Akriti Gupta | Artificial Intelligence | Women Researcher Award

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Dr. Akriti Gupta | Artificial Intelligence | Women Researcher Award

Assistant Professor | IIBS | India

Dr. Akriti Gupta’s research focuses on the application of artificial intelligence and advanced analytical techniques to understand human behavior within organizational and business contexts. Her work integrates decision sciences, organizational psychology, and data-driven modeling to examine factors influencing employee behavior, workplace performance, and managerial effectiveness. By employing comparative machine learning and statistical approaches, she contributes to evidence-based insights that support improved organizational outcomes and policy formulation. Her publications in Scopus-indexed journals reflect an interdisciplinary orientation, combining theory with practical relevance. Overall, her research advances the use of AI-enabled methods for behavioral analysis, supporting innovation in management practices and organizational decision-making.

Citation Metrics (Scopus)

60

50

40

30

20

10

Citations
57

Documents
9

h-index
3


View Scopus Profile

Featured Publications

Didier Torres Guzmán | Machine Learning | Best Researcher Award

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Dr. Didier Torres Guzmán | Machine Learning | Best Researcher Award

Professor | National Autonomous University of Mexico | Mexico

Dr. Didier Torres Guzmán is a distinguished researcher whose work focuses on biomedical signal processing, neuroimaging, and the application of machine learning to clinical diagnostics. His research contributions have advanced the understanding and analysis of neurological and physiological conditions, particularly through the development of innovative computational biomarkers and signal processing techniques. Notably, he has explored tortuosity and discrete compactness biomarkers for machine learning-based classification of mild cognitive impairment, providing new tools for early and accurate detection of cognitive decline. In addition, his studies on discrete neuroimaging metrics have enabled the identification of structural brain alterations associated with COVID-19, highlighting the relevance of his work to pressing global health challenges. Dr. Torres Guzmán has also contributed to non-invasive physiological monitoring, including methods for estimating heart and respiratory rates through face video processing and novel approaches for ECG signal morphology analysis using tortuosity estimation. His work consistently demonstrates a combination of methodological rigor, interdisciplinary application, and translational potential, bridging computational techniques with practical healthcare solutions. The originality and impact of his research are reflected in his publications in high-quality peer-reviewed journals and book chapters, where he collaborates with international researchers across biomedical engineering, signal processing, and clinical disciplines. Through these contributions, Dr. Torres Guzmán has established himself as a leading figure in his field, whose work not only advances scientific knowledge but also has tangible implications for improving patient care, diagnostic accuracy, and the integration of artificial intelligence in biomedical research, making him a highly deserving candidate for recognition with the Best Researcher Award.

Profile: ORCID | Scopus

Featured Publications

Torres Guzmán, D., Pinzón Vivas, J. D., & Barbará Morales, E. (2026). Tortuosity and discrete compactness biomarkers for machine learning-based classification of mild cognitive impairment. Biomedical Signal Processing and Control.

Delgado-Castillo, D., Barbará-Morales, E., Hevia-Montiel, N., Arámbula-Cosío, F., & Torres Guzmán, D. (2025). Discrete neuroimaging metrics for identifying structural alterations in COVID-19-related brain atrophy. International Journal of Online and Biomedical Engineering (iJOE).

Ruíz-Espinosa, G., Jimenez-Angeles, L., Torres Guzmán, D., Rojas-Arce, J. L., & Marmolejo-Saucedo, J. A. (2024). A comparison of algorithms to estimate heart and respiratory rate from face video processing. In Book chapter.

Pacheco González, L. E., Torres Guzmán, D., & Barbará-Morales, E. (2024). A novel method for ECG signal morphology analysis using tortuosity estimation. Biomedical Signal Processing and Control.

Jaime Iván López Veyna | Machine Learning | Best Researcher Award

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Prof. Dr. Jaime Iván López Veyna | Machine Learning | Best Researcher Award

Prof. Dr. Jaime Iván López Veyna | National Technological Institute | Mexico

Prof. Dr. Jaime Iván López Veyna is a distinguished computer scientist whose research focuses on search engines, keyword search, big data, and data analytics, with notable contributions to web mining, natural language processing (NLP), and the semantic web. His scholarly work demonstrates a strong interdisciplinary approach, integrating artificial intelligence and data science to address societal and technological challenges such as cybercrime detection, cyberbullying prevention, and public health analytics. Prof. Dr. Jaime Iván López Veyna has developed intelligent systems for detecting harmful online behaviors, leveraging big data analytics and NLP to enhance digital safety and understanding of internet communication. His publications also explore the intersection of data representation, machine learning, and human-computer interaction, with applications extending to mHealth technologies and educational contexts. In recent years, he has applied machine learning models to predict health outcomes and psychological conditions, such as COVID-19 recovery patterns and postpartum depression, underscoring his commitment to socially impactful computational research. Recognized by Mexico’s National System of Researchers (SNI) and the Programa para el Desarrollo Profesional Docente for his academic excellence, Prof. Dr. Jaime Iván López Veyna has contributed extensively to the advancement of intelligent systems and semantic technologies. His body of work, published in reputable journals and conferences, reflects a deep engagement with emerging challenges in information retrieval, web intelligence, and data-driven decision-making, positioning him as a leading figure in applied computational research in Mexico and the global research community.

