Zhongqiang Zhang | Mechanical Engineering | Best Researcher Award

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Prof. Dr. Zhongqiang Zhang | Mechanical Engineering | Best Researcher Award

Dean at Jiangsu University | China

Professor Zhongqiang Zhang is a distinguished scholar in mechanical engineering whose research bridges fundamental mechanics and advanced nanotechnology. He has made significant contributions to the understanding of solid–fluid interfacial phenomena, including boundary slip, interfacial friction, and their implications for the design of next-generation micro/nano fluidic systems. As a faculty member and academic leader at Jiangsu University, his work has advanced the frontiers of nanofluidics, soft robotics, and smart material design through innovative integration of theory, computation, and experiment. Professor Zhang’s pioneering studies on graphene-based membranes, droplet dynamics, and energy-efficient fluid systems have been published in leading international journals such as Science Advances, Chemical Engineering Journal, and ACS Applied Materials & Interfaces. His research has introduced novel mechanisms for unidirectional droplet transport and enhanced bubble collection, providing new pathways for desalination, energy harvesting, and biomedical applications. Recognized for his excellence and originality, he has received multiple prestigious honors, including the ICCES Outstanding Young Researcher Award and the Jiangsu Provincial Science and Technology Awards. His projects funded by the National Natural Science Foundation of China underscore his leadership in advancing electro-mechanical coupling and interface-driven transport in microstructured materials. Professor Zhang’s work embodies the synergy of mechanics, materials, and nanotechnology, continually inspiring innovation in sustainable energy systems and intelligent fluidic devices. His scholarly achievements reflect a sustained commitment to interdisciplinary research excellence, making him a leading figure shaping the global discourse in advanced mechanical and fluid systems engineering.

Profile: Google Scholar

Featured Publications

Cheng, G. G., Jiang, S. Y., Li, K., Zhang, Z. Q., Wang, Y., Yuan, N. Y., Ding, J. N., et al. (2017). Effect of argon plasma treatment on the output performance of triboelectric nanogenerator.

Zheng, Y., Ye, H., Zhang, Z., & Zhang, H. (2012). Water diffusion inside carbon nanotubes: Mutual effects of surface and confinement.

Zhang, H., Ye, H., Zheng, Y., & Zhang, Z. (2011). Prediction of the viscosity of water confined in carbon nanotubes.

Zhang, H., Zhang, Z., & Ye, H. (2012). Molecular dynamics-based prediction of boundary slip of fluids in nanochannels.

Zhang, Z., Li, S., Mi, B., Wang, J., & Ding, J. (2020). Surface slip on rotating graphene membrane enables the temporal selectivity that breaks the permeability–selectivity trade-off.

Vinay Chaudhri | Knowledge Engineering | Best Researcher Award

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Dr. Vinay Chaudhri | Knowledge Engineering | Best Researcher Award

Principal Scientist at Knowledge Systems Research LLC | United States

Dr. Vinay K. Chaudhri is a distinguished technology executive and research scientist renowned for his pioneering contributions in artificial intelligence, knowledge representation, and automated reasoning. His work bridges the gap between deep research and impactful real-world applications across domains such as education, finance, and law. As a thought leader in knowledge graphs, semantic reasoning, and large language models, Dr. Chaudhri has led groundbreaking projects that demonstrate the transformative potential of AI in enhancing learning outcomes, improving financial intelligence, and enabling computational understanding of complex legal structures. His tenure at organizations including SRI International, Stanford University, JPMorgan Chase, and Knowledge Systems Research has been marked by visionary leadership and innovation. At SRI, he played a key role in landmark AI initiatives like Project Halo and CALO—the latter evolving into Apple’s Siri—demonstrating his ability to architect systems that advance both academic inquiry and commercial technology. At Stanford, his efforts in intelligent education tools such as the HaloBook and Intelligent Textbook showcased AI’s capacity to personalize and elevate learning experiences, while his leadership in the LogicForAll initiative expanded logic education nationwide. In the finance sector, his work integrating NLP and graph-based AI systems has delivered multi-million-dollar impacts through enhanced analytics, compliance, and decision intelligence. A prolific researcher with numerous publications and awards, Dr. Chaudhri continues to shape the future of AI with a vision grounded in rigorous science, ethical innovation, and societal benefit, making him a respected figure in the global AI research and technology community.

