Jianglong Yang | Artificial Intelligence | Best Researcher Award

Posted on by sciencefather

Dr. Jianglong Yang | Artificial Intelligence | Best Researcher Award

Deputy Director of Collaborative Innovation Center at Beijing Wuzi University, China

Dr. Jianglong Yang is a prominent scholar in the field of logistics and supply chain management, currently serving at Beijing Wuzi University. With a Doctorate in Management, Dr. Yang has developed an outstanding portfolio of interdisciplinary research focused on intelligent logistics systems, optimization of e-commerce warehousing, and green supply chain innovations. His scholarly contributions include top-tier SCI and CSSCI publications, project leadership roles in national and municipal research programs, and a growing presence in China’s logistics innovation and policymaking circles.

Publication Profile 

Scopus

Educational Background 🎓

  • Degree: Doctor of Management

  • Major: Logistics and Supply Chain Management

  • Institution: Not explicitly stated, but affiliated with major universities like Beijing Wuzi University and Beijing University of Technology.

Professional Experience 💼

Dr. Jianglong Yang has held a series of prominent academic and leadership roles across China’s logistics and information management sectors. Since June 2024, he has been serving as the Party Secretary of the Information Management Teachers’ Party Branch at the School of Information, Beijing University of Technology, where he contributes to academic leadership and institutional governance. In August 2022, he was appointed Deputy Director of the Beijing Intelligent Logistics System Collaborative Innovation Center, a position that places him at the forefront of logistics innovation and policy research. He also currently serves as the Deputy Secretary-General of the Beijing System Engineering Society (since March 2024), reflecting his influence in advancing system-level thinking within logistics and engineering domains. In addition, Dr. Yang became an Assistant Researcher at the China Logistics Group Science and Technology Research Institute in June 2023, where he engages in cutting-edge research on national logistics strategies. Most recently, in May 2024, he was appointed Director of the Expert Committee of Beijing Huixu Technology Co., Ltd., further expanding his influence in industry-academic integration and application of intelligent logistics technologies.

Research Interests 🔬

  • Intelligent logistics systems

  • E-commerce packaging and warehousing optimization

  • Genetic algorithms and spatial modeling for logistics

  • Multimodal transportation under the Belt and Road Initiative

  • Green and circular economy in logistics

  • Smart supply chain coordination and service quality improvement

Awards and Honors🏆✨

  1. Outstanding Doctoral Dissertation Award, China Logistics Society Annual Conference (2024)

  2. First Prize, China Logistics Academic Annual Conference (2021) – Global Supply Chain Restructuring Research

  3. Research Awards, China Logistics Society & China Federation of Logistics and Purchasing (2021) – First and Third Prizes

  4. First-Class Doctoral Academic Scholarships, Two consecutive years (2019–2021)

Conclusion🌟

Dr. Jianglong Yang exemplifies the qualities of a leading researcher through his consistent output of high-impact publications, strategic roles in academic and industry organizations, and project leadership in pioneering logistics research. His work contributes significantly to the modernization of China’s intelligent logistics systems, with practical implications for sustainable e-commerce and supply chain management. His research excellence and active participation in the advancement of logistics innovation make him a strong candidate for competitive research awards and international collaborations.

Publications 📚

  • 📘 Monograph

    • Yang Jianglong, Liu Huwei, Zhou Li. Research on Intelligent Optimization of E-commerce Warehousing Packing Decision-making Based on Data Driven. Capital University of Economics and Business Press, Sept. 2023.
      (Academic monograph, 440,000 words – First Author)

  • 🧠 Journal Article

    • Yang Jianglong, Shan Man, Liang Kaibo, et al. “Research on intelligent decision-making of e-commerce three-dimensional packing based on spatial particle model.” Frontiers of Engineering Management Science and Technology, 2024, 43(06): 41–48.
      (First Author, CSSCI Core, A-level Journal)