Profiles: Scopus | Orcid | Google Scholar

Featured Publication 

Lopez-Veyna, J. I. (2020). Intelligent system for detection of cybercrime vocabulary on websites. DYNA, 95(5), 1–8.

Lopez-Veyna, J. I. (2020). Internet data analysis methodology for cyberterrorism vocabulary detection, combining techniques of big data analytics, NLP and semantic web. International Journal on Semantic Web and Information Systems, 16(1), 45–63.

Lopez-Veyna, J. I. (2019). Helping students detecting cyberbullying vocabulary in Internet with web mining techniques. 2019 International Conference on Inclusive Technologies and Education (CONTIE), 1–5.

Lopez-Veyna, J. I. (2018). Analyzing typical mobile gestures in mHealth applications for users with Down syndrome. Mobile Information Systems, 2018, 1–10.

Lopez-Veyna, J. I. (2017). Combinación de técnicas de Big Data Analytics y Web Semántica para la detección de vocabulario de acoso escolar en Internet. DYNA Ingeniería e Industria, 92(3), 1–7.

 

Omar | Artificial Intelligence | Best Researcher Award

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Dr. Omar | Artificial Intelligence | Best Researcher Award

Assistant Professor, King Saud University, Saudi Arabia

Dr. Omar, an accomplished Assistant Professor at King Saud University, is a leading researcher in Artificial Intelligence, High Performance Computing, and Parallel Processing with extensive expertise in interconnection networks. He earned his Ph.D. in Computer Science from Oregon State University, USA, in 2014, with a dissertation on “One-to-Many Node Disjoint Paths Routing in Generalized Hypercube, Dense Gaussian, and Hexagonal Mesh Networks,” following an M.Sc. in Computer Science (2007) and a B.Sc. in Computer Science (2004) from King Saud University, both completed with distinction. Professionally, Dr. Omar has over a decade of experience at King Saud University, including roles as Assistant Professor, Chief Information Officer, and Board Member at Knowledge Developers, where he has demonstrated exceptional leadership in managing teams, strategic IT initiatives and organizational digital transformation. He is actively engaged in teaching programming languages, data structures, artificial intelligence and parallel processing, while supervising student graduation projects. His research contributions include the development of novel routing algorithms that reduce communication latency in parallel systems, particularly in node-to-set routing across advanced interconnection networks. Dr. Omar has authored seven publications with 78 citations and an h-index of 4, reflecting his impact on both theoretical and applied aspects of computing. His technical proficiency spans Java, JavaScript, Shell Scripting, PHP, XML, Oracle, SQL Server, MySQL, Data Warehousing, Business Intelligence, Cloud Computing, Linux and IT systems integration, alongside strong competencies in project management, stakeholder engagement and executive leadership. He has earned recognition for his contributions to research, teaching and institutional development and is an active member of professional societies, holding certifications in project management and data governance. Dr. Omar’s research interests include advancing parallel processing frameworks, designing high-performance routing protocols, and applying AI techniques to computational optimization. His dedication to mentoring, innovation and collaborative research positions him as a future leader in global computing research. Dr. Omar is highly deserving of recognition for his outstanding contributions to Artificial Intelligence and High Performance Computing, demonstrating a blend of technical expertise, academic excellence, leadership and potential to influence the next generation of researchers and technological advancements worldwide.

Profile: Scopus | ORCID | Google Scholar | ACM Digital Library | LinkedIn 

Featured Publications

  • Al-Ahmadi, S., Alotaibi, A., & Alsaleh, O. (2022). PDGAN: Phishing detection with generative adversarial networks. IEEE Access, 10, 42459–42468.

  • Alsaleh, O., Bose, B., & Hamdaoui, B. (2015). One-to-many node-disjoint paths routing in dense Gaussian networks. The Computer Journal, 58(2), 173–187.

  • Alsaleh, O., Venkatraman, P., Hamdaoui, B., & Fern, A. (2011). Enabling opportunistic and dynamic spectrum access through learning techniques. Wireless Communications and Mobile Computing, 11(12), 1497–1506.

  • Alsaleh, O., Hamdaoui, B., & Fern, A. (2010). Q-learning for opportunistic spectrum access. In Proceedings of the 6th International Wireless Communications and Mobile Computing Conference (IWCMC) (pp. 1–6). ACM.

  • Alsaleh, O., Hamdaoui, B., & Rayes, A. (2012). Improving quality of data user experience in 4G distributed telecommunication systems. In Proceedings of the 2012 International Conference on Collaboration Technologies and Systems (CTS) (pp. 1–10).

 

Jurgita Malaiškienė | Innovation | Women Researcher Award

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Dr. Jurgita Malaiškienė| Innovation | Women Researcher Award

Chief researcher, Vilnius Gediminas technical university, Lithuania

Dr. Jurgita Malaiškienė (🎂 1979-05-02) is the Chief Researcher at the Laboratory of Composite Materials, Vilnius Gediminas Technical University 🏛️. With a strong academic background in Civil Engineering 👷‍♀️, she holds a Ph.D. in Technological Sciences (2008) 🎓. Her expertise centers on ceramic and cementitious materials, sustainable construction, and the application of nano-additives 🧪. Jurgita has held various academic and research positions since 2008, actively contributing to innovation in material science and engineering 🔬. She is also involved in project evaluation and education development across Lithuania 📘🇱🇹, reflecting her dedication to academic excellence and applied research 🚀.