Profile: Google Scholar

Featured Publications

Chaudhri, V. K., Farquhar, A., Fikes, R., Karp, P. D., & Rice, J. P. (1998). OKBC: A programmatic foundation for knowledge base interoperability.

Woolf, B. P., Lane, H. C., Chaudhri, V. K., & Kolodner, J. L. (2013). AI grand challenges for education.

Burger, J., Cardie, C., Chaudhri, V., Gaizauskas, R., Harabagiu, S., Israel, D., … & Weischedel, R. (2001). Issues, tasks and program structures to roadmap research in question & answering (Q&A).

Karp, P. D., Chaudhri, V. K., & Thomere, J. (1999, July). XOL: An XML-based ontology exchange language.

Chaudhri, V. K., Farquhar, A., Fikes, R., Karp, P. D., & Rice, J. P. (1998). Open knowledge base connectivity 2.0.

Bincy Kaluvilla | Artificial Intelligence | Best Academic Researcher Award

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Dr. Bincy Kaluvilla | Artificial Intelligence | Best Academic Researcher Award

Head of Academics at Learners University College | United Arab Emirates

Dr. Bincy B. Kaluvilla is an accomplished academic leader and researcher whose work bridges the disciplines of sustainable finance, hospitality management, and real estate investment. Her professional journey reflects a deep commitment to academic excellence, innovation, and the advancement of sustainability-focused business education. As an experienced higher education professional, she has played a transformative role in shaping curricula and fostering strategic partnerships that align academic programs with contemporary industry practices. Her teaching portfolio encompasses subjects such as Real Estate Finance, Hospitality Accounting, and Corporate Finance, delivered across international undergraduate and postgraduate programs. A Fellow of the Higher Education Authority (UK) and a CPA Australia member, she brings a strong foundation in finance and accounting to her academic leadership. Her scholarly contributions span peer-reviewed journals, book chapters, and international conferences, exploring topics including ESG reporting, sustainable investment, AI integration in hospitality, and the evolving intersections of culture, ethics, and finance. Notable among her works are publications in Frontiers in Computer Science, Asia Pacific Journal of Tourism Research, Performance Measurement and Metrics, and Journal of Open Innovation. She has also contributed to edited volumes published by Springer Nature, IGI Global, Emerald, and Elsevier. Beyond research and teaching, Dr. Kaluvilla has led numerous corporate training programs for leading organizations such as the Jumeirah Group and Omran Group, promoting financial literacy and leadership within the hospitality sector. Her contributions have been recognized globally through awards and invitations to serve as visiting faculty at institutions in Malta, Japan, and China. Through her research, teaching, and leadership, she continues to champion sustainability, innovation, and excellence in global higher education and industry practice.

Profile: Google Scholar

Featured Publications

Kaluvilla, B. B., Kalarikkal, S. A., & Thamilvanan, G. (2025). AI-driven extraction and intelligent retrieval of missionary archives in Malabar: Advancing preservation and accessibility with machine learning.

Mulla, T., Kaluvilla, B. B., Zahidi, F., Alsabbah, S., & Tantry, A. (2025). “Your house looks like that show…”: Exploring consumers’ perceptions towards media-inspired home décor.

Bouchon, F., Kaluvilla, B. B., & Kolmorgon, K. (2025). Sustainable luxury hospitality: A reality beyond antagonistic terms? Innovations and trends in Maldivian luxury resorts.

Thomsen, K., Kaluvilla, B. B., & Zahidi, F. (2025). Sustainable wildlife tourism: Government guidelines and lodge contributions in Zambia.

Kaluvilla, B. B. (2025). Review of The Routledge handbook of religious and spiritual tourism, by D. H. Olsen & D. J. Timothy.

