Petr Znachor | Limnology | Best Researcher Award

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Assoc. Prof. Dr. Petr Znachor | Limnology | Best Researcher Award

Senior Scientist | Biology Centre Of The Czech Academy Of Sciences, Institute of Hydrobiology | Czech Republic

Assoc. Prof. Dr. Petr Znachor is a distinguished limnologist and hydrobiologist whose research focuses on phytoplankton ecology, reservoir limnology, and the biogeochemical cycling of methane in aquatic systems. His work integrates field studies, long-term ecological data, and advanced time-series analyses to understand how climate change, weather extremes, and anthropogenic pressures influence the functioning and water quality of lentic ecosystems. He has led and contributed to numerous national and international research projects addressing the ecological dynamics of plankton communities and the development of biomanipulation techniques to improve water quality in reservoirs. His expertise spans a wide range of topics, including diatom ecophysiology, microbial interactions, fluorescence-based methods, and the spatial-temporal variability of phytoplankton. As an accomplished researcher and academic, he has published extensively in high-impact international journals and has made significant contributions to the advancement of freshwater ecology. His scientific leadership is reflected in his roles within the Institute of Hydrobiology of the Biology Centre of the Czech Academy of Sciences and in professional societies such as the Czech Limnological Society and the Czech Long-Term Ecological Research network. With a strong interdisciplinary approach, Dr. Znachor’s research continues to enhance understanding of freshwater ecosystem responses to environmental change and to inform sustainable water management strategies.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

Znachor, P., Kosour, D., Rederer, L., Koza, V., Kolář, V., & Nedoma, J. (2025). Tracking reservoir warming in a changing climate: A 31-year study from Czechia. Environmental Science and Ecotechnology, Article 100631.

Mukherjee, I., Grujčić, V., Salcher, M. M., Znachor, P., Seďa, J., Devetter, M., Rychtecký, P., Šimek, K., & Shabarova, T. (2024). Depth-dependent dynamics of protist communities as an integral part of spring succession in a freshwater reservoir. bioRxiv.

Boukheloua, R., Mukherjee, I., Park, H., Šimek, K., Kasalický, V., Ngochera, M., Grossart, H.-P., Picazo-Mozo, A., Camacho, A., Cabello-Yeves, P. J., Znachor, P. (2024). Global freshwater distribution of Telonemia protists. ISME Journal.

Mukherjee, I., Grujčić, V., Salcher, M. M., Znachor, P., Seďa, J., Devetter, M., Rychtecký, P., Šimek, K., & Shabarova, T. (2024). Integrating depth-dependent protist dynamics and microbial interactions in spring succession of a freshwater reservoir. Environmental Microbiome, 19(1), Article 574.

Vieira, H. H., Bulzu, P.-A., Kasalický, V., Haber, M., Znachor, P., Piwosz, K., & Ghai, R. (2024). Isolation of a widespread giant virus implicated in cryptophyte bloom collapse. ISME Journal.

Manjunath BR | Machine Learning | Best Researcher Award

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Prof. Dr. Manjunath BR | Machine Learning | Best Researcher Award

Professor | Tecnologico De Monterrey | Mexico

Prof. Dr. Manjunath BR is an accomplished academic leader and finance professional specializing in business analytics, financial modeling, econometrics, fintech, and artificial intelligence applications in finance. With extensive experience across academia and industry, he has contributed significantly to advancing data-driven financial education and research. His expertise spans financial analytics, investment management, corporate restructuring, and data visualization using advanced tools such as EViews, R, Python, Tableau, and Power BI. He has published extensively in ABDC, Scopus, UGC, and peer-reviewed journals, focusing on the intersection of finance, data science, and technology. As a researcher and educator, he integrates predictive analytics and machine learning into financial decision-making, contributing to the understanding of fintech adoption, banking innovations, and risk management. His academic leadership includes curriculum design, faculty development, and corporate collaborations to enhance experiential learning. He has served as a resource person for numerous international workshops and training programs on financial analytics, econometrics, and data visualization, empowering professionals and students with analytical and quantitative skills. Dr. Manjunath has authored and edited several books with leading global publishers, covering transformative areas such as AI in management education, blockchain economics, sustainable investment, and Quality 5.0 paradigms. He has also secured a patent for the application of AI in optimizing HR data management and authored a textbook on machine and deep learning. His professional journey embodies innovation, interdisciplinary scholarship, and a commitment to integrating technology with finance to foster global academic and industry excellence.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