Profile:

🎓 Education & 👩‍🔬 Professional Experience:

Dr. Jurgita Malaiškienė earned her B.Sc. 📘 (2001) and M.Sc. 📗 (2003) degrees in Civil Engineering from Vilnius Gediminas Technical University (VILNIUS TECH), followed by a Ph.D. 📕 in Technological Sciences (Civil Engineering) in 2008. Her professional journey began as a Researcher 🔬 at the Department of Building Materials, VILNIUS TECH (2008–2014). She also served as an Associate Professor 👩‍🏫 from 2009–2011 and again in 2013–2014. After a period of maternity and parental leave 👶 (2014–2016), she resumed work as a Senior Researcher 🧪 at the Research Institute of Building Materials (2016–2017) and later as a Professor 🧯 (2018–2019). In parallel, she contributed as an LVPA Assessor ✅ (2017–2018, 2023–2024). From 2017–2023, she worked as a Senior Researcher 🧬 at the Laboratory of Composite Materials and has been serving as the Chief Researcher 👩‍🔬 since 2023.

🔹Professional Development :

Dr. Malaiškienė has consistently enhanced her professional skills through specialized courses and seminars 🎓💼. From 2005–2008, she participated in human resource improvement seminars for civil engineering 🧑‍🏫. She deepened her expertise in thermal analysis and calorimetry in 2008 🌡️. Over the years, she has embraced new technologies and innovations, attending seminars like “Smart Building” (2013) 🏢💡 and courses on product development, R&D commercialization, and innovative teaching strategies 📊🧠. Her pedagogical knowledge was reinforced through dedicated courses in 2015, shaping her holistic approach to research, teaching, and industry collaboration 👩‍🏫🔬.

🔹 Research Focus :

Dr. Malaiškienė’s research revolves around ceramic and cementitious building materials 🧱🧪, with a strong emphasis on sustainability and innovation 🌍. She explores the utilization of industrial waste ♻️, enhancing the eco-efficiency of construction materials. Her studies also investigate the impact of chemical admixtures and nano additives on structural and performance properties of cement-based composites 🧬🏗️. She applies mathematical modeling to predict material behavior and optimize compositions based on key parameters 📈📐. Her interdisciplinary work bridges material science and environmental engineering, driving advances in next-generation, high-performance construction materials 🏘️🚀.

🔹Publication Top Notes :

1. Effect of Pozzolanic Additive on Properties and Surface Finish Assessment of Concrete

  • Citation:
    Girskas, G., Kriptavičius, D., Kizinievič, O., & Malaiškienė, J. (2025). Effect of Pozzolanic Additive on Properties and Surface Finish Assessment of Concrete. Buildings, 15(10), 1617. 

  • Summary:
    This study investigates the impact of a pozzolanic additive on concrete’s properties and surface finish. The additive reduced flowability, density, and ultrasonic pulse velocity while increasing entrained air content and reducing porosity. These changes suggest potential benefits for durability and surface quality in concrete applications.

2. Influence of Different Binders on the Municipal Solid Waste Incineration Fly Ash Granulation-Based Stabilization Process

  • Citation:
    Shevtsova, M., Malaiškienė, J., Škamat, J., & Antonovič, V. (2025). Influence of Different Binders on the Municipal Solid Waste Incineration Fly Ash Granulation-Based Stabilization Process. Sustainability, 17(10), 4573.

  • Summary:
    The research evaluates how various binders affect the stabilization of municipal solid waste incineration fly ash (MSWI FA). Findings indicate that while cement-based solidification/stabilization techniques can immobilize heavy metals, they are less effective in reducing the mobility of chlorides and sulfates. Pre-treatment washing is recommended to enhance ash stability for potential reuse in construction materials.

3. Utilisation of Different Types of Glass Waste as Pozzolanic Additive or Aggregate in Construction Materials

  • Citation:
    Bekerė, K., & Malaiškienė, J. (2025). Utilisation of Different Types of Glass Waste as Pozzolanic Additive or Aggregate in Construction Materials. Processes, 13(5), 1613.

  • Summary:
    This article explores the potential of using glass waste as a fine or coarse aggregate in concrete or mortar mixtures, replacing traditional materials like sand and gravel. The study highlights the environmental benefits, including reduced CO₂ emissions during clinker manufacturing, by incorporating dispersed glass into blended cements.

4. An Analysis of a Cement Hydration Process Using Glass Waste from Household Appliances as a Supplementary Material

  • Citation:
    Bekerė, K., Malaiškienė, J., & Škamat, J. (2025). An Analysis of a Cement Hydration Process Using Glass Waste from Household Appliances as a Supplementary Material. Processes, 13(3), 840.

  • Summary:
    The study examines the feasibility of using glass waste from household appliances as a supplementary material in cement-based products. It analyzes the chemical and mineral compositions, particle morphology, and size distribution of the glass waste, assessing its suitability as a replacement additive in cement hydration processes.

5. Influence of Pozzolanic Additives on the Structure and Properties of Ultra-High-Performance Concrete

  • Citation:
    Malaiškienė, J., & Jakubovskis, R. (2025). Influence of Pozzolanic Additives on the Structure and Properties of Ultra-High-Performance Concrete. Materials, 18(6), 1304.

