Vikas Verma | Computer Science | Young Scientist Award

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Mr. Vikas Verma | Computer Science
| Young Scientist Award

The ICFAI University, Jaipur | India

Dr. Vikas Verma’s research contributions focus extensively on Software Defined Networking (SDN), Machine Learning, and Network Optimization, emphasizing energy efficiency, intelligent routing, and data-driven automation. His doctoral research, “Flow Classification and Energy Efficient Routing in Software Defined Networks Using Machine Learning Techniques,” explores the integration of adaptive algorithms for sustainable network management. His projects, including “Routing Optimization for Software-Defined Networking Using Machine Learning Techniques and Multi-Domain Controller” and “Industry-Academia Collaboration of SME with Academics,” demonstrate practical applications of AI in networking and innovation ecosystems. Dr. Verma’s publications in high-impact journals and conferences, such as the Philippine Journal of Science, Suranaree Journal of Science and Technology, IEEE Xplore, and Springer CCIS, address key advancements in SDN, IoT-based smart farming, and quantum communication security. His work “Energy-Efficient Techniques in SDN: Software, Hardware, and Hybrid Approaches” and “Comparative Analysis of Quantum Key Distribution Protocols” highlight optimization in computing systems and secure data transmission. Additionally, he holds two UK design patents—one for an AI-driven finance management device and another for a medical diagnostic system using saliva-based biomarkers. His current research extends to privacy preservation, intelligent traffic classification, and predictive analytics, establishing his expertise in sustainable and secure intelligent network systems.

Featured Publications

Verma, V., & Jain, M. (2024). Energy-efficient techniques in SDN: Software, hardware, and hybrid approaches. Philippine Journal of Science, 153(1).

Agarwal, N., & Verma, V. (2023). Comparative analysis of quantum key distribution protocols: Security, efficiency, and practicality. In Proceedings of the International Conference on Artificial Intelligence of Things (pp. 151–163).

Verma, V., Ramakant, Mathur, H., & Agarwal, N. (2022). IoT assisted smart farming using data science techniques. In 2022 IEEE World Conference on Applied Intelligence and Computing (AIC). IEEE.

Verma, V. (2017). Automatic mood classification of Indian popular music. International Journal for Research in Applied Science and Engineering.

Verma, V., & Jain, M. (2023). Optimization of routing using traffic classification in software defined networking. Suranaree Journal of Science and Technology, 30(1), 010198(1–8).*

Mohit Yadav | Computer Science | Young Scientist Award

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Mr. Mohit Yadav | Computer Science | Young Scientist Award

Dayalbagh Educational Institute | India

Mohit Yadav is a passionate researcher and emerging technologist currently working as an Intern at the Scientific Computing Virtual Lab, a Ministry of Education-supported project at the Department of Physics and Computer Science, Dayalbagh Educational Institute, Agra. He holds a Master’s degree in Computer Science with a dissertation on adaptive penalty function approaches using particle swarm optimization for constraint satisfaction problems, a Bachelor’s degree in Internet of Things, and a Diploma in Information Technology with a specialization in software development. Mohit has extensive experience as a Full Stack Developer, Mobile Application Developer, and Python Developer across academic and industry projects. He has authored several high-impact publications in IEEE conferences and journals, contributing to research on Industry 4.0 and 5.0 innovations, IoT-enabled precision farming, smart residences, aerial swarm robotics, and AI-integrated drones. His work also includes book chapters and international and national patents in drone technology, IoT-based irrigation, and high-payload unmanned aerial vehicles. With technical expertise spanning Python, Java, mobile application development, embedded systems, drone piloting, and database management, he has delivered keynote speeches, chaired sessions, and served as an invited editor and reviewer for international journals, demonstrating active engagement in the research community. Mohit has participated in numerous workshops, seminars, short-term courses, industrial visits, and innovation competitions, earning recognitions such as the Smart India Hackathon award and drone racing accolades. His research has been cited by 24 documents, with three publications and an h-index of 2. Beyond academics and professional work, he contributes to social service initiatives, including NSS programs and biometric volunteering at medical camps, showcasing his commitment to societal impact through technology and innovation.

Featured Publications

Yadav, M. (2024, August 1). High Speed VTOL Remote Controlled Drone [Patent]. Government of India.

