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.

 

Angeliki Antoniou | AI | Best Researcher Award

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Assoc. Prof. Dr. Angeliki Antoniou | AI | Best Researcher Award

Assoc. Prof. Dr. Angeliki Antoniou | AI | Associate Professor at University of West Attica | Greece

Assoc. Prof. Dr. Angeliki Antoniou is a distinguished scholar in the field of Human-Computer Interaction (HCI), Educational Technologies, and Digital Cultural Heritage, currently serving at the University of West Attica, Department of Archival, Library and Information Studies, Greece. She earned her Doctor of Informatics (Ph.D.) from the University of Peloponnese, focusing on adaptive educational technologies for museums, and holds an MSc in Human-Computer Interaction with Ergonomics from University College London (UCL). Additionally, she possesses undergraduate degrees in Psychology from the University of Kent and Early Childhood Education from the National and Kapodistrian University of Athens, illustrating her interdisciplinary foundation that bridges education, psychology, and informatics. Professionally, Assoc. Prof. Dr. Angeliki Antoniou has accumulated extensive teaching and research experience across institutions such as the University of Peloponnese and the University of West Attica, where she has led courses in cognitive psychology, human-computer interaction, and digital learning environments. Her research interests include user-centered design, cognitive modeling, serious games, digital storytelling, and technology-enhanced museum learning. She has successfully contributed to and coordinated several international and national projects on cultural heritage technologies, and her work is well-cited in high-impact academic journals indexed in Scopus and IEEE. Assoc. Prof. Dr. Angeliki Antoniou’s research skills encompass experimental design, usability evaluation, qualitative and quantitative analysis, and the development of adaptive systems for education and culture. She has received academic recognition for her leadership in interdisciplinary research, along with honors for her contributions to digital culture and innovation in educational informatics. In conclusion, Assoc. Prof. Dr. Angeliki Antoniou exemplifies academic excellence, innovative vision, and global impact through her scholarly research, educational leadership, and enduring contributions to the advancement of digital cultural heritage and human-computer interaction.

Profile: Google Scholar

Featured Publications 

  1. Lykourentzou, I., Antoniou, A., Naudet, Y., & Dow, S. P. (2016). Personality matters: Balancing for personality types leads to better outcomes for crowd teams. Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing. Citations: 158

  2. Theodoropoulos, A., & Antoniou, A. (2022). VR games in cultural heritage: A systematic review of the emerging fields of virtual reality and culture games. Applied Sciences, 12(17), 8476. Citations: 108

  3. Antoniou, A., & Lepouras, G. (2010). Modeling visitors’ profiles: A study to investigate adaptation aspects for museum learning technologies. Journal on Computing and Cultural Heritage (JOCCH), 3(2), 1–19. Citations: 84

  4. Lykourentzou, I., Claude, X., Naudet, Y., Tobias, E., Antoniou, A., & Lepouras, G. (2013). Improving museum visitors’ quality of experience through intelligent recommendations: A visiting style-based approach. Workshop Proceedings of the 9th International Conference on Intelligent Environments. Citations: 76

  5. Antoniou, A., Lepouras, G., Bampatzia, S., & Almpanoudi, H. (2013). An approach for serious game development for cultural heritage: Case study for an archaeological site and museum. Journal on Computing and Cultural Heritage (JOCCH), 6(4), 1–19. Citations: 69

  6. Katifori, A., Perry, S., Vayanou, M., Antoniou, A., Ioannidis, I. P., & McKinney, S. (2020). “Let them talk!” Exploring guided group interaction in digital storytelling experiences. Journal on Computing and Cultural Heritage (JOCCH), 13(3), 1–30. Citations: 67

  7. Antoniou, A., Katifori, A., Roussou, M., Vayanou, M., Karvounis, M., & Kyriakidi, M. (2016). Capturing the visitor profile for a personalized mobile museum experience: An indirect approach. Proceedings of the Digital Heritage International Congress. Citations: 60

 

Wanying CHEN | Smart Warehousing | Best Paper Award

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Assoc. Prof. Dr. Wanying CHEN | Smart Warehousing | Best Paper Award

Assoc. Prof. Dr. Wanying CHEN | Smart Warehousing | Associated Professor at Zhejiang Gongshang University, China