  • Summary:
    This paper explores the structural changes and performance improvements in ultra-high-performance concrete (UHPC) when pozzolanic additives are incorporated. The study confirms enhancements in strength, density, and durability due to the pozzolanic reaction and refined microstructure, suggesting viable applications in high-demand structural elements.

🔹Conclusion:

Dr. Jurgita Malaiškienė’s distinguished career, scientific rigor, and meaningful contributions to sustainable material science make her a highly deserving nominee for the Best Researcher Award. Her work not only advances engineering knowledge but also delivers tangible benefits to society and the environment—embodying the spirit of this prestigious recognition.

Paulo Eugênio da Costa Filho | Artificial Intelligence | Best Researcher Award

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Mr. Paulo Eugênio da Costa Filho | Artificial Intelligence | Best Researcher Award

Researcher at Federal University of Rio Grande do Norte, Brazil

Paulo Eugênio da Costa Filho is a dedicated Brazilian researcher and educator in the field of Food Science and Technology, with a strong focus on Food Microbiology. He has played pivotal roles in advancing food safety and quality, particularly through microbiological analysis of food and food products. With over two decades of academic and scientific experience, he serves as a full professor at the Federal University of Ceará (UFC). Prof. Costa Filho is also recognized for his involvement in graduate education and leadership in various research projects and academic societies.

Profile

Education :

The academic journey of this accomplished scholar reflects a deep-rooted commitment to excellence in food science and engineering. They hold a Bachelor’s degree in Food Engineering from the Federal University of Ceará (1993), which laid a strong foundation in the principles of food processing and safety. Advancing their expertise, they pursued both a Master’s (1997) and a PhD (2003) in Food Science and Technology at the Federal University of Viçosa, where they honed their research skills and specialized knowledge in food systems. Their academic path culminated with a prestigious postdoctoral research tenure at Université Laval, Canada (2009), further enriching their global perspective and scholarly contributions to the field.

Experience :

Since 2016, the researcher has served as a Full Professor in the Department of Food Technology at the Federal University of Ceará (UFC), where they specialize in the Microbiology of Foods. In this capacity, they have played a pivotal role in shaping both academic and research directions within the field. As Coordinator of the Graduate Program in Food Science and Technology at UFC, they have demonstrated strong leadership in advancing graduate education, curriculum development, and research collaboration. Their international experience includes a valuable period as a Visiting Researcher at Université Laval in Canada, where they completed a postdoctoral fellowship, further enriching their expertise and fostering cross-border scientific exchange.

Awards and Recognitions :

Prof. Paulo Eugênio da Costa Filho is a CNPq Research Productivity Fellow – Level 1D, a prestigious recognition awarded to researchers with a consistent and influential scientific output in Brazil. This honor reflects his long-standing contributions to advancing food microbiology and food safety through innovative research and academic leadership. His impactful role in graduate education is equally distinguished; Prof. Costa Filho has been nationally recognized for his dedication to mentoring future scientists and for strengthening the graduate training infrastructure in Food Science and Technology across Brazil. His efforts have significantly influenced both academic excellence and professional development in the field.

Research Focus :

The researcher’s work in Food Microbiology is distinguished by a comprehensive and applied focus on critical areas impacting food safety and innovation. Their research emphasizes the study of pathogenic microorganisms in foods, addressing public health concerns through advanced microbiological quality control practices. They actively investigate antimicrobial compounds and bacterial biofilms, contributing to the understanding and mitigation of microbial resistance in food environments. A significant part of their work involves the development and validation of analytical methods for the precise detection and control of microorganisms, ensuring the reliability and safety of food systems. Additionally, they explore the functional properties of probiotic and antimicrobial food components, aiming to enhance the nutritional and protective qualities of food products. This multifaceted research approach reflects a strong commitment to advancing food microbiology through both scientific rigor and real-world application.

Research  Skills :

With extensive expertise in microbiological analysis of foods, this professional is deeply committed to advancing food safety and quality assurance through rigorous scientific approaches. Their work emphasizes the design of microbiological research methodologies tailored to emerging foodborne challenges and technological innovations. In addition to research, they play a pivotal role in graduate student mentorship and thesis supervision, nurturing the next generation of food scientists with a focus on critical thinking and applied microbiology. Their capacity for project coordination and academic leadership has consistently driven collaborative initiatives, strengthened interdisciplinary networks, and elevated the standards of both research output and educational excellence.

Pulication Top Notes : 

Internet of Smart Grid Things (IoSGT): Prototyping a Real Cloud-Edge Testbed

Authors: H. Santos, P. Eugênio, L. Marques, H. Oliveira, D. Rosário, E. Nogueira, et al.

Source: Anais do XIV Simpósio Brasileiro de Computação Ubíqua e Pervasiva

Citations: 7

Year: 2022

Predictive Fraud Detection: An Intelligent Method for Internet of Smart Grid Things Systems

Authors: L. Bastos, B. Martins, H. Santos, I. Medeiros, P. Eugênio, L. Marques, et al.

Source: Journal of Internet Services and Applications, Vol. 14(1), pp. 160–176

Citations: 5

Year: 2023

Analysis of Electrical Signals by Machine Learning for Classification of Individualized Electronics on the Internet of Smart Grid Things (IoSGT) Architecture

Authors: L. Marques, P. Eugênio, L. Bastos, H. Santos, D. Rosário, E. Nogueira, et al.