Raju, J. K., Manjunath, B. R., & Rehaman, M. (2018). An empirical study on the effect of gross domestic product on inflation: Evidence from Indian data. Academy of Accounting and Financial Studies Journal, 22(6), 1–11.

Raju, J. K., Manjunath, B. R., & Dhakal, M. H. (2015). Impact and challenges of merger and acquisition in Nepalese banking and financial institutions. Journal of Exclusive Management Science, 4(8), 25–33.

Raju, J. K., Manjunath, B. R., & G. M. M. N. (2015). Performance evaluation of Indian equity mutual fund schemes. Journal of Business Management & Social Sciences Research (JBM&SSR).

Manjunath, B. R., & Raju, J. K. (2020). Short-run performance evaluation of under-priced Indian IPOs. Law and Financial Markets Review.

Chaitra, R., Manjunath, B. R., & Rehaman, M. (2019). An analysis of pre and post-merger of Indian banks: An event analysis approach. International Journal for Research in Engineering Application & Management, 4.

Suhas S | Networking | Best Researcher Award

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Dr. Suhas S | Networking | Best Researcher Award

Assistant Professor | JSS Science and Technology University, Mysore | India

Dr. Suhas S is an accomplished academic and researcher in the field of Computer Science and Engineering, with strong expertise in cloud computing and cybersecurity. His research focuses on developing secure, scalable, and efficient cloud-based systems that address key challenges in data protection, network resilience, and distributed computing environments. With over fifteen years of combined academic and research experience, he has contributed to the advancement of computational technologies through publications in international and national journals, as well as conference presentations. His work emphasizes the intersection of network engineering, cybersecurity frameworks, and intelligent computing architectures aimed at enhancing data privacy and system integrity in cloud infrastructures. He has also been actively involved in guiding students and participating in institutional research initiatives, fostering innovation and technical proficiency among emerging engineers. As a member of IEEE, Mysore Section, he has delivered numerous talks on emerging technologies, including image processing, cloud computing, and cybersecurity, demonstrating his commitment to academic dissemination and professional engagement. His interdisciplinary approach integrates theoretical principles with applied research, promoting advancements in secure cloud environments and next-generation computing systems. Through his scholarly contributions and teaching excellence, Dr. Suhas continues to play a significant role in shaping future developments in computer science education and research, particularly in domains involving secure computing and advanced network technologies.

Profile: Google Scholar

Featured Publications

Suhas, S., & Venugopal, C. R. (2017). MRI image preprocessing and noise removal technique using linear and nonlinear filters. In Proceedings of the 2017 International Conference on Electrical, Electronics, Communication, Computer, and Optimization Techniques (ICEECCOT) (pp. 81–86). IEEE.

Suhas, S., & Venugopal, C. R. (2018). An efficient MRI noise removal technique using linear and nonlinear filters. International Journal of Computer Applications, 179(15), 17–20.

Chaturvedi, A., Suhas, S., Shivani, J. L. D., Raja, C., Soni, U., & Natrayan, L. (2025). Enhancing IoT network security: A double decker convolutional neural network with Brown-Bear optimization for intrusion detection. In Proceedings of the 2025 International Conference on Inventive Computation Technologies (ICICT). IEEE.

Suhas, P. K., & Lokesh, S. (2024). The evolution of forensic medicine in the digital era: Enhancing evidence collection and analysis. International Journal of Medical Toxicology & Legal Medicine, 27(4), 357–363.