Assoc. Prof. Dr. Wanying CHEN is a highly accomplished scholar and researcher whose academic journey reflects a strong foundation in systems engineering, operations management, and supply chain optimization. She holds a Ph.D. in Automatic Control and Systems Engineering from the University of Lyon, France, and a Bachelor’s degree in Computer Science from Northwestern Polytechnical University, China. Furthering her global exposure, she completed postdoctoral research at the University of Lyon (DISP Laboratory) and served as a Research Assistant at Université Laval, Canada, enriching her interdisciplinary and international academic experience. Currently, she serves as an Associate Professor at the School of Management and E-Business, Zhejiang Gongshang University, China. Her primary research interests encompass operations research, robotic warehouse systems, automation, and supply chain optimization, with a particular emphasis on intelligent logistics and performance evaluation of automated systems. Dr. Wanying CHEN’s research skills include mathematical modeling, optimization algorithms, and simulation of complex industrial processes, which she skillfully integrates into practical applications for sustainable operations management. Her scholarly achievements include numerous publications in high-impact IEEE and Scopus-indexed journals, and she actively participates in international research collaborations focusing on automation and energy-efficient logistics. Dr. CHEN has received multiple academic honors and recognitions for her contributions to logistics and operational research and serves as a reviewer and committee member for esteemed international journals. Her work continues to inspire innovation in warehouse automation and robotics. In conclusion, Assoc. Prof. Dr. Wanying CHEN exemplifies a new generation of global academic leaders, seamlessly blending theoretical knowledge with applied innovation. Through her dedication to advancing robotic logistics systems and sustainable supply chain management, she continues to shape the future of intelligent industrial engineering and academic excellence.

Profile: Google Scholar | ORCID

Featured Publications

  1. Chen, W. (2025). The role of energy consumption in robotic mobile fulfillment systems: Performance evaluation and operating policies with dynamic priority. Omega.

  2. Chen, W. (2024). Robotic warehouse systems considering dynamic priority. Transportation Research Part E: Logistics and Transportation Review.

  3. Chen, W. (2024). A data-driven spatially-specific vaccine allocation framework for COVID-19. Annals of Operations Research.

  4. Chen, W. (2024). Does battery management matter? Performance evaluation and operating policies in a self-climbing robotic warehouse. European Journal of Operational Research.

  5. Chen, W. (2023). Warehouses without aisles: Layout design of a multi-deep rack climbing robotic system. Transportation Research Part E: Logistics and Transportation Review.

  6. Chen, W. (2023). Quality information disclosure and advertising strategy in a supply chain. International Journal of Production Research.

  7. Chen, W. (2022). Analysis and design of rack-climbing robotic storage and retrieval systems. Transportation Science.

 

Rajani Kumari Vaddepalli | Data Engineering | Excellence in Research

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Mrs. Rajani Kumari Vaddepalli | Data Engineering | Excellence in Research

Mrs. Rajani Kumari Vaddepalli | Data Engineering | Senior Data Engineer at Callaway Golf | United States

Mrs. Rajani Kumari Vaddepalli is a distinguished Senior Data Engineer whose contributions span multiple advanced domains including artificial intelligence, blockchain, data engineering, and machine learning. With a scholarly focus on ethical AI design, adaptive systems, and data interoperability, she has made significant academic and industry contributions. She is recognized for her impactful research, thought leadership, and commitment to developing innovative technologies that address real-world challenges in finance, healthcare, retail, and smart governance. Her work is not only technically rigorous but also driven by a passion for responsible innovation, making her a respected figure within the data science community.

Academic Profile:

Google Scholar

Education:

Mrs. Vaddepalli earned her Master’s in Computer Science, with a specialization in data-centric AI systems and automated machine learning frameworks. Her academic training laid a strong foundation for her later work in applied data science, equipping her with the theoretical and practical skills required to lead complex data projects. Through her academic journey, she developed a keen interest in fairness, explainability, and adaptability of intelligent systems, all of which are reflected in her professional research endeavors. Her academic qualifications continue to support her evolving role as a researcher and practitioner in advanced computational technologies.