Source: Journal of Internet Services and Applications, Vol. 14(1), pp. 124–135

Citations: 2

Year: 2023

Virtualized 5G Testbed using OpenAirInterface: Tutorial and Benchmarking Tests

Authors: M. Dória, V. Sousa, A. Campos, N. Oliveira, P. Eduardo, C. Lima, J. Guilherme, et al.

Source: Journal of Internet Services and Applications, Vol. 15(1), pp. 523–535

Citations: Not yet cited

Year: 2024

Conclusion :

Paulo Eugênio da Costa Filho is a strong candidate for the Best Researcher Award, particularly for awards that value practical innovation, interdisciplinary research, and technology for public good. His profile showcases a rare blend of technicaldepth, creative application, and community impact, all rooted in scientific rigor and hands-on implementation. With cntinued development in publication strategy and international networking, he has the potential to become a leading figure in applied computing and sustainable technology solutions not just in Brazil, but globally.

Hamna Baig | Artificial Intelligence | Young Researcher Award

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Ms. Hamna Baig | Artificial Intelligence | Young Researcher Award

Research Internee | COMSATS University Islamabad, Attock Campus | Pakistan

Hamna Baig 🎓 is a passionate and award-winning Electrical Engineering graduate from COMSATS University Islamabad, Attock Campus. A gold medalist 🥇 with a CGPA of 3.66, she blends academic brilliance with innovative research in AI, IoT, and robotics 🤖. Hamna’s dynamic work spans smart environments, RF sensing, and machine learning applications 💡. She has published multiple research papers 📚, led various technical projects, and participated in prestigious conferences 🏛️. Her leadership roles and technical writing expertise further reflect her versatility 🧠. Hamna aims to revolutionize engineering solutions through creativity, technology, and social impact 🌍.

Professional profile : 

Google Scholar

Orcid 

Summary of Suitability : 

Hamna Baig exemplifies the essence of a young and emerging researcher through her exceptional academic performance, innovative contributions to AI-driven engineering, and a prolific portfolio of research publications. A gold medalist in Electrical Engineering from COMSATS University Islamabad, she has demonstrated consistent excellence in both theoretical knowledge and practical application. With multiple high-impact publications, advanced project implementations, and recognized conference presentations, she brings outstanding promise to the future of intelligent systems and healthcare engineering. Her dedication to interdisciplinary innovation, backed by hands-on experience and leadership roles, showcases her as a rising star in engineering research.

🔹 Education & Experience :

📘 Education:

  • 🎓 B.Sc. Electrical Engineering, COMSATS University Islamabad, Attock Campus (2020–2024) – CGPA: 3.66/4.00, Gold Medalist 🏅

  • 📑 Final Year Project: AI-based Environmental Control Model for Smart Homes 🏠🤖

🧑‍💼 Experience:

  • 🧪 Internee, Electrical & Computer Engineering Dept., COMSATS, under PEC GIT Program (2024–Present)

  • ⚡ Internee, Ghazi-Barotha Hydro Power Plant (GBHPP), WAPDA (2023)

  • 🖋️ Technical Writer (Electrical/Electronics), CDR Professionals (2023–Present)

Professional Development :

Hamna Baig has actively pursued professional growth through certifications, leadership, and community engagement 🌱. She completed the prestigious “Machine Learning Specialization” by DeepLearning.AI 🤖, “Generative AI for Everyone” 🧠, and several tech courses from Stanford, Yonsei, and the University of Michigan via Coursera 🎓. As a proactive learner, she enhances her skills in AI, IoT, wireless communication, and public speaking 🎤. Hamna has held key roles such as President of the Sports Society 🏸, Co-Campus Director of AICP 🧑‍🔬, and VP of COMSATS Science Society. Her drive to uplift communities and advance technology sets her apart 🌟.

Research Focus : 

Hamna’s research centers on the integration of Artificial Intelligence and Machine Learning into real-world electrical and biomedical systems 🤖🧠. She explores SDR-based gait monitoring for Parkinson’s patients 🧓, AI-controlled environmental systems for energy-efficient smart homes 🌡️, and intelligent robotic applications in agriculture 🤖🍎. Her work emphasizes non-invasive health monitoring using RF sensing 🛏️ and AI-powered automation solutions. She is deeply invested in translating complex algorithms into practical, user-centric applications that elevate health, comfort, and productivity ⚡. Her interdisciplinary approach bridges electrical engineering with innovative computing solutions 🔌📊.

Awards & Honors :

  • 🏆 Awards & Certificates:

    • 🥇 Gold Medalist, COMSATS University Islamabad (2024)

    • 🧾 Certificate of Gratitude, ICTIS Conference, UET Peshawar (2024)

    • 📜 Certificate of Gratitude, ICCSI Conference, University of Haripur (2024)

    • 🧠 ML Specialization Certificate, DeepLearning.AI – Stanford (2023)

    • 🧬 Generative AI for Everyone – DeepLearning.AI (2025)

    • 🧏‍♀️ Public Speaking Specialization – University of Michigan (2024)

    • 📶 Wireless Communications Course – Yonsei University (2024)

    • 🎓 Prime Minister’s Youth Laptop Scheme Awardee (2023)

    • 🥇 Winner – IoT Pick and Place Robotic Competition, COMSATS (2024)