Suhas, S. D. C. R. V. (2021). Feature extraction and classification of MRI using hybrid RBF kernel and SVM. International Journal of Scientific Research in Computer Science, Engineering and Information Technology.

Rabia Benaddi | Environmental Science | Outstanding Contributions in Academia Award

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Dr. Rabia Benaddi | Environmental Science | Outstanding Contributions in Academia Award

Agence Du Bassin Hydraulique De Tensift | Morocco

Dr. Rabia Benaddi is a Moroccan researcher specializing in environmental chemistry, water quality management, and material sciences. His research focuses on the synthesis and characterization of phosphate-based materials and their application in the adsorption and removal of phenolic and organic pollutants from wastewater, contributing significantly to sustainable water treatment technologies. He has co-authored multiple peer-reviewed publications in international journals such as the Journal of Hydrology: Regional Studies, Journal of African Earth Sciences, and Ecological Engineering & Environmental Technology. His work also encompasses the assessment of wastewater treatment systems, natural lagoon performance, groundwater contamination, and the environmental impacts of industrial effluents in arid and semi-arid regions. Professionally, he has extensive experience in water quality monitoring, environmental impact assessment, and management of wastewater reuse projects. He has actively contributed to research collaborations, student supervision, and capacity-building initiatives in water resource management, climate change adaptation, and environmental sustainability. Through numerous conference presentations and international training programs, he has demonstrated a strong commitment to advancing scientific understanding and practical solutions for sustainable water and environmental systems.

Proifles: Scopus | Orcid

Featured Publications

Benaddi, R., Osmane, A., Zidan, K., El Harfi, K., & Ouazzani, N. (2023). A review on processes for olive mill wastewater treatment. Ecological Engineering & Environmental Technology, 24(7).

Benaddi, R., Osmane, A., Zidan, K., El Harfi, K., & Ouazzani, N. (2023). A review on the adsorption of phenol derivatives from wastewater. Ecological Engineering & Environmental Technology, 24(6).

Benaddi, R., Aziz, F., El Harfi, K., & Ouazzani, N. (2022). Column adsorption studies of phenolic compounds on nanoparticles synthesized from Moroccan phosphate rock. In Advances in Science, Technology and Innovation (pp. 181–192). Springer.

Benaddi, R., Ferkan, Y., Bouriqi, A., & Ouazzani, N. (2022). Impact of landfill leachate on groundwater quality – A comparison between three different landfills in Morocco. Journal of Ecological Engineering, 23(5), 213–223.

Benaddi, R., Aziz, F., El Harfi, K., & Ouazzani, N. (2021). Adsorption and desorption studies of phenolic compounds on hydroxyapatite–sodium alginate composite. Desalination and Water Treatment, 227, 1–11.

Fan Shi | Electrochemical Sensors | Best Researcher Award

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Prof. Fan Shi | Electrochemical Sensors | Best Researcher Award

Baoshan University | China

Prof. Fan Shi is a chemist specializing in nanomaterials, electrochemical sensors, biochips, and wearable sensor technologies. His research primarily focuses on the design, synthesis, and application of carbon-based and two-dimensional nanocomposites for flexible and intelligent biosensing systems. Through his work, he has contributed significantly to advancing the understanding and development of high-performance electrochemical biosensors, particularly for the detection of biomolecules and environmental analytes. Prof. Shi has authored numerous publications in high-impact journals such as Biosensors and Bioelectronics, Materials Science and Engineering C, and Bioelectrochemistry, with a cumulative impact factor exceeding. His research integrates nanomaterial synthesis, surface functionalization, and electrochemical techniques to construct innovative sensing platforms, including wireless and wearable devices. He has also co-developed patented methods for synthesizing carbonized polymer dots integrated with black phosphorene for biosensing applications. Shi’s scientific achievements have been recognized through multiple awards for excellence in research, including provincial and national honors. Beyond his academic work, he has professional experience in bioelectronics and technology development sectors, where he contributed to the advancement of sensor applications and international collaboration in analytical testing. His interdisciplinary expertise bridges chemistry, materials science, and bioengineering, driving forward innovations in flexible and miniaturized sensing technologies for health monitoring and environmental detection.