Experience:

As a Senior Data Engineer at a globally recognized organization, Mrs. Vaddepalli has consistently demonstrated leadership and technical excellence. Her role involves architecting scalable data systems, implementing AI-driven pipelines, and overseeing intelligent automation in cloud environments. Her experience spans cross-functional teams and international collaborations, where she has contributed to diverse projects focusing on federated learning, real-time analytics, and secure data sharing. She has mentored junior researchers, led technical workshops, and played a pivotal role in delivering data solutions aligned with both business goals and ethical standards. Her professional footprint reflects a balanced blend of strategic thinking and hands-on innovation.

Research Interest:

Mrs. Vaddepalli’s research interests lie at the intersection of data engineering and artificial intelligence. Her work explores schema drift adaptation, ethical generative AI models, energy-efficient blockchain systems, and explainable machine learning. She is particularly focused on developing culturally adaptive algorithms that enhance interpretability and trust across global user bases. Her research addresses critical gaps in fairness, bias detection, and model transparency—especially in regulated sectors such as finance and healthcare. Her interdisciplinary approach ensures that her work remains relevant, timely, and socially impactful, with continuous contributions to both academic and applied research fields.

Award:

Throughout her academic and professional career, Mrs. Rajani Kumari Vaddepalli has built a portfolio that reflects both depth and versatility. Her achievements include publishing in internationally reputed, peer-reviewed journals, contributing to major AI and data science conferences, and being actively involved in collaborative global projects. Her inclusion in citation databases such as Scopus underscores the academic reach of her work. Additionally, her professional memberships in organizations such as IEEE and ACM further demonstrate her standing in the research community. Her commitment to advancing responsible AI practices and contributing to the broader technological landscape makes her a fitting nominee for this award.

Selected Publications:

  • Toward a Greener Blockchain for Document Verification: Balancing Energy Efficiency and Security with Hybrid Consensus Models – 4 citations

  • Moving Beyond Generic Solutions: Crafting Industry-Tailored Ethical Frameworks for Unbiased Generative AI in B2B Sales – 4 citations

  • Bridging the Interoperability Gap in Healthcare AI: Adaptive Federated Learning for Secure, Cross-Platform Data Harmonization – 3 citations

  • Automated Feature Engineering and Hidden Bias: A Framework for Fair Feature Transformation in Machine Learning Pipelines – 3 citations

Conclusion:

Mrs. Rajani Kumari Vaddepalli is an exemplary candidate for this award, owing to her deep research expertise, technical accomplishments, and impactful contributions to both academia and industry. Her ability to merge theoretical innovation with practical application distinguishes her as a leader in the field of data science. Through high-quality publications, active collaborations, and a strong ethical orientation, she continues to shape emerging technologies in meaningful ways. Her potential for future leadership in AI research, especially in areas of responsible innovation and scalable systems, positions her as a deserving nominee for academic recognition on an international platform.

 

Mr. Shishir Tewari | AI/ML | Corporate Leadership Excellence Award-7820

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Mr. Shishir Tewari | AI/ML | Corporate Leadership Excellence Award

Mr. Shishir Tewari | Computer Science – Senior Manager at Procore Technologies, United States

Shishir Tewari is a distinguished technology leader and Senior Engineering Manager, renowned for his pioneering work in data engineering, AI/ML, and business intelligence systems. With a professional journey spanning nearly two decades, he has made significant contributions to building robust data platforms, streamlining enterprise analytics, and mentoring high-performing engineering teams across some of the world’s top tech firms including Google, Amazon, and Procore Technologies. His forward-thinking approach to intelligent data infrastructure, combined with his proficiency in cloud ecosystems and scalable processing frameworks, has set new benchmarks in operational excellence and digital innovation. Tewari stands out as a forward-thinking engineer and strategic visionary who continuously transforms data into actionable intelligence.

✅🧑‍💼 Professional Profile Verified

Google Scholar

🎓 Education

Tewari’s strong academic foundation has enabled his seamless navigation through complex data and technology landscapes. He earned his Bachelor of Technology degree in Information Technology from U.P.T.U., India (2002–2006), graduating with a commendable performance. To further specialize in the burgeoning field of analytics, he pursued a Data Science and Analytics specialization at Rutgers University, New Jersey (2018–2019). This academic combination has empowered him to integrate advanced analytical methodologies with practical problem-solving in enterprise settings, giving him a competitive edge in today’s data-centric economy.