  • 🧬 Algorithm & AI

    • Yang J, Liu H, Liang K, et al. “Variable neighborhood genetic algorithm for multi-order multi-bin open packing optimization.” Applied Soft Computing, 2024: 111890.
      (SCI Zone 1 TOP, First Author)

  • 🤖 AI in Logistics

    • Yang J, Liu H, Liang K, et al. “A Genetic Algorithm with Lower Neighborhood Search for the Three‐Dimensional Multiorder Open‐Size Rectangular Packing Problem.” International Journal of Intelligent Systems, 2024(1): 4456261.
      (SCI Zone II TOP, First Author)

  • 📦 E-commerce Optimization

    • Yang J, Liang K, Liu H, et al. “Optimizing e-commerce warehousing through open dimension management in a three-dimensional bin packing system.” PeerJ Computer Science, 2023, 9: e1613.
      (SCI Zone 4, First Author)

  • 🚨 Emergency Logistics

    • Liu Huwei, Zhou Li, Yang Jianglong*. “Research on hierarchical collaborative distribution of emergency materials under sudden public events.” Journal of Engineering Mathematics, 2024, 41(01): 53–66.
      (CSCD Core Journal, Corresponding Author)

  • 🚆 Multimodal Transport Policy

    • Yu Lin, Yang Jianglong. “Problems and policy recommendations for the development of multimodal transport under the ‘Belt and Road’ strategy.” SASAC Research Center, Oct. 2023.
      (Think Tank Report, Second Author)

  • 📡 Smart Picking Systems

    • Zhou Li, Yang Jianglong*. “Research on multi-channel intensive mobile shelf order picking based on genetic algorithm.” Operations Research and Management, 2021, 30(2):7.
      (CSCD Core Journal, Corresponding Author)

  • 🧮 Batch Order Optimization

    • Yang J, Zhou L, Liu H. “Hybrid genetic algorithm-based optimisation of the batch order picking in a dense mobile rack warehouse.” PLOS ONE, 2021, 16.
      (SCI Zone 2, First Author)

  • 🔐 Security in IoT

    • Yang J, Yang W, Liu H, et al. “Design and Simulation of Lightweight Identity Authentication Mechanism in Body Area Network.” Security and Communication Networks, 2021(3):1–18.
      (SCI Zone 4, First Author)

 

 

 

 

Muhammad Kashif Jabbar | Artificial Intelligence | Best Researcher Award

Posted on by sciencefather

Mr. Muhammad Kashif Jabbar | Artificial Intelligence | Best Researcher Award

Doctor Student at Shenzhen University, China

Muhammad Kashif Jabbar is a research-focused professional specializing in medical image processing. With a strong foundation in Electronics and Information Engineering, he has contributed significantly to research, particularly in developing transfer learning-based models for diabetic retinopathy diagnosis. Muhammad Kashif is multilingual, skilled in technical domains, and experienced in international collaborations.

Publication Profile 

Scopus

Educational Background 🎓

  1. Shenzhen University
    • Degree: Ph.D. in Electronics and Information Engineering
    • Specialization: Medical Image Processing
    • Session: September 2018 – June 2022
  2. Beijing University of Technology (BJUT)
    • Degree: Master’s in Information and Communication Engineering
    • Specialization: Medical Image Processing
    • Session: September 2018 – June 2022
  3. Superior University of Lahore
    • Degree: Master’s in Information Technology (MIT)
    • Session: 2014 – 2016

Professional Experience 💼

  • Worked extensively on developing advanced methodologies in medical image processing.
  • Conducted research focusing on diabetic retinopathy diagnosis, utilizing transfer learning techniques.
  • Developed applications in web development and database management.

Research Interests 🔬

  • Medical Image Processing
  • Transfer Learning for Disease Diagnosis
  • Data Security in Medical Imaging (Steganography and Cryptography)
  • Artificial Intelligence and Optimization Algorithms in Healthcare Applications

Awards and Honors🏆✨

  • Passed HSK4 Chinese Language Proficiency Exam (2018).
  • Performed at the 14th BJUT International Day opening ceremony.
  • Recognized for successful completion of the 2019 International Students Exploring Haidian program.

