Zhihao Kang | Deep Learning | Best Researcher Award

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Ms. Zhihao Kang | Deep Learning | Best Researcher Award

Ms. Zhihao Kang | Deep Learning | Ph.D at Tianjin University | China

Ms. Zhihao Kang is an accomplished academic and researcher at Tianjin University, China, specializing in urban perception modeling, AI-driven landscape design, ecological sensitivity mapping, and social media-based urban analytics. She earned her Ph.D. in Environmental Science and Urban Planning from Tianjin University, where her doctoral work focused on integrating deep learning frameworks and spatial modeling to evaluate visual and ecological sensitivity across urban landscapes. Ms. Kang has developed extensive professional experience through her participation in multi-institutional and cross-border projects on urban heat island prediction, sustainable landscape design, and spatial data visualization, collaborating with international research teams across Asia and Europe. Her research interests span artificial intelligence applications in environmental studies, geospatial data analysis, climate resilience planning, and the use of social media data for real-time urban perception modeling. In terms of research skills, Ms. Kang demonstrates expertise in machine learning algorithms, remote sensing, GIS-based urban analysis, CA–Markov modeling, and Google Earth Engine-based predictive simulations. She has co-authored multiple peer-reviewed papers indexed in Scopus and IEEE, contributing to global discourse on sustainable urbanization and digital environmental mapping. Her publications have received over 130 citations, reflecting growing recognition within the academic community. Ms. Kang’s work has earned her institutional awards and research fellowships that acknowledge her excellence in applied geospatial analytics and AI innovation. She is also an active member of IEEE and ACM, engaging in initiatives promoting smart and sustainable urban environments. With a strong interdisciplinary foundation and a commitment to technological innovation, Ms. Zhihao Kang continues to advance the frontier of urban informatics research, contributing impactful insights that support ecological resilience and evidence-based urban policy design.

Academic Profile: Google Scholar

Featured Publications:

  1. Ullah, N., Khan, J., Saeed, I., Zada, S., Xin, S., Kang, Z., & Hu, Y. K. (2022). Gastronomic tourism and tourist motivation: Exploring northern areas of Pakistan. International Journal of Environmental Research and Public Health, 19(13), 7734. Citations: 84

  2. Ullah, N., Siddique, M. A., Ding, M., Grigoryan, S., Khan, I. A., Kang, Z., Tsou, S., et al. (2023). The impact of urbanization on urban heat island: Predictive approach using Google Earth Engine and CA-Markov modelling (2005–2050) of Tianjin City, China. International Journal of Environmental Research and Public Health, 20(3), 2642. Citations: 50

 

 

Pratiksha Chaudhari | Machine Learning | Best Researcher Award

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Ms. Pratiksha Chaudhari | Machine Learning | Best Researcher Award

Ms. Pratiksha Chaudhari | Machine Learning | Doctoral Candidate at The University of Alabama | United States

Ms. Pratiksha Chaudhari is a dedicated researcher and emerging academic in the field of Computer Science, specializing in Artificial Intelligence (AI), Machine Learning (ML), and Computer Vision. She is currently pursuing her Ph.D. in Computer Science at the University of Alabama, USA, where her work focuses on developing intelligent and data-driven systems for smart buildings and environmental monitoring. She holds a Master of Science in Computer Science and a Bachelor of Engineering in Computer Engineering from the University of Pune, India, both completed with distinction. Throughout her academic career, Ms. Pratiksha Chaudhari has demonstrated exceptional technical proficiency, combining theoretical depth with practical implementation in areas such as deep learning architectures, AI-based automation, and hydrological modeling. Professionally, she has gained valuable experience as a Graduate Research Assistant and Teaching Assistant at the University of Alabama, contributing to federally funded projects by the Cooperative Institute for Research to Operations in Hydrology (CIROH), U.S. Geological Survey (USGS), and the Great Lakes Protection Fund (GLPF). Her expertise spans Python, C++, PyTorch, TensorFlow, OpenCV, and QT Creator, alongside an ability to build and optimize large-scale AI frameworks for IoT and environmental data analysis. Her research interests include smart infrastructure, sustainable AI systems, microplastic detection, and federated learning-based IoT applications. Ms. Chaudhari has published multiple peer-reviewed papers in IEEE and Scopus-indexed journals, contributing to the advancement of applied AI research. She has been recognized for her academic excellence, innovative research contributions, and mentoring roles in interdisciplinary learning environments. With her growing portfolio of impactful publications and ongoing collaborations, Ms. Pratiksha Chaudhari continues to demonstrate strong potential as a future leader in AI research, committed to creating intelligent, ethical, and sustainable technologies for real-world applications.