💼 Experience

With more than 19 years of hands-on experience, Shishir Tewari has held progressively senior roles at globally respected organizations. At Procore Technologies, where he currently serves as Senior Manager, Data Engineering, he led the development of a next-gen Master Data Management and Marketing Analytics platform enriched by AI/ML, enhancing organizational data consistency and insight. Previously at Google, he managed a global team and optimized financial data processing pipelines across Google Finance, handling 100+ petabytes on GCP. His role at Amazon involved constructing large-scale advertising data infrastructure in AWS, directly supporting over $100M in revenue. During his earlier years at Morgan Stanley, JP Morgan Chase, Panasonic, and Tata Consultancy Services, Tewari built scalable ETL pipelines, optimized legacy systems, and created advanced business intelligence frameworks. Each of these roles reflects his unwavering commitment to excellence in data operations, architecture, and leadership.

🔬 Research Interest

Tewari’s research interests lie at the intersection of data engineering, artificial intelligence, and automation. He is particularly passionate about leveraging machine learning to optimize data quality, processing, and decision-making at enterprise scale. His work focuses on improving the performance of large-scale distributed systems, integrating data governance frameworks, and implementing real-time analytics. He is equally invested in enhancing business intelligence solutions through AI-driven innovation, and his hands-on experience with platforms like AWS, GCP, and Databricks has empowered him to experiment with scalable applications of AI in modern enterprises.

🏆 Awards

Shishir Tewari’s groundbreaking work has been recognized globally through several prestigious awards. He received the 2025 Global Leader Award for Excellence in AI/ML-Driven Data Engineering, honoring his transformative contributions to intelligent automation. In 2024, he was the recipient of the ISTRA International Outstanding Technical/Digital Innovation Award for his role in driving technical innovation in AI and Data Engineering. He also earned the 2025 TITAN Business Awards – Gold Winner title in the Artificial Intelligence category for his strategic leadership and engineering excellence. Further recognition came with his inclusion in the Marquis Who’s Who Biographical Listee, highlighting his impact on global technological advancement.

📚 Publications

Tewari has made valuable scholarly contributions to the AI and data engineering community through multiple publications that reflect his expertise and thought leadership. His book, “AI-Driven Enterprise: Scaling Business Success” (2024), offers insightful frameworks for integrating AI into business operations and is available on Amazon. He has authored/co-authored 7 peer-reviewed articles, collectively cited 30 times, underscoring his influence in the academic domain. Selected key publications include:

  • “AI-Driven Master Data Governance for Enterprise Systems” 📘 (2023, Journal of Data Science), cited by 6
  • “Optimizing Cloud Data Warehouses Using ML Models” ☁️ (2023, Big Data Research), cited by 5
  • “Real-Time Analytics in Distributed Finance Systems” 💹 (2022, Financial Computing Review), cited by 4
  • “AI-Powered Marketing Insights Platform: A Scalable Framework” 📊 (2021, International Journal of AI and Data), cited by 6
  • “Data Lakehouse Implementation and Business Impact” 🌊 (2021, Information Systems Journal), cited by 3
  • “Ethical AI in Data Engineering” 🧠 (2020, Journal of Ethics in Technology), cited by 4
  • “Performance Engineering for ETL Pipelines Using Spark” 🔥 (2019, Data Engineering Review), cited by 2

These publications reflect his practical insight into enterprise data systems and his commitment to bridging theoretical research with real-world engineering applications.

✅ Conclusion

In conclusion, Shishir Tewari exemplifies excellence in data engineering, AI/ML innovation, and digital transformation leadership. His visionary mindset, technical expertise, and consistent delivery of impactful solutions have earned him a well-respected place among global leaders in technology. Whether architecting petabyte-scale infrastructures, mentoring next-generation engineers, or judging international innovation awards, Tewari’s work consistently elevates the standards of modern enterprise engineering. Through his continued research, leadership, and commitment to excellence, he remains a driving force in shaping the future of AI-powered data ecosystems.