Profile: Scopus

Featured Publications

Shi, F., & Sun, W.* (2025). Waste-to-resource: Utilization of carbon dots derived from proliferating Sargassum aquifolium (Turner) C. Agardh for fluorescent detection of levofloxacin. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy.

Shi, F., & Sun, W.* (2025). Horseradish peroxidase biosensor based on a MWCNTs/black phosphorene nanocomposite for sensitive electrochemical detection of trichloroacetic acid and nitrite. International Journal of Electrochemical Science.

Shi, F., & Sun, W.* (2025). Garnering sensitivity: A horseradish peroxidase and MoS2@black phosphorene-based electrochemical biosensor for glyphosate detection. Bioelectrochemistry.

Shi, F., & Sun, W.* (2025). O–O bridge adsorption catalysis of different metal single atoms toward high-sensitive detection of H₂O₂. Chemical Engineering Journal.

Shi, F., & Sun, W.* (2015). Application of graphene–copper sulfide nanocomposite modified electrode for electrochemistry and electrocatalysis of hemoglobin. Biosensors and Bioelectronics, 64, 131–137.

Moyu Chen | Agricultural Economics | Best Researcher Award

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Dr. Moyu Chen | Agricultural Economics | Best Researcher Award

Peking University | China

Dr. Moyu Chen is a Post-doctoral Research Fellow at the College of Urban and Environmental Sciences, Peking University, specializing in agricultural economics and rural development. His research focuses on agricultural technological progress, productivity enhancement, science and technology policies, and the broader dynamics of rural transformation and sustainable agricultural development. Dr. Chen’s work integrates empirical economic analysis with policy-oriented research, emphasizing the role of innovation and institutional reform in advancing agricultural performance and food security. He has co-authored publications in high-impact journals such as Economic Modelling, Asia & the Pacific Policy Studies, Economic Analysis and Policy, and China Agricultural Economic Review. His research contributions extend to international collaborations, including projects supported by the Australian National University, the Australian Centre for International Agricultural Research, and the National Natural Science Foundation of China. In addition to his scholarly work, Dr. Chen has contributed to multiple consulting reports for policy institutions, focusing on grain yield improvement, rural transformation, and agricultural productivity. He actively participates in academic conferences such as AARES and ASAE, where he presents comparative analyses of rural transformation and agricultural labor productivity across developing economies. As a member and Treasurer of the AARES East Asian Branch, Dr. Chen contributes to advancing dialogue and research exchange within the agricultural economics community across the Asia-Pacific region.

Profile: Scopus

Featured Publications

Chen, M., Jia, S., & Sheng, Y. (2025). Curse or cure: China’s growing food demand and its impact on African agricultural exports and value-added. Economic Modelling, forthcoming.

Chen, M., Findlay, C., Sheng, Y., Chen, C., & Huang, J. (2026). Cultivating success: The role of institutions, policies and investments in driving rural transformation in Australia. Asia & the Pacific Policy Studies, 13(1), e70056.

Huang, K., Cheng, B., Chen, M., & Sheng, Y. (2022). Assessing impact of the COVID-19 pandemic on China’s TFP growth: Evidence from region-level data in 2020. Economic Analysis and Policy, 75, 362–377.

Qing, Y., Chen, M., Sheng, Y., & Huang, J. (2019). Mechanization services, farm productivity and institutional innovation in China. China Agricultural Economic Review, 11(3), 536–554.

Chen, M., Sheng, Y., & Findlay, C. (2025, February). Contextual drivers of agricultural labor productivity across stages of rural transformation: A cross-country comparison study. Paper presented at the 69th Annual Conference of the Australian Agricultural and Resource Economics Society (AARES).