Profile: ORCID | Google Scholar

Featured Publications 

  1. Chaudhari, P. (2025). Translution: A Hybrid Transformer–Convolutional Architecture with Adaptive Gating for Occupancy Detection in Smart Buildings. Electronics. 5 Citations.

  2. Chaudhari, P. (2024). Fundamentals, Algorithms, and Technologies of Occupancy Detection for Smart Buildings Using IoT Sensors. Sensors. 8 Citations.

  3. Chaudhari, P. (2024). Deep Learning-Based Streamflow Reconstruction Using Hydro-Transformer Models for Climate Data Analysis. Environmental Modelling & Software. 4 Citations.

  4. Chaudhari, P. (2023). Real-Time Detection and Classification of Microplastic Particles Using OpenCV and Raman Spectroscopy. Journal of Environmental Informatics. 6 Citations.

  5. Chaudhari, P. (2023). Federated Learning Models for Anomaly Detection in IoT-Enabled Smart Environments. IEEE Internet of Things Journal. 9 Citations.

  6. Chaudhari, P. (2022). AI-Powered Vocal Coaching System Using Wearable Sensors and Machine Learning Feedback Loops. Computers in Human Behavior. 3 Citations.

  7. Chaudhari, P. (2022). Developing an AI Framework for Smart Building Energy Optimization Using Transformer Networks. Applied Energy. 7 Citations.

 

Serdar Ozcan | Computer Science | Best Researcher Award

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Dr. Serdar Ozcan | Computer Science | Best Researcher Award

Dr. Serdar Ozcan | Computer Science – Canakkale Onsekiz Mart University, Turkey

Dr. Serdar Ozcan is an innovative researcher and seasoned industry professional whose work bridges the domains of artificial intelligence, energy sustainability, and digital transformation in manufacturing. With over three decades of leadership experience in Research & Development (R&D) and technological innovation, he has played a crucial role in shaping smart industry practices, particularly in ceramic and energy-intensive production lines. As an R&D Technology Development Manager at Kaleseramik, Türkiye’s leading ceramics manufacturer, Dr. Ozcan blends scientific inquiry with industry-scale implementation, making his research deeply impactful and immediately applicable. His expertise spans industrial automation, machine learning applications, piezoelectric energy harvesting, hydrogen energy systems, and predictive maintenance in smart factories.

Academic Profile

ORCID  |  Google Scholar

Education

Dr. Ozcan holds a Doctorate in International Business Administration, awarded in 2024 by Çanakkale Onsekiz Mart University, where he specialized in the integration of supervised artificial intelligence algorithms into predictive quality analysis in ceramic production lines. He earned his Master’s degree in Computer Engineering from the same university, where his thesis addressed the application of machine learning techniques to industrial process optimization. His undergraduate studies were completed in Electronics and Telecommunication Engineering at Yıldız Technical University, providing a robust foundation in control systems, embedded technologies, and communication protocols that later shaped his multidisciplinary career.

Experience

Over the course of more than 30 years, Dr. Ozcan has held a range of senior roles in the Turkish industrial and technology sectors, including General Manager, CTO, and Factory Manager. He currently leads cross-functional research and innovation teams, integrating academic research into commercial solutions in fields like robotics, IoT, and green manufacturing. His experience includes managing national and EU-funded projects, guiding more than 200 engineers and technicians, and aligning industrial output with carbon reduction and sustainability goals. He has also served as a mentor to junior researchers, providing guidance in both academic publishing and applied research design.

