Weijia Han | Design of Experiments (DOE) | Research Excellence Award

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Assoc Prof. Dr. Weijia Han | Design of Experiments (DOE) | Research Excellence Award

Wuhan Textile University | China

Assoc Prof. Dr. Weijia Han is an accomplished researcher in physics, materials science, and microelectronics, currently serving as a Lecturer at the School of Microelectronics, Wuhan Textile University, China. He has developed a strong international academic background through his roles as a Postdoctoral Researcher in Experimental Physics and Functional Materials at the Brandenburg University of Technology in Germany, a Guest Scientist at the Leibniz Institute for High Performance Microelectronics in Frankfurt (Oder), and a Research Associate at Osnabrück University as well as the Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences. He holds a PhD in Physical Chemistry from Osnabrück University, a Master’s degree in Applied Physics from Xiangtan University, and a Bachelor’s degree in Physics from Huanggang Normal University. His research focuses on plasmonic and photonic nanostructures, including plasmonic titanium nitride nanohole arrays, metamaterial narrowband absorbers, graphene-based composites, and insect-inspired nanostamping technologies. His work spans design, simulation, nanofabrication, and extensive optical and structural characterization, using tools such as electron microscopy, atomic force microscopy, Raman imaging, X-ray diffraction, FTIR, spectroscopy, and advanced photocurrent measurement systems. He has contributed significantly to several national and international projects involving on-chip optical sensors, CMOS-compatible plasmonic devices, and refractive-index sensor engineering. His scholarly output includes numerous peer-reviewed publications in high-impact journals, and his research performance is reflected in an h-index of 4, with approximately 49 citations across over 11 scientific documents, demonstrating strong global visibility and influence. In addition, he is co-inventor on a Chinese patent related to black phosphorus flake preparation. Known for his creativity, analytical strengths, and problem-solving skills, he is highly self-motivated, collaborative, and deeply committed to innovation in electronic engineering, sensor technology, and advanced material systems.

Profiles: Scopus | Google Scholar 

Featured Publications

Michael Pitton | Descriptive and Inferential Statistics | Best Researcher Award

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Prof. Dr. Michael Pitton | Descriptive and Inferential Statistics | Best Researcher Award

Medical University of Mainz | Germany

Professor Dr. Michael Pitton is a distinguished German physician-scientist and expert in diagnostic and interventional radiology. A graduate of the Johannes Gutenberg University Mainz, he completed his medical studies and advanced clinical training in internal medicine, cardiology, radiology, and neuroradiology at leading German university hospitals, including the University Medical Center Mainz and the Deutsches Herzzentrum Berlin. His academic achievements include a habilitation on functional and morphological aspects of endovascular aneurysm therapy, followed by his appointment as university lecturer and senior consultant in interventional radiology. Professor Pitton has held successive leadership positions and currently serves as the Acting Director of the Department of Diagnostic and Interventional Radiology and Head of the Section of Interventional Radiology at the University Medical Center Mainz. He also holds European Board Certification in Interventional Radiology (EBIR) and the European Certification for Endovascular Specialists (CIRSE) and is a certified DEGIR instructor across all modules. Combining clinical excellence with managerial insight, he earned a Master of Health Business Administration, reflecting his engagement in healthcare management and innovation. Professor Pitton has an extensive scientific record, with approximately 127 publications, an h-index of around 33, and more than 6,771 citations, underscoring his influence in vascular and interventional radiology. His research contributions have advanced the understanding and treatment of aneurysms, transjugular intrahepatic portosystemic shunt (TIPS) interventions, and image-guided oncologic therapies. Recognized with numerous national and international awards, his work bridges academic medicine, translational research, and health leadership. Professor Pitton exemplifies excellence in clinical radiology, academic scholarship, and interdisciplinary collaboration, contributing significantly to the development of interventional radiology in Europe.

Profiles: Scopus | Orcid

Featured Publications

Graafen, D., Bart, W., Halfmann, M. C., Müller, L., Hobohm, L., Yang, Y., Neufang, A., Espinola-Klein, C., Pitton, M. B., Kloeckner, R., Varga-Szemes, A., & Emrich, T. (2022). In vitro and in vivo optimized reconstruction for low-keV virtual monoenergetic photon-counting detector CT angiography of lower legs.

Gairing, S. J., Kuchen, R., Müller, L., Cankaya, A., Weerts, J., Kapucu, A., Sachse, S., Zimpel, C., Stoehr, F., Pitton, M. B., Mittler, J., Straub, B. K., Marquardt, J. U., Schattenberg, J. M., Labenz, C., Kloeckner, R., Weinmann, A., Galle, P. R., Wörns, M. A., & Foerster, F. (2022.). 13C-Methacetin breath test predicts survival in patients with hepatocellular carcinoma undergoing transarterial chemoembolization.