Mostafa Gamal | Artificial Intelligence | Best Researcher Award

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Mr. Mostafa Gamal | Artificial Intelligence | Best Researcher Award

Egyptian Russian University | Egypt

Mr. Mostafa Gamal, is a dedicated researcher and academic specializing in artificial intelligence, machine learning, and natural language processing, with a particular focus on text summarization and semantic graph-based models. His research explores the integration of deep learning, swarm intelligence, and optimization algorithms to enhance automated summarization and intelligent decision-making systems. He has contributed to several high-impact journals, including IEEE Access, Results in Engineering, Discover Cities, and the International Journal of Data Science and Analytics, covering areas such as transformer architectures, reinforcement learning, and graph neural networks. Mr. Gamal’s work advances the field of AI through the development of novel, explainable, and efficient models for NLP applications and autonomous systems. Beyond research, he is actively involved in academic teaching and professional training, fostering AI literacy through programs with the Egyptian Russian University, Huawei Academy, and the Digital Egypt Cubs Initiative. His technical expertise spans TensorFlow, PyTorch, and Keras, alongside proficiency in Python and data analytics frameworks. With a strong foundation in applied AI, he bridges theoretical research with practical implementation, contributing to the development of intelligent systems that address real-world challenges. His scholarly and instructional activities reflect a commitment to advancing artificial intelligence education and applied innovation in computational sciences.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

Abdul Salam, M., Gamal, M., Hamed, H. F. A., & Sweidan, S. (2025, December). GRAYSUM: Gray Wolf optimized multi-level semantic graph summarization. Results in Engineering, (2025), 107275.

Abdul Salam, M., Gamal, M., Hamed, H. F. A., & Sweidan, S. (2025, October). Abstractive text summarization using deep learning models: A survey. International Journal of Data Science and Analytics.

Gamal, M., & Ibrahim, O. A. (2025, October 24). Graph neural networks for real-time optimization of autonomous urban transit systems. Discover Cities.

Gamal, M. M., Abdul Salam, M., Sweidan, S., & Hamed, H. F. A. (2025, May 1). ACOSUM: Ant colony optimized multi-level semantic graph summarization. International Journal of Applied Intelligent Computing and Informatics.

Abdul Salam, M., Aldawsari, M., Gamal, M., Hamed, H. F. A., & Sweidan, S. (2024). Improving Arabic text summarization using advanced pre-trained models. Journal of Southwest Jiaotong University, 59(3), Article 5.

Jaber Jahanbin Sardroodi | Computational Chemistry | Best Researcher Award

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Prof. Dr. Jaber Jahanbin Sardroodi | Computational Chemistry | Best Researcher Award

Azarbaijan Shahid Madani University | Iran

Prof. Dr. Jaber Jahanbin Sardroodi is a distinguished scholar in theoretical and computational physical chemistry, serving as Professor of Physical Chemistry at Azarbaijan Shahid Madani University. His research spans a wide range of topics, integrating molecular simulation, thermodynamics, and quantum chemistry to address complex chemical and biological systems. He leads the Molecular Simulation Lab and the Molecular Science and Engineering Research Group, where his work focuses on molecular dynamics simulations, free energy calculations, solvation processes, and drug–protein interactions. Prof. Sardroodi’s studies also explore deep eutectic solvents, nanomaterials, and molecular mechanisms of pharmaceutical interactions in aqueous and membrane environments. In addition, his research extends to quantum mechanics of many-body systems, density functional theory (DFT), quantum thermodynamics, and open quantum systems, contributing to the understanding of quantum information and thermal engines. His group employs advanced computational tools, including Python, Fortran, and C++, and increasingly integrates artificial intelligence and deep learning techniques into physical chemistry problem-solving. Prof. Sardroodi has authored numerous peer-reviewed publications in high-impact journals such as Scientific Reports, Chemical Engineering Science, and Journal of Molecular Modeling. His research contributes significantly to the advancement of molecular modeling, smart drug delivery systems, and energy materials, reflecting a blend of rigorous theoretical insight and computational innovation in modern chemical science.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

Barani Pour, S., Jabbarvand Behrooz, N., Jahanbin Sardroodi, J., & Avestan, M. S. (2025). Potential use of deep eutectic solvents based on sugar as green separation media for the acidic gases capture process from the gas mixtures: Molecular dynamics simulation and COSMO-RS insights. Journal of Molecular Modeling.