Research Interest

Dr. Ozcan’s research is deeply focused on artificial intelligence in manufacturing, energy efficiency, and behavioral digital transformation strategies. He is particularly passionate about Industry 4.0 technologies, hydrogen-based energy systems, and predictive analytics using machine learning and deep learning techniques. His recent projects focus on developing AI-supported decision systems to optimize quality control and reduce energy consumption in ceramic tile production. He is also exploring hybrid renewable energy systems involving piezoelectric generators, microgrid optimization, and smart factory integration. His ability to merge theoretical constructs with real-world applications makes his work highly relevant to industry leaders and academic peers alike.

Awards

Dr. Ozcan’s pioneering work has earned him several awards, most notably 1st Prize at the 2024 ISO Green Transformation Awards for his innovative R&D project on energy harvesting using piezoelectric ceramics. He was also recognized by the Turkish Ministry of Industry and Technology for his contributions to digital transformation in the manufacturing sector. His leadership in EU-funded sustainability initiatives has received commendations from project steering committees for outstanding technological impact and cross-border collaboration. These recognitions highlight his role as a key figure in both scientific innovation and practical implementation.

Publications

📘 “Supervised Artificial Intelligence Application in Ceramic Production Quality Forecasting” (2023), published in Journal of Intelligent Manufacturing – cited by 12 articles.
⚙️ “Energy Harvesting via Piezoelectric Ceramics for Sustainable Infrastructure” (2022), Renewable Energy Advances – cited by 17 articles.
🤖 “AI-Based Fault Detection in Industrial Motors Using Sensor Fusion” (2021), IEEE Access – cited by 24 articles.
🔋 “Hydrogen Integration in Smart Factory Grids” (2022), International Journal of Energy Research – cited by 9 articles.
🧠 “Deep Learning in Predictive Maintenance for Ceramic Production” (2023), Applied Soft Computing – cited by 14 articles.
🌱 “Digital Transformation Models for Sustainable Manufacturing” (2021), Technovation – cited by 18 articles.
🛰️ “Robotic Path Optimization Using Reinforcement Learning” (2020), Journal of Industrial Robotics – cited by 20 articles.

Conclusion

Dr. Serdar Ozcan stands as a beacon of translational research and sustainable innovation in the intersection of industry and academia. His expertise, spanning artificial intelligence, energy systems, and digital transformation, positions him as a frontrunner in the global movement toward smart and sustainable manufacturing. His recognition through awards, publications, and leadership roles reflect not just past accomplishments but a future-oriented trajectory filled with promise and continued impact. As such, he is an outstanding nominee for the Best Researcher Award, a testament to his lifetime commitment to innovation, academic excellence, and industrial advancement.

Sara Bendjeddou | Statistics | Best Researcher Award

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Mrs. Sara Bendjeddou | Statistics | Best Researcher Award

Teacher researcher at USTHB (University of Science and Technology Houari Boumediene), Algeria

Dr. Sara Bendjeddou is a distinguished mathematician and educator with a robust focus on stochastic methods and operational research. Her academic journey is marked by a series of achievements, reflecting her dedication to advancing mathematical sciences. Currently serving as a Maître de Conférences at the University of Sciences and Technology Houari Boumediene (U.S.T.H.B.) in Algeria, Dr. Bendjeddou has made significant contributions to the fields of statistics and probability theory. With a passion for teaching and research, she has inspired numerous students and colleagues, fostering an environment of inquiry and intellectual growth. Her work, particularly in time series analysis, showcases her exceptional analytical abilities and commitment to excellence in research and education.

Profile

ORCID

Education

Dr. Bendjeddou holds an impressive array of academic credentials. She earned her Doctorate in Mathematics in April 2018 from U.S.T.H.B., specializing in Stochastic Methods in Operational Research. Her doctoral thesis, Inference of Quasi-Maximum Likelihood for Integer-Valued Time Series Models, received high praise, earning a “very honorable” mention under the guidance of Professor A. Aknouche. Prior to her doctorate, she completed her Magister in Mathematics in October 2011, focusing on periodic bilinear models, which also garnered an “honorable” mention. Dr. Bendjeddou’s educational foundation began with her engineering degree in statistics from U.S.T.H.B. in September 2008, where she achieved a “very honorable” distinction. Her academic journey is complemented by a solid grounding in natural sciences, having completed her Baccalauréat with distinction in 2003.

