined clay”
    • Authors: Qian, X.; Ruan, Y.; Jamil, T.; Hu, S.; Liu, Y.
    • Year: 2023
    • Journal: Construction and Building Materials
    • Citations: 13
  6. Publication: “Investigating the crumpling effect in honeycomb sandwich panels under bending loads using FEA technique”
    • Authors: Saqib, N.; Jamil, T.; Zai, B.A.
    • Year: 2023
    • Journal: Aeronautical Journal
    • Citations: 0
  7. Publication: “HEAT-TRANSFER ENHANCEMENT OF A SOLAR PARABOLIC TROUGH COLLECTOR USING TURBULATORS AND NANOPARTICLES: A NUMERICAL STUDY”
    • Authors: Allauddin, U.; Ikhlaq, M.; Jamil, T.; Mustafa, H.; Azeem, M.H.
    • Year: 2023
    • Journal: Journal of Enhanced Heat Transfer
    • Citations: 1
  8. Publication: “Comparative Study on LC3-50 with OPC Concrete Using Raw Materials from Pakistan”
    • Authors: Sheikh, M.D.; Jamil, T.; Ayub, T.; Bilal, S.M.; Hu, C.
    • Year: 2023
    • Journal: Advances in Materials Science and Engineering
    • Citations: 2
  9. Publication: “Numerical simulation and validation of MWCNT-CFRP hybrid composite structure in lightweight satellite design”
    • Authors: Iqbal, S.; Jamil, T.; Murtuza Mehdi, S.
    • Year: 2023
    • Journal: Composite Structures
    • Citations: 9
  10. Publication: “Virtual Captive Model tests for Maneuvering Prediction”
    • Authors: Khan, O.U.; Mansoor, A.; Zai, B.A.; Hussain, M.; Jamil, T.
    • Year: 2022
    • Journal: Journal of Maritime Research
    • Citations: 1