    • 🧒 Student of the Year – COMSATS University, Attock (2023)

Publication Top Notes : 

  • • Title: Intelligent Frozen Gait Monitoring using Software Defined Radio Frequency Sensing
    Citation: Electronics, 14(8), 1603, 2025
    Authors: Khan, M. B., Baig, H., Hayat, R., Tanoli, S. A. K., Rehman, M., Thakor, V. A., & Haider, D.
    Year: 2025

  • • Title: Machine Learning-Based Estimation of End Effector Position in Three-Dimension Robotic Workspace
    Citation: IJIST Journal (Impact Factor: 4.312)
    Authors: Baig, H., Ahmed, E., Jadoon, I., & Pakistan, K. C. A.
    Year: 2024

  • • Title: A Robotic Approach for Fruit Harvesting with Machine Learning-Based Joint Angles Prediction
    Citation: Submitted to ICCSI – International Conference on Computational Sciences and Innovations
    Authors: Baig, H., Baig, A.A, Ahmed, E., Jadoon, I., & Pakistan
    Year: 2024

  • • Title: Artificial Intelligence Based Adaptive Fan Control in Office Settings for Energy Efficiency
    Citation: Submitted to ICCIS – Proceedings to Springer Journal
    Authors: Baig, H.
    Year: 2024

  • • Title: A Robotic Arm Based Intelligent Biopsy System
    Citation: Submitted to ICCIS – Kohat University, Springer Proceedings
    Authors: Baig, H.
    Year: 2024

  • • Title: Design of an Intelligent Wireless Channel State Information Sensing System to Prevent Bedsores
    Citation: IEEE Sensors Journal (Under Review)
    Authors: Baig, H.
    Year: 2024

  • • Title: Enhancing Home Comfort and Energy Consumption with an Artificial Intelligence-Based Environmental Sensing Control Model
    Citation: PeerJ (Computer Science) (Under Review)
    Authors: Baig, H.
    Year: 2024

  • • Title: Breathing Techniques Redefined: The Pros and Cons of Traditional Methods and the Promise of SDRF Sensing
    Citation: Elsevier – Digital Communications and Networks (Under Review)
    Authors: Baig, H.
    Year: 2024

Conclusion : 

  • Hamna Baig not only meets but exceeds the expectations of a Young Researcher Award recipient. Her innovative mindset, research productivity, and real-world problem-solving approach make her an ideal candidate. Her work is not just academically sound but socially impactful—especially in the domains of healthcare and automation. She is a beacon of excellence and innovation, representing the future of engineering research. 🌟

 

Prof. Dr. Dongxing Song | Machine Learning | Best Researcher Award-3904

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Prof. Dr. Dongxing Song | Machine Learning | Best Researcher Award

Prof. Dr. Dongxing Song, Zhengzhou University, China

Prof. Dr. Dongxing Song is an innovative researcher in power engineering and thermophysics, currently serving as a Research Fellow at Zhengzhou University’s School of Mechanics and Safety Engineering. He earned his doctoral degree from Tsinghua University and previously studied at Xi’an Jiaotong University and Central South University. His expertise lies in nanofluid dynamics, ionic thermoelectric conversion, and energy system optimization. Dr. Song’s research integrates machine learning with thermodynamics, pushing boundaries in sustainable energy technologies. His work has been published in top-tier journals such as Joule and Cell Reports Physical Science, gaining recognition for both originality and technical depth. Driven by scientific rigor and curiosity, Dr. Song continues to shape future solutions for clean energy and advanced material systems. ⚛️🔬🌱

🌍 Professional Profile 

Orcid

Google Scholar

🏆 Suitability for Best Researcher Award 

Prof. Dr. Dongxing Song is a standout candidate for the Best Researcher Award due to his cutting-edge work in ionic thermoelectric energy conversion and nanoscale heat transfer. His publications in high-impact journals, including Joule and Cell Reports Physical Science, demonstrate his role in shaping the future of clean and efficient energy generation. Dr. Song has independently led national-level research projects supported by the NSFC and China Postdoctoral Science Foundation, focusing on ion-electron coupling mechanisms and dynamic heat-mass transport. His interdisciplinary approach—blending thermophysics, machine learning, and materials science—makes him a trailblazer in green energy innovation. His research not only advances scientific understanding but also offers scalable solutions for low-grade waste heat recovery. 🔋🏅🌍

🎓 Education

Prof. Dr. Dongxing Song holds a robust academic background in power engineering and thermophysics. He completed his Ph.D. at Tsinghua University (2018–2022) under Prof. Weigang Ma, following his Master’s studies at Xi’an Jiaotong University (2015–2018) under Prof. Dengwei Jing. His foundational education in Thermal Energy and Power Engineering was completed at Central South University (2011–2015), where he was mentored by Dengwei Jing and Jianzhi Zhang. Throughout his academic journey, Dr. Song developed deep expertise in energy conversion, ionic transport, and thermodynamic modeling. His cross-institutional training at China’s most prestigious engineering schools laid the groundwork for his innovative and interdisciplinary research in the clean energy domain. 🎓📘⚙️