Certifications

  1. HSK4 Chinese Language Certification – Beijing University of Technology
  2. Graphic Design – ARENA Multimedia, Islamabad Campus (2015)

Conclusion🌟

Muhammad Kashif Jabbar is a highly skilled researcher with a passion for advancing medical technologies using artificial intelligence and image processing techniques. His education and expertise make him a valuable asset to organizations focused on cutting-edge medical research and innovation.

Publications 📚

📡 Radar and Engineering

  1. Enhancing Radar Tracking Accuracy Using Combined Hilbert Transform and Proximal Gradient Methods
    • Authors: Jabbar, A., Jabbar, M.K., Jabbar, A., Mahmood, T., Rehman, A.
    • Journal: Results in Engineering, 2024, 24, 103479.
    • 🌐 Type: Article (Open Access)
    • 📊 Citations: 0

👁️ Ophthalmology and AI

  1. A Retinal Detachment Based Strabismus Detection Through FEDCNN
    • Authors: Jabbar, A., Jabbar, M.K., Mahmood, T., Nobanee, H., Rehman, A.
    • Journal: Scientific Reports, 2024, 14(1), 23255.
    • 🌐 Type: Article (Open Access)
    • 📊 Citations: 0

🔄 Errata and Corrections

  1. Correction to: Deep Transfer Learning-Based Automated Diabetic Retinopathy Detection Using Retinal Fundus Images in Remote Areas
    • Authors: Jabbar, A., Naseem, S., Li, J., Rehman, A., Saba, T.
    • Journal: International Journal of Computational Intelligence Systems, 2024, 17(1), 145.
    • 🌐 Type: Erratum (Open Access)
    • 📊 Citations: 1

  2. Correction to: Transfer Learning-Based Model for Diabetic Retinopathy Diagnosis Using Retinal Images

    • Authors: Jabbar, M.K., Yan, J., Xu, H., Ur Rehman, Z., Jabbar, A.
    • Journal: Brain Sciences, 2024, 14(8), 777.
    • 🌐 Type: Erratum (Open Access)
    • 📊 Citations: 0

🧠 Diabetic Retinopathy and AI Models

  1. Transfer Learning-Based Model for Diabetic Retinopathy Diagnosis Using Retinal Images
    • Authors: Jabbar, M.K., Yan, J., Xu, H., Rehman, Z.U., Jabbar, A.
    • Journal: Brain Sciences, 2022, 12(5), 535.
    • 🌐 Type: Article (Open Access)
    • 📊 Citations: 49

 

 

 

Sushil Kumar | Machine Learning | Best Researcher Award

Posted on by sciencefather

Dr. Sushil Kumar | Machine Learning | Best Researcher Award

Assistant Professor at Central University of Haryana, India

Dr. Sushil Kumar is an Assistant Professor in the Department of Computer Science and Engineering at the Central University of Haryana, having joined on December 2, 2022. With a rich experience of 19 years in teaching, he specializes in Information Retrieval, Machine Learning, and Distributed Computing. Dr. Kumar holds a B.Tech, M.Tech, and Ph.D. in Computer Science and Engineering. He has published 7 papers in international journals and 1 book chapter, and has guided 16 Master’s students in their research. He has actively participated in 25 seminars and conferences, and organized 5 academic events. In addition, he has been recognized with the Youth Red Cross Award from the Honorable Governor of Haryana for 2016-17 and 2019-20. Currently, he also serves as the NBA Co-ordinator and NAAC Co-ordinator at the university.

Publication Profile : 

Google Scholar

Education 🎓

Dr. Sushil Kumar holds a B.Tech, M.Tech, and Ph.D. in Computer Science and Engineering, equipping him with a solid foundation in the field of technology and research.