Müller, L., Hahn, F., Mähringer-Kunz, A., Stoehr, F., Gairing, S. J., Foerster, F., Weinmann, A., Galle, P. R., Mittler, J., Pinto Dos Santos, D., Pitton, M. B., Düber, C., Fehrenbach, U., Auer, T. A., Gebauer, B., & Kloeckner, R. (2022). Prevalence and clinical significance of clinically evident portal hypertension in patients with hepatocellular carcinoma undergoing transarterial chemoembolization.

Kiran Sree Pokkuluri | Machine Learning and Statistics | Excellence in Research Award

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Prof. Dr. Kiran Sree Pokkuluri | Machine Learning and Statistics | Excellence in Research Award

Shri Vishnu Engineering College For Women | India

Prof. Dr. Kiran Sree Pokkuluri is a distinguished academician, researcher, and innovator in the field of Artificial Intelligence and Machine Learning with an illustrious career of academic and research excellence. Currently serving as Professor and Head of the Department of Computer Science and Engineering at Shri Vishnu Engineering College for Women, he has significantly contributed to advancing computational intelligence and data-driven innovation in academia and industry. He holds a Ph.D. in Artificial Intelligence from JNTU-Hyderabad and has an impressive scholarly record with over 100 research publications in reputed SCI and Scopus-indexed journals, a citation count exceeding 653, an h-index above 13, and an Documents exceeding 152, reflecting the global impact of his research. His research areas include Deep Learning, Healthcare Analytics, Bioinformatics, IoT Power Optimization, Big Data Analytics, and Cloud Computing. Dr. Sree has authored six textbooks with ISBNs on Artificial Intelligence, Machine Learning, and Deep Learning, and has filed and published six patents in the domains of AI and intelligent systems. His innovations such as the Hybrid Deep Neural ZF Network (HDNZF-Net) have set new benchmarks in real-time speech enhancement for speech-impaired individuals and IoT optimization. He has completed five major funded projects and collaborated with premier institutions including Stanford University through the UIF program, fostering cross-disciplinary innovation. A recognized thought leader, Dr. Sree serves as Editor-in-Chief, editorial board member, and reviewer for multiple international journals. His remarkable achievements have earned him prestigious recognitions like the Bharat Excellence Award and Rashtriya Ratan Award, and he has been featured in Marquis Who’s Who in the World. As Global Vice President of the World Statistical Data Analysis Research Association (WSA) and a member of professional bodies such as IEEE, ISTE, CSI, and IAENG, Dr. Kiran Sree continues to inspire excellence in AI-driven research, education, and technological innovation.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

Venkatachalam, B., Pokkuluri, K. S., Suguna Kumar, S., Dhandapani, A., & Bhonsle, M. (2025). Adaptive fuzzy heuristic algorithm for dynamic data mining in IoT integrated big data environments. Journal of Fuzzy Extension and Applications, 6(3), 615–636.

Pokkuluri, K. S., Sarkar, P., Birchha, V., Mathariya, S. K., Veeramachaneni, V., & others. (2025). Intelligent reasonable optimization for virtual machine provisioning in hybrid cloud using fuzzy AHP and cost-effective autoscaling. SN Computer Science, 6(7), 1–15.

Sivanuja, M., Raju, P. J. R. S., Prasad, M., RR, P. B. V., Kumar, K. S., & Pokkuluri, K. S,. (2025). A novel ensemble-based deep learning framework combining CNN and transfer learning models for enhanced wildfire detection. In Proceedings of the 2025 International Conference on Computational Robotics, Testing and Applications.

Alzubi, J. A., Pokkuluri, K. S., Arunachalam, R., Shukla, S. K., Venugopal, S., & others. (2025). A generative adversarial network-based accurate masked face recognition model using dual scale adaptive efficient attention network. Scientific Reports, 15(1), 17594.

Pokkuluri, K. S., Chandanan, A. K., Mishra, A. K., Jyothi, D., Lavanya, M. S. S. L., & others. (2025). Deep learning-enhanced intrusion detection and privacy preservation for IIoT networks. In Proceedings of the 2025 4th International Conference on Distributed Computing and Electrical Systems.

Tao Zhong | Machine Learning and Statistics | Best Researcher Award

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Dr. Tao Zhong | Machine Learning and Statistics | Best Researcher Award