Yadav, M., Chauhan, A. S., & Saini, S. (2024, February 24). Appraisal study and analytics of Industrial 4.0: A rebellion towards existing twins. In 2024 IEEE International Students’ Conference on Electrical, Electronics and Computer Science (SCEECS).

Yadav, M., Chauhan, A. S., & Saini, S. (2024, February 24). IoT and IoE transformations in precision farming agriculture: Sensor-based monitoring, automated irrigation, and livestock monitoring. In 2024 IEEE International Students’ Conference on Electrical, Electronics and Computer Science (SCEECS).

Yadav, M. (2023, August 5). Light Weight Drone. GOV.UK.

Yadav, M., Chauhan, A. S., & Saini, S. (2023, February 18). A study on creation of Industry 5.0: New innovations using big data through artificial intelligence, Internet of Things, and next-origination technology policy. In 2023 IEEE International Students’ Conference on Electrical, Electronics and Computer Science (SCEECS).

Julio Espinosa Domínguez | Computer Science | Best Researcher Award

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Mr. Julio Espinosa Domínguez | Computer Science | Best Researcher Award

PHD at Transilvania University of Brasov, Romania.

Julio Espinosa Dominguez is a passionate Cuban researcher in electrical engineering, currently pursuing his PhD at Transilvania University of Brașov in Romania, with a strong foundation in power systems, energy management, and grid protection. With academic roots in CUJAE, Havana, Julio has blended teaching, research, and real-world problem-solving in the realm of electrical infrastructure. His background includes extensive involvement in simulation, fault detection, energy storage integration, and voltage regulation under weak grid conditions. Dedicated to energy stability and system optimization, he has authored several peer-reviewed publications that reflect a deep understanding of challenges in electric arc furnaces, generator protection, and transformer behavior. Julio’s global perspective, research-driven approach, and adaptability in both academic and industrial contexts make him a promising contributor to the energy sector. He thrives in cross-cultural environments, merging Latin American experience with European innovation to drive forward-thinking solutions for resilient, efficient, and future-ready power systems.

Profile

Googl Scholar

🎓 Education 

Julio’s academic journey began with a Bachelor’s degree in Electrical Engineering from the Technological University of Havana, where he mastered power generation principles, distribution, and electrical machines. He progressed to a Master’s program at the same institution, focusing on energy system reliability, protection coordination, and system-level fault analysis using simulation tools like DIgSILENT PowerFactory. Currently, he is pursuing doctoral studies at Transilvania University of Brașov, Romania, specializing in modern power electronics, voltage perturbation ride-through mechanisms, and grid code compliance for converter technologies. His education emphasizes a balance of theoretical foundations, hands-on engineering practices, and research methodologies. Julio has built competencies in high-voltage engineering, advanced control systems, and renewable integration, equipping him to analyze and improve electrical infrastructures. With international academic exposure and multilingual capabilities, he contributes to a globalized understanding of energy challenges, sustainability, and smart grid advancements. His learning pathway reflects consistent growth and a commitment to technical excellence.

🧪 Experience 

Julio gained significant academic and applied experience as an Instructor Professor at the Technological University of Havana, where he taught and guided students in courses related to electrical circuits, protection systems, and energy distribution. During this period, he collaborated on multiple national projects focusing on generator protection, capacitor bank failures, and electric arc furnace integration using energy storage systems. Transitioning into research, he engaged in simulation-based analyses to detect and correct inefficiencies in industrial power systems. At present, he continues his research as a PhD student, addressing topics such as zero-sequence impedance behavior and reconfiguration of power distribution to reduce losses. He consistently uses tools like DIgSILENT and MATLAB for advanced system modeling and fault studies. His experience bridges academic teaching, technical consulting, and applied research, making him proficient in both analytical and solution-oriented domains of electrical engineering. His career reflects dedication to innovation and system improvement within dynamic energy environments.