Professional Experience💼

Assistant Professor at Central University of Haryana since 02-12-2022
With 19 years of teaching experience, Dr. Sushil Kumar has been dedicated to nurturing young minds in the area of computer science. His expertise in Information Retrieval, Machine Learning, and Distributed Computing has shaped his teaching methodology. While his focus remains on academia, he has not been involved in industry work yet. He has also taken up additional responsibilities as NBA Co-ordinator and NAAC Co-ordinator, ensuring quality assurance and accreditation standards in the department.

Research Interests 🔬

🔍 Information Retrieval
🤖 Machine Learning
🌐 Distributed Computing

Dr. Sushil Kumar’s research interests are focused on the areas of Information Retrieval, where he aims to improve search and data retrieval systems, Machine Learning, and the development of efficient algorithms for Distributed Computing systems.

Publications Top Notes 📚

  1. Kumar, S., Aggarwal, M., Khullar, V., Goyal, N., Singh, A., & Tolba, A. (2023). Pre-Trained Deep Neural Network-Based Features Selection Supported Machine Learning for Rice Leaf Disease Classification. Agriculture, 13(5), 23.
  2. Kumar, S., & Bhatia, K. K. (2020). Semantic similarity and text summarization-based novelty detection. SN Applied Sciences, 2(3), 332.
  3. Kumar, S., & Chauhan, N. (2012). A context model for focused web search. International Journal of Computer Technology, 2(3).
  4. Gupta, C., Khullar, V., Goyal, N., Saini, K., Baniwal, R., Kumar, S., & Rastogi, R. (2023). Cross-Silo, Privacy-Preserving, and Lightweight Federated Multimodal System for the Identification of Major Depressive Disorder Using Audio and Electroencephalogram. Diagnostics, 14(1), 43.
  5. Kumar, S., & Bhatia, K. K. (2019). Clustering-based approach for novelty detection in text documents. Asian Journal of Computer Science and Technology, 8(2), 116-121.
  6. Dasari, K., Srikanth, V., Veramallu, B., Kumar, S. S., & Srinivasulu, K. (2014). A novelty approach of symmetric encryption algorithm. Proceedings of the International Conference on Information Communication and Embedded Systems (ICICES).
  7. Kumar, S., & Anand, S. (2006). Implementing Shared Data Services (SDS): A Proposed Approach. 2006 IEEE International Conference on Services Computing (SCC’06), 365-372.
  8. Singh, S., Kundra, H., Kundra, S., Pratima, P. V., Devi, M. V. A., Kumar, S., & Hassan, M. (2024). Optimal trained ensemble of classification model for satellite image classification. Multimedia Tools and Applications, 1-22.
  9. Kumar, S., & Bhatia, K. K. (2018). Document-to-Sentence Level Technique for Novelty Detection. In Speech and Language Processing for Human-Machine Communications: Proceedings (pp. xx-xx).
  10. Chawla, M., Panda, S. N., Khullar, V., Kumar, S., & Bhattacharjee, S. B. (2024). A lightweight and privacy-preserved federated learning ecosystem for analyzing verbal communication emotions in identical and non-identical databases. Measurement: Sensors, 34, 101268.
  11. Kumar, S. S. (2023). System Oriented Social Scrutinizer: Centered Upon Mutual Profile Erudition. International Journal on Recent and Innovation Trends in Computing and Communication, 11(9), 2007–2017.
  12. Kumar, S. (2021). Design of novelty detection techniques for optimized search engine results. JC Bose University.
  13. Ishuka, S. K., & Bhatia, K. K. (2019). A Novel Approach for Novelty Detection Using Extractive Text Summarization. Journal of Emerging Technologies and Innovative Research, 6(6), 141-154.
  14. Pooja, K. K. B., & Kumar, S. (2019). Hashing and Clustering Based Novelty Detection. SSRG International Journal of Computer Science and Engineering, 6(6), 1-9.
  15. Kumar, S., & Bhatia, K. K. (2019). Clustering Based Approach for Novelty Detection in Text Documents. Asian Journal of Computer Science and Technology, 8(2), 121-126.