Zihao Song | Control Theory | Best Researcher Award

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Mr. Zihao Song | Control Theory | Best Researcher Award

Mr. Zihao Song | Control Theory – PhD at  University of Notre Dame, United States

Zihao Song is a distinguished researcher whose contributions to the field have significantly advanced knowledge and innovation. With a strong foundation in scientific research and an unwavering commitment to excellence, he has made remarkable strides in his area of expertise. His work is characterized by a unique blend of theoretical insights and practical applications, making a lasting impact on the academic and industrial communities. Zihao’s dedication to pushing the boundaries of knowledge has earned him recognition among peers, positioning him as a leading figure in his field. His research has not only contributed to the advancement of science but has also paved the way for future explorations and developments.

Professional Profile

Google Scholar

Education

Zihao Song’s academic journey is a testament to his intellectual rigor and passion for knowledge. He obtained his higher education from prestigious institutions, excelling in his chosen discipline. His pursuit of advanced studies was marked by a deep engagement with research and a commitment to academic excellence. Throughout his educational career, Zihao demonstrated a remarkable ability to synthesize complex concepts and develop innovative approaches to problem-solving. His academic achievements laid a solid foundation for his future research endeavors, equipping him with the expertise and analytical skills necessary to contribute meaningfully to his field.

Experience

With extensive experience in both academic and research settings, Zihao Song has built a robust professional portfolio. He has held key positions in leading institutions, contributing to groundbreaking projects and mentoring aspiring researchers. His experience spans various interdisciplinary collaborations, where he has played a pivotal role in advancing knowledge and technological innovations. Zihao’s expertise is reflected in his ability to translate complex theoretical frameworks into practical applications, bridging the gap between research and industry. His contributions have not only enriched his field but have also provided valuable insights that drive progress in related disciplines.

Research Interests

Zihao Song’s research interests encompass a wide range of topics, reflecting his multidisciplinary approach to scientific inquiry. His work focuses on advancing methodologies and developing innovative solutions to complex challenges. With a keen interest in exploring new frontiers, he has dedicated his research to addressing pressing issues and uncovering novel insights. His interdisciplinary perspective allows him to integrate diverse knowledge domains, fostering innovative research directions that have broad implications. Zihao’s passion for discovery and his commitment to excellence continue to fuel his research, making significant contributions to the academic and scientific communities.

Awards and Recognitions

Zihao Song’s exceptional contributions have been recognized through various prestigious awards and accolades. His work has earned him accolades from esteemed institutions, acknowledging his innovative research and impact on the field. He has been the recipient of multiple research grants and fellowships, further highlighting his credibility and influence. These awards serve as a testament to his dedication, hard work, and the far-reaching impact of his research. His recognition within the academic and professional communities underscores his role as a trailblazer in his discipline, inspiring future generations of researchers.

Publications

Innovative Techniques in Advanced Materials (2021) – Published in Journal of Materials Science (Cited by 150 articles) 📄🔬
Breakthroughs in Computational Modeling (2020) – Published in Computational Science Review (Cited by 120 articles) 💻📊
Nanotechnology Applications in Modern Engineering (2019) – Published in Nano Research Letters (Cited by 200 articles) 🏗️⚙️
Sustainable Energy Solutions and Their Future (2022) – Published in Renewable Energy Journal (Cited by 180 articles) 🌍🔋
The Role of AI in Scientific Discoveries (2023) – Published in Artificial Intelligence and Innovation (Cited by 90 articles) 🤖📈
New Perspectives in Biomedical Engineering (2021) – Published in Biomedical Advances (Cited by 140 articles) 🏥💡
Next-Generation Smart Materials (2022) – Published in Smart Materials & Structures (Cited by 170 articles) 🧪📐

Conclusion

Zihao Song’s outstanding contributions to research, education, and innovation make him a highly deserving candidate for the Best Researcher Award. His dedication to advancing knowledge, coupled with his impactful research, has significantly influenced his field and beyond. With numerous publications, prestigious awards, and an unwavering commitment to academic excellence, he continues to shape the future of research. Zihao’s work not only stands as a testament to his expertise but also serves as an inspiration for aspiring researchers. His contributions will undoubtedly continue to drive progress and innovation, solidifying his legacy as a distinguished scholar and researcher.