Experience

Dr. Bendjeddou’s professional experience is extensive and varied, spanning over a decade in academia and research. She began her career as a Statistics Engineer at the Ministry of Territorial Planning and Environment from April 2009 to March 2012. This role provided her with practical insights into statistical applications in government projects. Subsequently, she transitioned into academia, taking on positions as an assistant lecturer at various institutions before joining U.S.T.H.B. as a Maître de Conférences in 2018. Throughout her tenure, Dr. Bendjeddou has taught a wide range of courses, including General Mathematics, Stochastic Processes, and Advanced Statistics, demonstrating her versatility as an educator. She has also played a crucial role in mentoring Master’s students, guiding their research projects in statistical applications and operational research.

Research Interests

Dr. Bendjeddou’s research interests lie primarily in the areas of stationary and non-stationary time series, as well as statistical inference for stochastic processes. Her work aims to enhance the understanding of complex statistical models and their applications in various fields. Dr. Bendjeddou’s contributions to time series analysis are noteworthy, particularly her focus on maximum likelihood estimation methods. She has actively engaged in research that addresses real-world statistical challenges, collaborating with esteemed colleagues and contributing to the advancement of statistical methodology. Her research findings are not only significant for theoretical development but also have practical implications, making her work relevant to both academia and industry.

Awards

Throughout her career, Dr. Bendjeddou has received recognition for her academic excellence and contributions to the field of mathematics. Her Doctorate thesis was awarded “very honorable,” underscoring her capability and dedication to research. Additionally, she has participated in several national and international conferences, showcasing her research and engaging with the broader academic community. These opportunities have not only enriched her knowledge and experience but have also provided a platform for her to share her insights and foster collaborations. Dr. Bendjeddou’s ongoing commitment to research and education positions her as a strong candidate for prestigious awards recognizing excellence in academia.

Publications

Aknouche, A. & Bendjeddou, S. (2017). Estimateur du quasi-maximum de vraisemblance géométrique d’une classe générale de modèles de séries chronologiques à valeurs entières. C. R. Acad. Sci. Paris, Ser. I, 355, 99-104.

Aknouche, A., Bendjeddou, S. & Touche, N. (2018). Inférence du quasi maximum de vraisemblance binomiale négative d’une classe générale de modèles de séries chronologiques à valeurs entières. Journal of Time Series Analysis.

Bendjeddou, S. (2024). Preliminary Test Estimation for Parallel 2-Sampling in Autoregressive Model. Stats, 7(4), 1141-1158.

Conclusion

In conclusion, Dr. Sara Bendjeddou’s remarkable academic background, extensive research contributions, and unwavering dedication to teaching position her as a leading figure in the field of mathematics. Her strengths in research and education make her a deserving candidate for the Best Researcher Award. Dr. Bendjeddou’s work not only advances the field of stochastic processes and time series analysis but also serves as an inspiration to her peers and students. Recognizing her achievements with this award would honor her contributions and encourage her ongoing commitment to excellence in research and education.

Mohammad Arashi | Statistics | Best Researcher Award

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Prof.Mohammad Arashi | Statistics | Best Researcher Award 

Professor Ferdowsi University of Mashhad  Iran

Dr. Mohammad Arashi is a distinguished professor at the Department of Statistics, Faculty of Mathematical Sciences, Ferdowsi University of Mashhad. He specializes in shrinkage estimation, variable selection, and high-dimensional data analysis. His extensive academic and professional journey has positioned him as a leading figure in statistical sciences.

Profile 

Scopus

Education 🎓

Dr. Arashi holds a Ph.D. in Statistics (2008) and an M.Sc. in Mathematical Statistics (2005) from Ferdowsi University of Mashhad, Iran. He completed his B.Sc. in Statistics from Shahid Bahonar University of Kerman in 2003. His rigorous academic background has laid a solid foundation for his research and teaching excellence.

Experience 🏅

Dr. Arashi has held various academic positions, including Professor at Ferdowsi University of Mashhad (2021-present) and Extraordinary Professor at the University of Pretoria (2014-present). He also served as Associate Professor at Shahrood University of Technology (2012-2020). His leadership roles include directing the Data Science Laboratory at Ferdowsi University and serving on several scientific committees.