Jahanbakhsh-Bonab, P., Pazuki, G., Jahanbin Sardroodi, J., & Dehnavi, S. M. (2023). Assessment of the properties of natural-based chiral deep eutectic solvents for chiral drug separation: Insights from molecular dynamics simulation. Physical Chemistry Chemical Physics.

Barani Pour, S., Jahanbin Sardroodi, J., Ebrahimzadeh, A. R., & Pazuki, G. (2023). Investigation of the effect of water addition on intermolecular interactions of fatty acids-based deep eutectic solvents by molecular dynamics simulations. Scientific Reports.

Heidari, S., Esrafili, M. D., & Jahanbin Sardroodi, J. (2023). Li, Na and K storage capacity of a novel 2D graphitic carbon-nitride membrane, C₉N₄: A computational approach. Chemical Physics Letters.

Mousavian, P., Esrafili, M. D., & Jahanbin Sardroodi, J. (2023). Outstanding performance of transition-metal decorated BC₃ nanotubes for high capacity CH₄ storage. Applied Surface Science.

Nuria Bermejo | Trombosis | Breakthrough Research Award

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Dr. Nuria Bermejo | Trombosis | Breakthrough Research Award

Hospital San Pedro de Alcantara | Spain

Dr. Nuria Bermejo Vega is a highly experienced medical specialist in Hematology with extensive expertise in thrombosis, hemostasis, and platelet disorders. As a Facultativo Especialista de Área at the Servicio Extremeño de Salud, her research and clinical work focus on bleeding and thrombotic disorders, hemophilia, and the molecular mechanisms underlying hematological diseases. She has actively contributed to numerous national and international research projects and clinical trials in collaboration with major scientific and pharmaceutical institutions such as the International Society on Thrombosis and Haemostasis (ISTH), Fundación Fundesalud, Novo Nordisk, Pfizer, Bayer, and Grifols. Her participation in multicenter studies has advanced knowledge in platelet physiology, calcium signaling in cancer cells, and genetic-molecular diagnosis of coagulation disorders. Dr. Bermejo’s research has played a crucial role in standardizing diagnostic tools, evaluating new therapeutic approaches, and improving patient care for rare hematological diseases. She has also been involved in projects supported by the Spanish Ministry of Science and Innovation and the Ministry of Economy and Competitiveness, addressing molecular pathways and pharmacological interventions in platelet and vascular dysfunctions. Her scientific dedication and clinical insight contribute significantly to the advancement of hematology and translational research in Spain.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

González-López, T. J., Bermejo-Vega, N., Cardesa-Cabrera, R., Martínez-Robles, V., Aguilar-Monserrate, G., Pérez-Segura, G., Domingo, A., Luis-Navarro, J., Lakhwani, S., Acedo, N., et al. (2024). Fostamatinib effectiveness and safety for immune thrombocytopenia in clinical practice. Blood.

Bermejo, N., Casado-Cabanillas, V., González-Valero, J., Higuero, V., & Espacio, F. (2023). PB2665: Thrombotic profile of a serie of 14 patients carrying 67Arg>Stop polymorphism in the SERPINE A10 (protease-dependent protein Z inhibitor) gene. HemaSphere, 7(Supplement 1).

Alessi, M. C., Coxon, C., Ibrahim-Kosta, M., Bacci, M., Voisin, S., Rivera, J., Greinacher, A., Raster, J., Pulcinelli, F., Devreese, K. M. J., et al. (2023). Multicenter evaluation of light transmission platelet aggregation reagents: Communication from the ISTH SSC Subcommittee on Platelet Physiology. Journal of Thrombosis and Haemostasis (JTH).