💼 Experience

Since February 2022, Dr. Dongxing Song has served as a Research Fellow at the School of Mechanics and Safety Engineering, Zhengzhou University, contributing significantly to ionic thermoelectric research. He previously pursued advanced research at Tsinghua University, one of China’s top engineering institutions, from 2018 to 2022. His earlier academic appointments include graduate research at Xi’an Jiaotong University and Central South University, where he gained hands-on experience in power engineering, energy optimization, and thermophysical modeling. In every role, Dr. Song has demonstrated scientific leadership, managing national-level projects and publishing influential research. His experience reflects a well-rounded career rooted in high-impact research and technological innovation in sustainable energy. 🧑‍🔬🔋📈

🏅 Awards and Honors

Prof. Dr. Dongxing Song has received prestigious grants and recognition from leading national institutions. He is the Principal Investigator of a National Natural Science Foundation of China (NSFC) Original Exploration Program Project, as well as multiple China Postdoctoral Science Foundation awards, including the Innovative Talents Grant (BX20220275). His work on ion thermoelectric conversion received a high recommendation from Joule Preview, marking him as a rising star in energy systems innovation. Dr. Song’s publications in top-impact journals and his ability to secure competitive funding reflect his academic excellence and research potential. These accolades highlight his position as a thought leader in the next generation of thermophysical science and energy innovation. 🥇🏛️📚

🔬 Research Focus

Dr. Dongxing Song’s research centers on the optimization of power generation systems for low-grade waste heat recovery, specifically using ion thermoelectric conversion and salt gradient power. He investigates the fundamental coupling between heat and ion transport and has derived a new expression for the ionic Seebeck coefficient, setting the stage for thermoelectric optimization. His studies also integrate nanofluidic heat transfer, solid-state ion battery transport, and machine learning to enhance the performance of sustainable energy devices. His broader focus includes nanoscale heat and mass transfer, where he explores transport mechanisms across interfaces using simulation and experimental validation. Dr. Song’s pioneering models are helping redefine energy recovery systems with enhanced efficiency and low environmental impact. 🔬♻️🧪

📊 Publication Top Notes

  • Design of Microchannel Heat Sink with Wavy Channel and Its Time-Efficient Optimization with Combined RSM and FVM Methods

    • Citations: 209

    • Year: 2016

  • Optimization of a Circular-Wavy Cavity Filled by Nanofluid under Natural Convection Heat Transfer

    • Citations: 194

    • Year: 2016

  • Optimization of a Lid-Driven T-Shaped Porous Cavity to Improve the Nanofluids Mixed Convection Heat Transfer

    • Citations: 138

    • Year: 2017

  • Prediction of Hydrodynamic and Optical Properties of TiO₂/Water Suspension Considering Particle Size Distribution

    • Citations: 87

    • Year: 2016

  • A Nitrogenous Pre-Intercalation Strategy for the Synthesis of Nitrogen-Doped Ti₃C₂Tₓ MXene with Enhanced Electrochemical Capacitance

    • Citations: 71

    • Year: 2021

 

Dr. XInbo MA | Machine Learning | Best Researcher Award

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Dr. XInbo MA | Machine Learning | Best Researcher Award

Dr. XInbo MA, Northeastern University, China

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Ma Xinbo is a prominent figure in the field of geotechnical engineering, currently serving as an Associate Professor at the College of Resources and Civil Engineering, Northeastern University, Shenyang, China. His scholarly pursuits focus on the intelligent detection of internal fractures in mine rock masses, utilizing advanced imaging techniques to enhance the safety and efficiency of mining operations.

Profile:

Scopus​

Education:

Professor Ma earned his Ph.D. in Geotechnical Engineering from Northeastern University, Shenyang, China, in 2010. His doctoral research laid the foundation for his ongoing commitment to advancing mining safety through technological innovation.​

Experience:

Throughout his career, Professor Ma has held several academic and research positions. Prior to his current role, he served as a Lecturer and then as an Associate Professor at the same institution. His professional journey reflects a steadfast dedication to both teaching and research in geotechnical engineering.​

Research Interests:

Professor Ma’s research interests are centered around the application of intelligent detection methods in mining engineering. A notable area of his work includes the development of techniques for identifying internal fractures in mine rock masses using borehole camera images. This research aims to improve the understanding of rock mass integrity, which is crucial for the safety and sustainability of mining operations.​

Publications:

Professor Ma Xinbo has contributed to several scholarly publications, including:​

  1. “Abcb1 is Involved in the Efflux of Trivalent Inorganic Arsenic from Brain Microvascular Endothelial Cells” by Man Lv, Ziqiao Guan, Jia Cui, Xinbo Ma, Kunyu Zhang, Xinhua Shao, Meichen Zhang, Yanhui Gao, Yanmei Yang, Xiaona Liu. This study explores the role of Abcb1 in mediating arsenic efflux in brain microvascular endothelial cells. Published in 2024. ​
  2. “Liberal Arts in China’s Modern Universities: Lessons from the Great Catholic Educator and Statesman, Ma Xiangbo” by You Guo Jiang. This article discusses the contributions of Ma Xiangbo to liberal arts education in modern China. Published in Frontiers of Education in China, Volume 7, Issue 3, in 2012. ​
  3. “Catholic Intellectuals in Modern China and Their Bible Translation: Li Wenyu and Ma Xiangbo” by Xiaochun Hong. This paper examines the roles of Li Wenyu and Ma Xiangbo in Bible translation efforts in modern China. Published in the Journal of the Royal Asiatic Society, Volume 33, Issue 2, in 2023.