Muhammad Danish Ali | Bioinformatics | Best Researcher Award

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Mr. Muhammad Danish Ali | Bioinformatics | Best Researcher Award

PhD Scholar at Jeju National University Republic of korea | South Korea

Mr. Muhammad Danish Ali is a dedicated researcher and emerging scholar in computer science whose work bridges artificial intelligence, deep learning, and computer vision to address critical problems in medical imaging. As a PhD Research Scholar at Jeju National University, Republic of Korea, he is focused on developing meta-learning and ensemble-based deep neural frameworks for cancer detection and medical diagnostics. His academic foundation, rooted in strong research training from COMSATS University Islamabad and Gomal University, has shaped his analytical approach to solving real-world computational challenges. Danish has authored impactful papers in leading international journals, including works on breast cancer classification through meta-learning ensemble techniques, automatic melanoma diagnosis via adaptive fine-tuned convolutional networks, and advanced deep learning models for skin cancer classification. His research further extends to projects involving object detection, plant disease recognition, and explainable AI, showcasing a versatile command over both theoretical and applied aspects of machine learning. In addition to his scholarly pursuits, he contributes to academia as a lecturer and mentor, guiding students in computer science and fostering innovation through research-driven pedagogy. His technical proficiency spans Python, TensorFlow, Keras, MATLAB, and computer vision frameworks such as YOLO and GANs, reflecting his comprehensive skill set across AI technologies. Danish’s academic achievements and conference publications highlight his commitment to advancing computational intelligence and medical informatics. A passionate learner and innovator, he envisions leveraging AI-driven solutions to enhance healthcare diagnostics, promote automation, and contribute to scientific progress through collaborative global research.

Profile: Google Scholar

Featured Publications

Ali, M. D., Saleem, A., Elahi, H., Khan, M. A., Khan, M. I., Yaqoob, M. M., et al. (2023). Breast cancer classification through meta-learning ensemble technique using convolution neural networks.

Javid, M. H., Jadoon, W., Ali, H., & Ali, M. D. (2023). Design and analysis of an improved deep ensemble learning model for melanoma skin cancer classification.

Khan, M. A., Mazhar, T., Ali, M. D., Khattak, U. F., Shahzad, T., Saeed, M. M., et al. (2025). Automatic melanoma and non-melanoma skin cancer diagnosis using advanced adaptive fine-tuned convolution neural networks.

Ali, M. D., Mazhar, T., Shahzad, T., Rehman, W. U., Shahid, M., & Hamam, H. (2025). An advanced deep learning framework for skin cancer classification.

Ali, M. D., Han, I. C., & Kim, S. K. (2025). Advanced skin cancer detection using dual partial attention aware multiple convolutional framework

Bhavesh Kataria | AI and Machine Learning | AI & Machine Learning Award

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Dr. Bhavesh Kataria | AI and Machine Learning | AI & Machine Learning Award

Post-Doctoral Fellow at Emory University | United States

Dr. Bhavesh Kataria is a highly accomplished academician, researcher, and innovator in Computer Engineering, recognized globally for his leadership in Artificial Intelligence, Machine Learning, and Digital Image Processing. His professional journey spans academia and research institutions across India and the United States, including his role at Emory University, where he contributes to advanced AI-driven healthcare analytics and digital pathology solutions. With a Ph.D. focused on Optical Character Recognition of Sanskrit Manuscripts using Convolutional Neural Networks, Dr. Kataria has combined technical precision with deep domain expertise to address challenges in multilingual text recognition and medical imaging. His scholarly portfolio includes numerous publications in reputed international journals, multiple granted patents, and several authored books covering cutting-edge topics in AI, cloud computing, and web technologies. An active member of prestigious organizations such as IEEE and ACM, he serves on editorial boards of international journals and as a reviewer for globally recognized publishers like Springer Nature and Science Publishing Group. He has also chaired sessions and reviewed Ph.D. theses, contributing significantly to the academic ecosystem. Dr. Kataria’s pioneering innovations, such as AI-based network visualization tools, smart teaching devices, and healthcare monitoring systems, underscore his commitment to translational research and practical AI applications. Honored with awards including the Best Researcher Award and Teaching Excellence Award, he exemplifies a blend of scholarly excellence, innovation, and mentorship. His dedication to advancing intelligent systems and promoting interdisciplinary research continues to inspire global collaboration in emerging computational technologies.

Profiles: Scopus | ORCID

Featured Publications

Kataria, B., & Jethva, H. B. (2024, September 30). Decentralized security mechanisms for AI-driven wireless networks: Integrating blockchain and federated learning.