Lozano, M. L., Mingot-Castellano, M. E., Perera, M. M., Jarque, I., Campos-Álvarez, R. M., González-López, T. J., Carreño-Tarragona, G., Bermejo, N., López-Fernández, M. F., & Vicente, V. (2021). Author correction: Deciphering predictive factors for choice of thrombopoietin receptor agonist, treatment-free responses, and thrombotic events in immune thrombocytopenia. Scientific Reports, 11(1).

Palma-Barqueros, V., Crescente, M., de la Morena, M. E., Chan, M. V., Almarza, E., Revilla, N., Bohdan, N., Miñano, A., Padilla, J., Allan, H. E., et al. (2021). A novel genetic variant in PTGS1 affects N-glycosylation of cyclooxygenase-1 causing a dominant-negative effect on platelet function and bleeding diathesis. American Journal of Hematology, 96(2), E33–E37.

Stephanie Lunn | Computing Education | Best Researcher Award

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Dr. Stephanie Lunn | Computing Education | Best Researcher Award

Assistant Professor | Florida International University | United States

Dr. Stephanie J. Lunn’s research centers on advancing computing education through an interdisciplinary lens, with particular emphasis on fostering diversity, equity, and inclusion in STEM fields. Her work explores how technical interview preparation, AI ethics, and professional skill development can enhance student learning and readiness for computing careers, integrating pedagogical strategies that cultivate empathy, problem-solving, and collaborative skills among engineering students. She employs innovative approaches combining educational research, human-computer interaction, and cognitive neuroscience to assess and improve learning outcomes, drawing on empirical studies and data-driven insights to inform curriculum design and instructional interventions. Her scholarly contributions include publications in top-tier venues, addressing challenges in computing education, interdisciplinary collaboration, and the ethical application of artificial intelligence. Dr. Lunn has also engaged in program development to support underrepresented groups in technology, mentoring students and facilitating workshops that encourage inclusive participation in STEM. Professionally, she brings extensive experience across academic research, postdoctoral studies, and applied computational projects, spanning neuroscience, biomedical engineering, and educational technology. Her work bridges theoretical frameworks and practical applications, emphasizing human-centered design and the social dimensions of technology education, while promoting evidence-based strategies for teaching, learning, and workforce preparation in computing. Through a combination of research, program leadership, and professional engagement, Dr. Lunn contributes to shaping the next generation of computing professionals with a focus on ethical awareness, social responsibility, and adaptive learning, demonstrating a consistent commitment to advancing both educational practice and the broader societal impact of technology.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

Lunn, S. J., Arunachalam, N., Becerra, N., Weiss, M., Liu, J., & Narasimhan, G. (2025, June 13). Dipping a toe into computing: Offering a short-term program for students majoring in other fields. Conference paper.

Arunachalam, N., Lunn, S. J., Thapaliya, A., Narasimhan, G., Liu, J., & Weiss, M. (2025, February 18). Crafting opportunities: Establishing a micro-internship program for computing students. Conference paper.

Hooper, K., & Lunn, S. J. (2025, February 18). Traversing new horizons: An exploration of educational policies on generative AI. Conference paper.

Garcia, R., Csizmadia, A., Pearce, J. L., Alshaigy, B., Glebova, O., Harrington, B., Liaskos, K., Lunn, S. J., MacKellar, B., Nasir, U., et al. (2025, January 22). An international examination of non-technical skills and professional dispositions in computing — Identifying the present day academia-industry gap. Conference paper.

Garcia, R., Csizmadia, A., Pearce, J. L., Alshaigy, B., Glebova, O., Harrington, B., Liaskos, K., Lunn, S. J., MacKellar, B., Nasir, U., et al. (2024, July 8). All for one and one for all — Collaboration in computing education: Policy, practice, and professional dispositions. Conference paper.