Zhihao Kang | Deep Learning | Best Researcher Award

Published on by Academic Achievements

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

Published on by Academic Achievements

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.