Kataria, B. (2024, June 2). Automated detection of tuberculosis using deep learning algorithms on chest X-rays.

Shivadekar, S., Kataria, B., Hundekari, S., Wanjale, K., Balpande, V. P., & Suryawanshi, R. (2023). Deep learning based image classification of lungs radiography for detecting COVID-19 using a deep CNN and ResNet 50.

Shivadekar, S., Kataria, B., Limkar, S., Wagh, K., Lavate, S., & Mulla, R. (2023, June 15). Design of an efficient multimodal engine for preemption and post-treatment recommendations for skin diseases via a deep learning-based hybrid bioinspired process.

Kataria, B., Jethva, H. B., Shinde, P. V., Banait, S. S., Shaikh, F., & Ajani, S. (2023, April 30). SLDEB: Design of a secure and lightweight dynamic encryption bio-inspired model for IoT networks.

Xiaolin Zhu | Computer Vision | Best Researcher Award

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Dr. Xiaolin Zhu | Computer Vision | Best Researcher Award

Lecturer at Xiangtan University | China

Dr. Xiaolin Zhu is a dynamic researcher and lecturer at the School of Automation and Electronic Information, Xiangtan University, China, specializing in advanced computer vision and deep learning. His scholarly pursuits focus on video understanding, group activity recognition, and multi-object tracking, with a strong commitment to developing intelligent algorithms that enhance human–machine perception and real-world visual interpretation. A prolific author, Dr. Zhu has published eight influential papers, including contributions in IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Circuits and Systems for Video Technology, and Expert Systems with Applications, one of which has garnered over one hundred citations. His innovative research has also led to five granted Chinese patents and one software copyright, demonstrating his skill in translating theoretical insights into practical applications. Dr. Zhu has collaborated with top institutions, including the University of Technology Sydney and Shanghai Jiao Tong University, advancing cross-disciplinary innovation and producing four notable joint publications. As a member of professional organizations such as IEEE, the Chinese Association of Automation, and the Chinese Institute of Electronics, he remains an active contributor to the scientific community. His recent comprehensive review on deep learning-based group activity recognition offers a refined taxonomy of methodologies from 2016 to 2024, mapping out the evolution of the field through supervision types, network architectures, modeling mechanisms, and input modalities. Recognized for his rigorous analytical approach and consistent academic excellence, Dr. Zhu represents the new generation of AI scholars pushing the boundaries of visual intelligence and autonomous systems, making significant strides toward the future of intelligent surveillance, human activity analysis, and video-based behavioral prediction.

Profile: Google Scholar

Featured Publications

Zhang, X., & Zhu, X. (2019). Autonomous path tracking control of intelligent electric vehicles based on lane detection and optimal preview method.

Zhu, X., Zhou, Y., Wang, D., Ouyang, W., & Su, R. (2022). Mlst-former: Multi-level spatial-temporal transformer for group activity recognition.

Wu, D., Qu, Z. S., Guo, F. J., Zhu, X. L., & Wan, Q. (2019). Hybrid intelligent deep kernel incremental extreme learning machine based on differential evolution and multiple population grey wolf optimization methods.

Zhu, X., Wang, D., Li, J., Su, R., Wan, Q., & Zhou, Y. (2024). Dynamical attention hypergraph convolutional network for group activity recognition.

Zhu, X., Wang, D., & Zhou, Y. (2023). Hierarchical spatial-temporal transformer with motion trajectory for individual action and group activity recognition.

Manal Hassanien | Medicine Rheumatology | Academic Brilliance Star Award

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Prof. Dr. Manal Hassanien | Medicine Rheumatology | Academic Brilliance Star Award

