Hugo Terashima Marín | Computer Science | Best Researcher Award

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Prof. Hugo Terashima Marín | Computer Science | Best Researcher Award

Professor at Tecnológico de Monterrey | Mexico

Dr. Hugo Terashima-Marín is a distinguished Professor of Computer Science and Intelligent Systems at Tecnológico de Monterrey, Mexico, widely recognized for his pioneering work in computational intelligence and heuristic optimization. His academic foundation spans prestigious institutions in Mexico, the United States, and the United Kingdom, reflecting a strong interdisciplinary background in informatics, artificial intelligence, and knowledge-based systems. As a leading researcher in evolutionary computation, constraint satisfaction problems, and hyper-heuristics, Dr. Terashima-Marín has developed innovative methodologies that bridge artificial intelligence and practical problem-solving across domains such as logistics, medicine, and smart cities. His extensive publication record in high-impact journals demonstrates his global influence in advancing algorithmic design, machine learning integration, and automated reasoning systems. Beyond research, he has mentored numerous doctoral and master’s students, fostering new generations of scientists in computational intelligence. His leadership roles at Tecnológico de Monterrey—directing graduate and doctoral programs and leading research groups in intelligent systems—underscore his commitment to academic excellence and institutional innovation. Recognized by the Mexican National System of Researchers and honored by the Mexican Academy of Sciences and the IEEE, Dr. Terashima-Marín’s contributions have elevated the standards of AI research in Latin America. His current projects explore multi-objective optimization, digital twins for smart city applications, and AI-driven decision support systems, continuing to push the boundaries of how computation can model, predict, and enhance complex human and industrial processes. Through decades of scholarship and collaboration, he remains an influential figure shaping the global discourse on intelligent systems and applied artificial intelligence.

Profiles: Scopus | ORCID

Featured Publications

Ali, F., Ahmed, A., Alipour, M. A., & Terashima-Marin, H. (2025, October 25). Adoption of AI-coding assistants in programming education: Exploring trust and learning motivation through an extended technology acceptance model.

Morales-Paredes, A., Juárez, J., Falcón-Cardona, J., Terashima-Marin, H., & Coello Coello, C. (2025, July 14). Automatic design of specialized variation operators for the multi-objective quadratic assignment problem.

Morales-Paredes, A. I., Falcón-Cardona, J. G., Juárez, J., Terashima-Marín, H., & Coello Coello, C. A. (2025, July 14). Reference point specification in greedy inclusion hypervolume-based subset selection: A study on two objectives. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2025).

Pirzado, F. A., Ahmed, A., Hussain, S., Ibarra-Vázquez, G., & Terashima-Marin, H. (2025, March 11). Assessing computational thinking in engineering and computer science students: A multi-method approach.

Garza-Santisteban, F., Cruz-Duarte, J. M., Amaya, I., Ortiz-Bayliss, J. C., Conant-Pablos, S. E., & Terashima-Marín, H. (2025, February). Selection hyper-heuristics and job shop scheduling problems: How does instance size influence performance

Mr. Sachin Pandey | AI Data Science | AI & Machine Learning Award

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Mr. Sachin Pandey | AI Data Science | AI & Machine Learning Award

Head of Data Engineering and Data Science, Oracle Corporation, United States

Mr. Sachin Pandey is an accomplished data scientist and engineering professional whose expertise bridges the domains of artificial intelligence, data management, and enterprise analytics. With more than thirteen years of progressive experience, Mr. Sachin Pandey currently serves as the Head of Data Engineering and Data Science at Oracle Corporation, where he leads multidisciplinary teams in the development of intelligent data infrastructures, machine learning solutions, and scalable MLOps frameworks. He previously contributed his expertise as Head of Data Science at Walmart US, overseeing large-scale analytical transformations that enhanced predictive decision systems and optimized data-driven strategies across global business operations. Mr. Sachin Pandey’s academic foundation is rooted in a Master of Science in Management Information Systems from the University of Illinois at Chicago – Liautaud Graduate School of Business, where he developed a strong grounding in business intelligence, data visualization, and statistical computing. He earned his Bachelor of Technology in Electronics and Telecommunication Engineering from the Vivekananda Education Society’s Institute of Technology, Mumbai, where his technical acumen and analytical thinking shaped his approach to applied data research. His research interests include machine learning algorithms, deep learning optimization, big data analytics, AI-based automation, and data governance, focusing on how scalable AI systems can transform decision-making and industry practices. Mr. Sachin Pandey has published and co-authored peer-reviewed papers in internationally recognized journals and conference proceedings indexed by Scopus and IEEE, including notable contributions in areas of image detection, intelligent automation, and cloud-based analytics. His most cited work, “Smoke and Fire Detection” is recognized for advancing the use of AI models in safety and monitoring systems, reflecting his commitment to practical applications of data science for societal benefit. In addition to research, he possesses exceptional skills in Python programming, Spark, Airflow, data modeling, ELT/ETL frameworks, MLFlow, and cloud analytics platforms such as Power BI, Tableau, and Alteryx, complemented by a deep understanding of optimization, data governance, and model versioning techniques.

Profiles: Google Scholar | Orcid 

Featured Publications

  • Gharge, S., Birla, S., Pandey, S., Dargad, R., & Pandita, R. (2013). Smoke and fire detection. International Journal of Advanced Research in Computer and Communication Engineering, 2(6). Cited by: 16

  • Singh, A., & Pandey, S. (2014). Advanced Centralised RTO System for Traffic Data Automation. International Journal of Emerging Technology and Advanced Engineering, 4(5). Cited by: 9

  • Pandey, S. (2015). Intelligent Data Governance Using Cloud-based Frameworks. International Journal of Data Science and Analytics, 3(2). Cited by: 11

  • Pandey, S., & Birla, S. (2016). Optimization of Machine Learning Pipelines for Enterprise Analytics. Proceedings of the IEEE International Conference on Computational Intelligence. Cited by: 7

  • Pandey, S. (2019). Scalable AI Systems for Predictive Data Engineering. Journal of Artificial Intelligence Research and Applications, 10(4). Cited by: 13