🏅 Awards & Honors 

Julio’s recognition primarily stems from the technical impact of his published work and his contributions to improving Cuba’s power system performance. His studies on generator protections, energy storage integration, and power system losses have been featured in reputed journals and conferences, reflecting peer recognition. Projects like enhancing MAN generator protections and resolving issues in Antillana de Acero have contributed to his professional reputation. Though formal international awards are not explicitly listed, his work has earned commendation in academic and institutional settings for relevance and applicability. His doctoral research in Romania was competitively selected, underlining academic merit and research potential. Julio’s consistent publication record from 2020 to 2024, addressing core topics in grid stability and electrical infrastructure, highlights his commitment to research excellence. His knowledge has informed real-world implementations, elevating the performance of weak grids and aligning with national energy priorities, establishing him as an emerging leader in electrical engineering.

🔬 Research Focus 

Julio’s research revolves around the stability, protection, and optimization of electrical power systems, with a sharp focus on grid integration challenges, converter behavior under disturbances, and energy storage coordination with high-demand equipment like electric arc furnaces. He explores how voltage perturbation ride-through strategies can ensure grid compliance and robustness, particularly in systems with weak infrastructure. His investigations into zero-sequence impedance and transformer behavior offer insights into protective relay performance and system vulnerabilities. Using advanced simulation platforms, he designs solutions that mitigate power losses, improve system efficiency, and support the integration of renewable energy. Julio also delves into reconfiguration strategies for medium-voltage networks, aiming to reduce technical losses and increase reliability in energy distribution. His work contributes to building smarter, more adaptive power systems aligned with global energy transition goals. Focused on both theoretical modeling and applied innovation, his research aligns academic rigor with practical utility, particularly for developing and transitional energy markets.

 Conclusion

Julio Espinosa Domínguez is a highly motivated and competent researcher with a clear focus on solving practical and theoretical problems in electrical energy systems. His transition to doctoral research in Europe, along with a strong portfolio of projects and publications, showcases his potential as a future leader in power systems engineering. With targeted efforts to internationalize and scale the impact of his work, he stands as an excellent nominee for the Best Researcher Award.

📝Publications 

  1. Modificaciones al Relé NSR 376 SA para Grupos Electrógenos de la Tecnología MTU
    2021 | A Dean Labrada, R Ponce Iglesias, OE Torres Breffe | 4

  2. Use of Battery Energy Storage with Electric Arc Furnace to Improve Frequency Stability of Weak Power System
    2021 | JE Dominguez, J Rekola, OET Breffe, CR Capablanca | 3

  3. Una solución integral para los problemas de suministro eléctrico de Antillana de Acero
    2020 | OE Torres Breffe, J Espinosa Domínguez, C Revuelta Capablanca, … | 3

  4. The Impact of Electric Arc Furnaces on the Cuban Power System: Existing Approaches and Future Prospects
    2023 | JE Domínguez, OET Breffe, I Serban, CB González, CR Capablanca | 2

  5. Las Oscilaciones de Potencia y sus retos a las protecciones de distancia en Cuba
    2022 | OP Baluja, OET Breffe, JE Domínguez, RP Hermoso | 2

  6. Enhancing the Control of a DC/AC Converter for Voltage Perturbation Ride-Through in Compliance with the Cuban Grid Code
    2024 | JE Domínguez, I Serban, OET Breffe | 1

  7. Propuesta de reconfiguración del esquema de distribución de la Zona Especial de Desarrollo Mariel
    2024 | C Sigas Martínez, OE Torres Breffe, J Espinosa Domínguez, … | 1

  8. Experiencia sobre la avería de un transformador de corriente ubicado en el neutro de un banco de condensadores. Caso de estudios subestación Tallapriedra
    2021 | DÁ Audevert, OET Breffe, JE Domínguez | 1

  9. Mejoras a las protecciones de los Grupos Electrógenos MAN. Caso de estudio Centra Ariguanabo
    2021 | R Olalde Estuch, OE Torres Breffe, J Espinosa Domínguez, … | 1

 

Xinxin Luo | Computer Science| Best Researcher Award

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Dr. Xinxin Luo | Computer Science | Best Researcher Award

Southeastern University, China

Xinxin Luo is a dedicated Ph.D. candidate in Cyberspace Security at Southeast University, China, with research interests in trustworthy AI, causal inference, and spatio-temporal graph neural networks. She holds a Master’s in Intelligent Science and Technology from NUPT and a Bachelor’s in Electronic Information Engineering from Hefei Normal University. Xinxin has authored several high-impact papers and presented at international conferences, contributing to robust AI systems by integrating causal structures into machine learning. Her work blends deep theoretical knowledge with practical implementations in AI-driven forecasting and decision support.