Professor of Rheumatology at Assuit University | Egypt

Prof. Dr. Manal Hassanien is a distinguished Egyptian rheumatologist and academic leader recognized for her profound contributions to rheumatology, immunology, and rehabilitation medicine. As a Professor and Consultant at Assiut University Hospitals, she has played a central role in advancing musculoskeletal and neuromuscular ultrasound diagnostics and interventions across Upper Egypt. Her professional expertise spans autoimmune diseases, systemic sclerosis, rheumatoid arthritis, and pain management, where she integrates advanced ultrasound-guided procedures and biologic therapies. A prolific researcher, Professor Hassanien has published extensively in high-impact international journals, with notable studies on systemic sclerosis, lupus nephritis, rheumatoid arthritis genetics, and interventional pain management. Her collaborative work with global research networks such as EUSTAR and EULAR underscores her commitment to clinical excellence and translational science. Beyond her research, she has made remarkable contributions to education, mentoring young physicians, and introducing innovative diagnostic and therapeutic practices into clinical settings. Her leadership in establishing the region’s first combined Neuromuscular Ultrasound and Electrodiagnosis Unit has been transformative in improving regional healthcare services. A respected member of leading scientific bodies including the European League Against Rheumatism, the American College of Rheumatology, and the European Scleroderma Trials and Research Group, Professor Hassanien has also been a regular speaker at international conferences. Her scholarly achievements, professional integrity, and dedication to patient care collectively define her as a leading figure in modern rheumatology, embodying the integration of research innovation, compassionate medical practice, and academic mentorship in advancing musculoskeletal and autoimmune disease management globally.

Profiles: Scopus | ORCID

Featured Publications

Barakat, O. M., Badari, M. S., Elgendy, S. G., Abdel Hameed, M. R., Zahran, A. M., Hassanien, M. M. A., & Embarek, M. S. (2024). The expression pattern of NK cells in systemic lupus erythematosus patients with different disease activities.

Abdelrady, M. M., Lam, K. H. S., Shabaan, N., Aboelfadl, G. M., et al. (2024). Selective ultrasound-guided nerve root block improves outcomes for discectomy in patients with cervical disc disease: A randomized, controlled, single-blinded study. Abo Elfadl, G., Osman, A. M., Elmasry, Y. A.-E., & Hassanien, M. (2024). Effect of pulsed radiofrequency to the suprascapular nerve (SSN) in treating frozen shoulder pain: A randomised controlled trial.

Emad, Y., Ragab, Y., Cozzi, D., Ibrahim, O., Abdelrahman, W., Abdelali, M., Kechida, M., Hassanien, M., Tharwat, S., Salah, S., Elshaarawy, N., Frikha, F., Hassanein, S., Young, P., Pankl, S., Barman, B., Abou-Zeid, A., & Rasker, J. J. (2023). Pulmonary vasculitis in Behçet’s disease: Reference atlas computed tomography pulmonary angiography (CTPA) findings and risk assessment-management proposal.

Raouf, M., Alsaeed, M. A., Hassanien, M., & Kamel, E. Z. (2022). Intracarpal midazolam: Does it offer better pain relief than dexamethasone in carpal tunnel syndrome patients? A randomized double-blind clinical trial.

Kevin Chuen Kong Cheong | Business | Best Researcher Award

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Dr. Kevin Chuen Kong Cheong | Business | Best Researcher Award

Lecturer at University of Newcastle | Australia

Dr. Kevin Cheong is a distinguished academic and industry leader whose career bridges business education, sustainable tourism, and organizational innovation. With a Doctorate in Business Administration from Singapore Management University and a Master’s in Finance from Baruch College, City University of New York, he has built a strong foundation in research and practice focused on leadership, governance, and service excellence. As a lecturer at the University of Newcastle (Australia) and Singapore Management University, Dr. Cheong is recognized for his expertise in corporate governance, digital transformation, and sustainability innovation. Beyond academia, his leadership roles at Sentosa 4D Adventureland and Syntegrate reflect his ability to translate theory into impactful real-world applications, while his consultancy work with the Global Sustainable Tourism Council underscores his commitment to advancing responsible and sustainable development practices. Dr. Cheong has significantly influenced the tourism and hospitality sectors through his involvement with the Singapore Tourism Board, the Association of Singapore Attractions, and various national competency framework committees. His publications, including works in Business Process Management Journal (2025), Human Resource Development International (2024), and VINE Journal of Information and Knowledge Management Systems (2022), explore themes such as AI-driven transformation, digital learning, and knowledge management in the new normal. As co-editor of Vision for the Future: Towards More Vibrant, Sustainable and Smart Cities (World Scientific, 2024), he continues to shape discourse on urban sustainability and education. Dr. Cheong’s professional journey exemplifies the integration of academic rigor, strategic leadership, and visionary thinking in fostering sustainable and innovative business ecosystems.