Research Interests 📊

Dr. Arashi’s research interests are diverse and impactful. He focuses on shrinkage estimation, variable selection, high-dimensional and big data analysis, statistical machine learning, graphical models, and longitudinal data analysis. His work significantly contributes to the advancement of statistical methodologies and their applications.

Awards 🏆

Dr. Arashi has received numerous awards, including the DSI-NRF CoE-MaSS Statistics Publication Impact Award (2023) and multiple teaching and research excellence awards from Ferdowsi University of Mashhad and Shahrood University of Technology. He is also an ISI Elected Member and an NRF rated researcher (C2).

Publications 📚

Dr. Arashi has published extensively in reputed journals. Notable publications include:

  1. “Shrinkage Estimation in Big Data” (2023), Journal of Statistical Computation and Simulation. Cited by Article 1, Article 2.
  2. “Variable Selection in High-Dimensional Models” (2021), Computational Statistics & Data Analysis. Cited by Article 3, Article 4.
  3. “Advanced Statistical Machine Learning Techniques” (2019), Journal of Machine Learning Research. Cited by Article 5, Article 6.

Abdallah Houcheimi | Information Systems | Best Researcher Award

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Mr. Abdallah Houcheimi | Information Systems | Best Researcher Award

Doctor Researcher | Åbo Akademi University | Finland

Short Bio 🌟

Abdallah Houcheimi, born on September 22, 1981, is a university instructor and researcher specializing in information systems. With dual addresses in Bekaa, Lebanon, and Turku, Finland, he combines his expertise in business administration and technology to advance academic and practical knowledge in e-commerce, decision analytics, and artificial intelligence solutions. You can reach him via email at Abdallah.Houcheimi@abo.fi or Skype at ahouchimi@gmail.com.

Profile

ORCID

Education 🎓

Abdallah Houcheimi is currently pursuing a D.Sc. in Information Systems, expected to be completed in October 2024, at Åbo Akademi University in Turku, Finland. He holds a Master of Business Administration in International Business, obtained with Merit in 2015 from the University of Liverpool, UK. His foundational education includes a B.S. in Information Technology, earned in 2006 from the Lebanese International University, Lebanon.

Experience 👨‍🏫

Abdallah Houcheimi has a diverse professional background, starting as an Information Technology Support Analyst at Exceed IT Services Company in Abu Dhabi, UAE, and progressing to roles such as IT Project Leader at the Abu Dhabi Investment Authority (ADIA) and Managing IT Projects at Alpha Data. He served as Assistant Dean and instructor at the Lebanese International University and is currently a full-time doctoral researcher at Åbo Akademi University.

Research Interests 🔬

Abdallah’s research focuses on e-commerce, decision analytics, and artificial intelligence applications across various business domains. His work aims to enhance the understanding and implementation of secure online payment systems, online product information, and the role of social media in electronic retailing (e-tailing).

Awards 🏆

Throughout his career, Abdallah Houcheimi has been recognized for his contributions to academia and the field of information systems. His innovative research and commitment to education have earned him respect and accolades within the academic community.

Publications 📚

Abdallah Houcheimi has contributed several notable publications to the field of information systems:

  1. Houcheimi, A., & Mezei, J. (2024). “The Role of Secure Online Payments in Enabling the Development of E-Tailing.” Journal of Organizational Computing and Electronic Commerce. Read here. Cited by articles in leading journals.
  2. Houcheimi, A., & Mezei, J. (2024). “The Role of Online Product Information in Enabling Electronic Retail/E-tailing.” In: Rocha, Á., et al. (eds) Good Practices and New Perspectives in Information Systems and Technologies. Springer, Cham. Read here.
  3. Houcheimi, A. (2022). “The Key E-Tail Opportunities and Challenges in The Lebanese E-Commerce Market.” Journal of Information System and Technology Management, 7(26), 13-31. Read here.
  4. Houcheimi, A. (In Press). “The Role of Social Media Networks in Enabling the Development of Electronic Retail (E-Tailing).” Submitted to Knowledge and Information Systems Journal.