Awards and Recognitions:

Professor Ma’s excellence in research and academia has been acknowledged through various awards and honors. In 2016, he was honored as an Outstanding Graduate of Dalian Maritime University, reflecting his early commitment to academic excellence. He also received the National Scholarship, awarded to the top 0.2% of students by China’s Ministry of Education, in both 2013 and 2016. These accolades highlight his dedication to his field and his institution.​

Conclusion:

Professor Ma Xinbo’s academic journey and research endeavors underscore his pivotal role in advancing geotechnical engineering, particularly in the realm of mining safety. His innovative approaches to fracture detection and his commitment to scholarly excellence make him a valuable asset to the academic community and a strong candidate for the “Best Researcher Award.”

Dr. Ryszard Ćwiertniak | Artificial Intelligence | Best Researcher Award

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Dr. Ryszard Ćwiertniak | Artificial Intelligence | Best Researcher Award

Dr. Ryszard Ćwiertniak, Krakow University of Economics, Poland

Dr. Ryszard Ćwiertniak is an accomplished expert in project management, specializing in agile methodologies, Design Thinking, and AI-driven innovation. He holds a PhD in Management and Quality Sciences from the University of Economics in Krakow and has a strong academic and professional background in administration, management, and electrical engineering. With extensive experience in research and teaching, he has contributed to the fields of digital transformation, e-learning, and Industry 4.0. As an IBM Design Thinking mentor and Early Warning Europe ambassador, he helps businesses implement cutting-edge solutions. His work spans academia, consulting, and applied research in AI and business process optimization.

🌍 Professional Profile:

Orcid

Google Scholar

🏆 Suitability for Best Researcher Award 

Dr. Ryszard Ćwiertniak’s pioneering research in AI-driven project management, digital transformation, and innovation management makes him an outstanding candidate for the Best Researcher Award. His involvement in Erasmus+ projects, contributions to Industry 4.0, and mentorship in agile methodologies showcase his impact on academia and industry. His expertise in AI-based decision-making, personalized education, and digital business models has transformed organizational processes. With numerous peer-reviewed publications, a book, and a grant-winning project, his research advances the future of smart business ecosystems. His leadership in AI-powered business solutions and educational innovations solidifies his reputation as a top researcher in the field.

🎓 Education 

Dr. Ryszard Ćwiertniak earned his PhD in Management and Quality Sciences from the University of Economics in Krakow (2019), focusing on innovation management. He also holds a Master’s degree in Administration and Management from the University of Warsaw (1994). In addition, he has a background in electrical engineering, equipping him with a multidisciplinary approach to research. His academic journey reflects a deep commitment to combining management principles with technology, particularly in AI applications, e-learning, and agile business strategies. His education has laid the foundation for his expertise in digital transformation, business innovation, and advanced project management methodologies.

💼 Professional Experience 

Dr. Ćwiertniak currently serves as an academic teacher at Krakow University of Economics, specializing in technology and product ecology. Previously, he was the Rector’s Representative for Quality of Education and E-learning at the College of Economics and Computer Science (2020–2024). His role in the Early Warning Europe initiative highlights his expertise in digital business transformation. He also contributes to the Erasmus+ program, working on AI-powered educational solutions. As an IBM Design Thinking mentor, he facilitates agile project implementation. His professional engagements bridge academia and industry, driving innovation, AI adoption, and digital business strategies in various sectors.

🏅 Awards and Honors 

🔹 Early Warning Europe Ambassador (2021–Present) – Recognized for supporting digital business transformation.
🔹 Erasmus+ Research Grant Recipient – Contributed to AI-driven education models.
🔹 Ministerial Research Grant Winner (2021) – Awarded funding for advancing e-learning and digital education techniques.
🔹 IBM Design Thinking Mentor – Certified expert in guiding agile and innovative project execution.
🔹 Industry 4.0 & AI Innovation Contributor – Acknowledged for pioneering work in integrating AI with project management and digital marketing.
🔹 Invited Researcher at THWS Business School (2024) – Recognized for leadership in AI-based digital transformation.

His contributions to AI, project management, and education technology have earned him national and international acclaim.

🔬 Research Focus

Dr. Ćwiertniak’s research spans AI-driven project management, innovation strategies, digital transformation, and e-learning technologies. He explores Industry 4.0 applications, AI-based decision-making, and agile methodologies to optimize business processes. His focus on digital business models, social media analytics, and e-commerce strategies has redefined marketing and management practices. Through Design Thinking and AI integration, he enhances project execution efficiency. His research also covers personalized education using AI, ensuring smarter, data-driven learning environments. As an expert in AI-powered business solutions, he contributes to making organizations more adaptable and efficient in an era of rapid technological advancements.

📊 Publication Top Notes:

  1. Rola potencjału innowacyjnego w modelach biznesowych nowoczesnych organizacji – próba oceny

    • Citations: 11
    • Year: 2015

  2. Zarządzanie portfelem projektów w organizacji: Koncepcje i kierunki badań

    • Citations: 4
    • Year: 2018

  1. Addressing students’ perceived value with the virtual university concept

    • Citations: 3
    • Year: 2022

  2. Kształtowanie portfela projektów w zarządzaniu innowacjami

    • Citations: 2
    • Year: 2018

  1. The concept of project evaluation in the implementation of innovation

    • Citations: 1
    • Year: 2020