Profile: Scopus

Featured Publication

Tan, K.-L., Yeap, P.-F., Cheong, K. C.-K., & Loganathan, S. R. (2025). Crafting an organizational strategy for the new era: A qualitative study of artificial intelligence transformation in a homegrown Singaporean hotel chain.

Tan, K. L., Loganathan, S. K., Pidani, R. R., Yeap, P. F., Ng, D. W. L., Chong, N. T. S., Liow, M. L. S., Cheong, K. C. K., & Yeo, M. M. L. (2024). Embracing imperfections: A predictive analysis of factors alleviating adult leaders’ digital learning stress on Singapore’s lifelong learning journey.

Menkhoff, T., Kan, S. N., & Cheong, K. C. K. (2024). Vision for the future: Towards more vibrant, sustainable and smart cities.

Tan, K. L., Hii, I. S. H., & Cheong, K. C. K. (2022). Knowledge “hiding and seeking” during the pandemic: Who really wins in the new normal?

Gan, B., Menkhoff, T., Liow, D. J., Cheong, K. C. K., & Mangold, A. (in press). Making sustainability education engaging and motivating for undergraduate students.

Yousef Asadi | Artificial Intelligence | Best Paper Award

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Mr. Yousef Asadi | Artificial Intelligence | Best Paper Award

Master Degree at Bu Ali Sina University | Iran

Mr. Yousef Asadi is a dedicated electrical engineer and researcher whose academic and professional pursuits center on advancing power systems, smart grids, and sustainable energy technologies. With a master’s degree in electrical engineering specializing in power systems from Buali Sina University, his expertise bridges theoretical insight with practical application in energy optimization, control, and artificial intelligence. His scholarly contributions have significantly enriched the field, with impactful publications in top-tier journals such as the Journal of Energy Storage, International Journal of Electrical Power & Energy Systems, Energies, Applied Sciences, and IEEE Access. His works focus on developing intelligent frameworks for energy management, universal models for power converters, and adaptive neural control techniques for active power filters—reflecting a strong interdisciplinary command of power electronics, control theory, and computational intelligence. Asadi’s research interests span microgrid stability, distributed generation, and reinforcement learning-based optimization, positioning him at the forefront of innovation in clean and resilient energy systems. His experiences in teaching, software-hardware setup, and internships across power distribution and aviation electronics have strengthened his technical and analytical capabilities. Fluent in English, Persian, and Kurdish, he demonstrates effective communication across diverse professional environments. Known for his proficiency in MATLAB, Python, and electrical design software, he applies computational modeling and automation to solve real-world energy challenges. His continuous pursuit of advanced, sustainable solutions reflects a commitment to bridging academia and industry for the development of smarter, more efficient energy infrastructures. Through his research and technical acumen, Yousef Asadi exemplifies a new generation of engineers dedicated to transforming the global energy landscape through innovation and intelligent system design.

Profile: Scopus

Featured Publications

Mansouri, M., Eskandari, M., Asadi, Y., & Savkin, A. (2024). A cloud-fog computing framework for real-time energy management in multi-microgrid system utilizing deep reinforcement learning.

Asadi, Y., Eskandari, M., Mansouri, M., Moradi, M. H., & Savkin, A. V. (2023). A universal model for power converters of battery energy storage systems utilizing the impedance-shaping concepts.

Asadi, Y., Eskandari, M., Mansouri, M., Savkin, A. V., & Pathan, E. (2022). Frequency and voltage control techniques through inverter-interfaced distributed energy resources in microgrids

Asadi, Y., Eskandari, M., Mansouri, M., Chaharmahali, S., Moradi, M. H., & Tahriri, M. S. (2022). Adaptive neural network for a stabilizing shunt active power filter in distorted weak grids.

Mansouri, M., Eskandari, M., Asadi, Y., Siano, P., & Alhelou, H. H. (2022). Pre-perturbation operational strategy scheduling in microgrids by two-stage adjustable robust optimization.

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