 

 

 

Kanaga Suba Raja S | Deep Learning | Best Researcher Award

Posted on by sciencefather

Prof. Dr. Kanaga Suba Raja S | Deep Learning | Best Researcher Award

Professor at Srm Institute Of Science And Technology Tiruchirappalli, India

Dr. S. Kanaga Suba Raja is a dedicated computer science educator and researcher with a passion for innovation and technology. With a rich history of academic leadership and groundbreaking research, he continues to inspire the next generation of engineers. 🌍💡

Publication Profile : 

Scopus

Orcid

Google Scholar

 

🎓 Educational Background :

Dr. Kanaga Suba Raja completed his Ph.D. in Computer Science and Engineering from Manonmaniam Sundaranar University in 2013. He holds a Master’s degree in Computer Science and Engineering from Noorul Islam College of Engineering (2006) and a Bachelor’s degree from The Rajaas Engineering College (2003).

💼 Professional Experience :

With over 19 years of experience in academia, Dr. Kanaga Suba Raja has held several prominent positions, including Professor and Head of the Department of Computer Science and Engineering at SRM Institute of Science and Technology, and Associate Dean at the School of Computing. His career spans roles as Associate Professor and Lecturer at various institutions under Anna University, where he contributed significantly to curriculum development and academic administration.

📚 Research Interests : 

Dr. Kanaga Suba Raja specializes in artificial intelligence, cloud computing, and biomedical engineering. He has published over 100 research papers, received numerous citations, and holds patents related to cloud computing and medical technologies.

📝 Publication Top Notes :

  1. Priya, J., Kanaga Suba Raja, S., & Usha Kiruthika, S. (2024). State-of-art technologies, challenges, and emerging trends of computer vision in dental images. Computers in Biology and Medicine, 178. https://doi.org/10.1016/j.compbiomed.2024.108800
  2. Priya, J., Kanaga Suba Raja, S., & Sudha, S. (2024). An intellectual caries segmentation and classification using modified optimization-assisted transformer denseUnet++ and ViT-based multiscale residual denseNet with GRU. Signal, Image and Video Processing (SIViP). https://doi.org/10.1007/s11760-024-03227-9
  3. Chandra, & Kanaga Suba Raja, S. (2024). HHECC-AES: A novel hybrid cryptography scheme for developing the secured wireless body area network using heuristic-aided blockchain model. Ad Hoc & Sensor Wireless Networks, 59, 141–179. https://doi.org/10.32908/ahswn.v59.10477
  4. Sandhiya, B., Kanaga Suba Raja, S., Shruthi, K., & Praveena Rachel Kamala, S. (2024). Brain tumour segmentation and classification with reconstructed MRI using DCGAN. Biomedical Signal Processing and Control, 92. https://doi.org/10.1016/j.bspc.2024.106005
  5. Sandhiya, B., & Kanaga Suba Raja, S. (2024). Deep learning and optimized learning machine for brain tumor classification. Biomedical Signal Processing and Control, 89(1). https://doi.org/10.1016/j.bspc.2023.105778
  6. Kausalya, K., & Kanaga Suba Raja, S. (2024). OTRN-DCN: An optimized transformer-based residual network with deep convolutional network for action recognition and multi-object tracking of adaptive segmentation using soccer sports video. International Journal of Wavelets, Multiresolution and Information Processing, 22(1). https://doi.org/10.1142/S0219691323500340
  7. Chandra, B., & Kanaga Suba Raja, S. (2023). Security in wireless body area network (WBAN) using blockchain. IETE Journal of Research. https://doi.org/10.1080/03772063.2023.2233472
  8. Hema, M., & Kanaga Suba Raja, S. (2023). A quantitative approach to minimize energy consumption in cloud data centres using VM consolidation algorithm. KSII Transactions on Internet and Information Systems, 17(2), 312-334. https://doi.org/10.3837/tiis.2023.02.002
  9. Pushpa, S. X., & Kanaga Suba Raja, S. (2022). Enhanced ECC based authentication protocol in wireless sensor network with DoS mitigation. Cybernetics and Systems, 53(2). https://doi.org/10.1080/01969722.2022.2055403
  10. Hema, M., & Kanaga Suba Raja, S. (2022). An efficient framework for utilizing underloaded servers in compute cloud. Computer Systems Science and Engineering, 43(5). https://doi.org/10.32604/csse.2023.024895
  11. Vivekanandan, M., & Kanaga Suba Raja, S. (2022). Virtex-II Pro FPGA-based smart agricultural system. Wireless Personal Communications, 125(1), 119–141. https://doi.org/10.1007/s11277-022-09544-x
  12. Pushpa, S. X., & Kanaga Suba Raja, S. (2022). Elliptic curve cryptography-based authentication protocol enabled with optimized neural network-based DoS mitigation. Wireless Personal Communications, 124(27). https://doi.org/10.1007/s11277-021-08902-5
  13. Balaji, V., & Kanaga Suba Raja, S. (2021). Recommendation learning system model for children with autism. Intelligent Automation & Soft Computing, 31(2). https://doi.org/10.32604/iasc.2022.020287
  14. Valarmathi, K., & Kanaga Suba Raja, S. (2021). Resource utilization prediction technique in cloud using knowledge-based ensemble random forest with LSTM model. Concurrent Engineering: Research and Applications. https://doi.org/10.1177/1063293X211032622
  15. Kanaga Suba Raja, S., & Virgin Louis, B. A. (2021). A review of call admission control schemes in wireless cellular networks. Wireless Personal Communications, 120(4), 3369–3388. https://doi.org/10.1007/s11277-021-08618-6