Sun Yat-sen University | China

Dr. Zhong Tao is a dedicated interdisciplinary researcher specializing in environmental engineering, material science, and computational modelling. A native of Chongqing, China, he is a member of the Communist Party of China and currently based in Guangzhou. He earned his Bachelor’s degree in Environmental and Ecological Engineering with a minor in Computer Science and Technology from Sichuan Agricultural University, followed by a Master’s in Environmental Science and Engineering from Guangxi University under Prof. Yu Zebin, and is pursuing his Doctor of Engineering (Ph.D.) in Resources and Environment at Sun Yat-sen University under Prof. He Chun. His research focuses on the design and development of high-activity environmental functional materials for atmospheric and water pollutant removal, catalytic ozonation, and clean-energy catalysis, including hydrogen production via water splitting. He also employs Density Functional Theory (DFT) to analyze catalytic materials and pollutant molecular structures, building structure–property relationships to guide experiments. Dr. Zhong has contributed to 31 SCI-indexed papers, including 11 as first or co-first author, and applied for 5 patents, with 4 granted. His ongoing research includes national and provincial projects as principal investigator or key contributor. He has received multiple national and university-level scholarships and awards for academic excellence, innovation, and leadership. His Scopus metrics reflect a growing international influence, with an h-index of 10, 22 documents, and over 343 citations, underscoring his strong academic productivity. Known for his rigorous research approach, interdisciplinary collaboration, and mentoring of peers and students, Dr. Zhong also pursues interests in history, literature, and sports, maintaining an optimistic, resilient, and disciplined outlook that complements his scientific career.

Profiles: Scopus 

Featured Publications

Guo, X., Yao, Z., Long, X., Zeng, L., Wang, C., Fang, Z., Zhong, T., Tian, S., Shu, D., & He, C. (2025). Recent advances in tailored nanostructured ozonation catalysts for enhanced VOCs removal: Synergistic optimization of scale configuration and electronic microenvironment.

Zhong, T., Yao, Z., Zeng, L., Zhao, H., Long, X., Li, T., Tian, S., & He, C. (2025). Manipulating spin-configuration via electron reverse overflow to dynamically tune the adsorption behavior of sulfur-containing intermediates for enhanced sulfur resistance.

Kuruba Chandrakala | Machine Learning and Statistics | Best Researcher Award

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Dr. Kuruba Chandrakala | Machine Learning and Statistics | Best Researcher Award

Siddhartha Academy of Higher Education | India

Dr. Kuruba Chandrakala is an emerging researcher in the domains of computer vision, deep learning, and medical image processing, currently serving as Assistant Professor (Selection Grade) in the CSE department at Siddhartha Academy of Higher Education, Vijayawada. She earned her Ph.D. from NIT Tiruchirappalli, preceded by M.Tech in Computer Science and Engineering with distinction from JNTU Kakinada and B.Tech in the same discipline from JNTU Anantapur. She has qualified both NET and APSET examinations. Her professional trajectory includes roles as Head of Department (CSE-AIML) at Vignan’s Nirula Institute of Technology & Science for Women and previous teaching appointments at VNITSW and SITAM, along with industry experience as a System Engineer with Tata Consultancy Services. Her publication record comprises five Scopus indexed papers, four of which are in SCIE journals, two IEEE conference papers, and one book chapter; she also holds one patent. Her Scopus metrics include an h-index of 4, 10 documents, and 150 citations. Her research has addressed areas such as diabetic retinopathy segmentation, robust blood vessel detection, and image enhancement through deep learning architectures. She teaches courses including Deep Learning, Machine Learning, Big Data Analytics, Cloud Computing, and programming in C, C++, Java, and Python. She has earned numerous certifications from NPTEL, Coursera, Microsoft, IBM, and Wipro and received awards such as the NPTEL Discipline Star and Wipro Project Excellence Award. Her leadership and mentoring roles include serving as a mentor for Wipro TalentNext, nodal officer for Microsoft Upskilling and APSCHE virtual internship programs, and coordinator for various hackathons. She is a life member of professional bodies such as CSI, ISTE, IAENG, and IET, and has delivered several invited and guest lectures, contributing significantly to academic excellence and research advancement.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

Chandrakala, K., & Gopalan, N. P. (2025). 3DECNN: A novel method for segmentation of diabetic retinopathy in retinal fundus images using 3D-edge CNN. Neural Computing and Applications.

Kuruba, C., Sharmila, S. K., Mounika, V., Aswini, D., & Poojitha, G. (2023). Three layered security model to prevent credit card fraud using LBPH and CNN-ResNet architecture. International Conference on Hybrid Intelligent Systems, 422–428.

Dharmaiah, K., Mebarek-Oudina, F., Sreenivasa Kumar, M., & Chandra Kala. (2023). Nuclear reactor application on Jeffrey fluid flow with Falkner-Skan factor, Brownian and thermophoresis, non-linear thermal radiation impacts past a wedge. Journal of the Indian Chemical Society, 100(2), 117.

Kuruba, C., & Gopalan, N. P. (2023). Robust blood vessel detection with image enhancement using relative intensity order transformation and deep learning. Biomedical Signal Processing and Control, 86, 105195.

Kuruba, C., Pushpalatha, N., Ramu, G., Suneetha, I., Kumar, M. R., & Harish, P. (2023). Data mining and deep learning-based hybrid health care application. Applied Nanoscience, 13(3), 2431–2437.