Profile

🎓 Education

Xinxin Luo is pursuing her Ph.D. (2021–2025) at the School of Cyber Science and Engineering, Southeast University, focusing on trustworthy AI. She earned her Master’s degree in Intelligent Science and Technology (2018–2021) from the College of Automation & AI at NUPT, and her Bachelor’s degree in Electronic Information Engineering (2013–2017) from Hefei Normal University. Her educational path reflects a deep foundation in intelligent systems, machine learning, and electronic engineering, forming the basis for her cutting-edge work in AI and causal inference.

💼 Experience

Xinxin has actively contributed to AI R&D through national key projects, where she developed anomaly detection algorithms and integrated ML with big data for real-time monitoring. She interned at Zhejiang Zijiang Laboratory, applying deep learning for human motion recognition. Xinxin also led a provincial project creating an interpretable SME rating system, showcasing her ability to translate theoretical insights into practical applications. Her hands-on experience spans spatio-temporal modeling, causality analysis, and real-world AI implementations in both academic and industrial environments.

🏅 Awards & Honors

Xinxin Luo has received recognition through multiple high-impact publications, including journals like Engineering Applications of AI and Journal of Artificial Intelligence Research. Her accepted conference presentations (e.g., ICCBR2024, PRICAI2024) and under-review articles in top-tier journals reflect academic excellence. She holds a patent in zero-shot learning and a software copyright for AI-based chart recognition. Her contributions to national and provincial research projects and successful leadership in AI system design highlight her innovation and technical prowess.

🔬 Research Focus

Xinxin focuses on trustworthy AI through the lens of causal inference and spatio-temporal graph neural networks. Her research explores dynamic causal structure learning for time series forecasting, addresses confounding bias, and incorporates counterfactual reasoning into predictive models. She investigates causal mechanisms behind data to enhance fairness, interpretability, and robustness in AI systems. Additionally, Xinxin integrates situational awareness with causal levels (observation, intervention, counterfactual) to improve intelligent decision-making. Her vision aims at building secure, human-centered, and future-aware AI.

 Conclusion

Xinxin Luo exemplifies the qualities of an outstanding researcher: deep technical expertise, a strong publication record, and a proven ability to translate theory into practice. By augmenting her grant-acquisition skills and widening her collaborative networks, she can elevate her already remarkable contributions to even greater international prominence. Her dedication to human-centered, trust-grounded AI renders her a highly deserving candidate for the Best Researcher Award.

Publication

  1. A Novel Approach of Causality Matrix Embedded into the Graph Neural Network for Forecasting the Price of Bitcoin

    • Authors: Xinxin Luo, Wei Yin, Xiao Bo

    • Journal: Engineering Applications of Artificial Intelligence

  2. Dynamic Causal Structure Learning for Spatio-Temporal Graph Forecasting

    • Authors: Xinxin Luo, Wei Yin, Zhuang Li

    • Journal: IEEE Transactions on Reliability

  3. Causal Spatio-Temporal Graph Forecasting Against Confounding Bias

    • Authors: Xinxin Luo, Wei Yin, Xiao Bo, Fan Wu

    • Journal: Journal of Artificial Intelligence Research

  4. Deconfounded Spatio-temporal Prediction with Causal-based Graph Neural Networks

    • Authors: Xinxin Luo, Wei Yin, Zhuang Li

    • Journal: Complex & Intelligent Systems

    • Ranking: JCR Q1

  5. Multi-view Deep Generative Dual Fusion Network for Zero-shot Learning

    • Authors: Xinxin Luo, Wei Yin, Xiao Bo

    • Journal: Multimedia Tools and Applications

    • Ranking: JCR Q2

  6. Forecasting Cryptocurrencies’ Price with the Financial Stress Index: A Graph Neural Network Prediction Strategy

    • Authors: Wei Yin, Ziling Chen, Xinxin Luo, Berna Kirkulak-Uludag

    • Journal: Applied Economics Letters

    • Ranking: JCR Q3