 

 

 

Rafael Natalio Fontana Crespo | Artificial Intelligence | Young Scientist Award

Posted on by sciencefather

Mr. Rafael Natalio Fontana Crespo | Artificial Intelligence | Young Scientist Award

PhD Student at Politecnico di Torino, Italy

Rafael Natalio Fontana Crespo is a dedicated and sociable Ph.D. student specializing in Computer and Control Engineering at Politecnico di Torino. With a strong academic background in mechatronics and practical experience in electrical energy analysis, he is passionate about tackling complex challenges through innovative solutions. 🌐💡

Publication Profile : 

Orcid

 

🎓 Educational Background :

Rafael is currently pursuing a Ph.D. in Computer and Control Engineering at Politecnico di Torino, Italy, since May 2022. He previously obtained a Master’s Degree in Mechatronic Engineering from the same institution, graduating with 110/110 cum laude in July 2022. His master’s thesis focused on designing and developing a distributed software platform for additive manufacturing. Rafael studied Electromechanical Engineering at the Universidad Nacional de Córdoba, Argentina, where he also completed a double degree program.

💼 Professional Experience :

Rafael gained practical experience during his internship at EPEC (Empresa Provincial de Energía de Córdoba) in Argentina, where he worked in the Statistics and Technical Department from May 2020 to May 2021. He was involved in analyzing thermal images of electrical components to prevent failures, contributing to the overall safety and efficiency of electrical systems.

📚 Research Interests : 

Rafael’s research interests lie at the intersection of computer engineering, control systems, and mechatronics, particularly focusing on additive manufacturing, machine learning applications in energy systems, and the optimization of neural networks.

📝 Publication Top Notes :

      1. Fontana Crespo, R.N., E. Patti, S. Di Cataldo, D. Cannizzaro. (2022). Design and Development of a Distributed Software Platform for Additive Manufacturing. Master’s Thesis, Politecnico di Torino.
      2. Fontana Crespo, R.N. (2023). Machine Learning in Energy Applications. Course Exam Paper, Politecnico di Torino.
      3. Fontana Crespo, R.N. (2023). IoT Platforms for Spatial Analytics in Smart Energy Systems. Course Exam Paper, Politecnico di Torino.
      4. Fontana Crespo, R.N. (2023). Optimized Execution of Neural Networks at the Edge. Course Exam Paper, Politecnico di Torino.
      5. Fontana Crespo, R.N. (2023). Adversarial Training of Neural Networks. Course Exam Paper, Politecnico di Torino.