Heba Afify | Engineering | Editorial Board Member

Published on by Young Scientists Awards

Dr. Heba Afify | Engineering | Editorial Board Member

Cairo | Egypt

Dr. Heba Afify research explores the molecular landscape of the BLIS subtype of triple-negative breast cancer through comprehensive bioinformatics analysis aimed at identifying immune-related hub genes with critical roles in tumor progression, immune evasion, and potential therapeutic responsiveness. Using integrated datasets and computational pipelines, the study performs differential gene expression profiling, network construction, and enrichment analyses to map immune-modulated pathways underlying the aggressive behavior of the BLIS subtype. Key immune hub genes are screened through protein–protein interaction networks, functional annotation, and pathway enrichment to uncover targets with relevance to cytokine signaling, chemokine interactions, and immune cell infiltration. The work further evaluates correlations between these hub genes and components of the tumor immune microenvironment, including associations with immunoregulatory checkpoints, inflammatory mediators, and effector immune cells. By combining multi-level computational evidence, the study highlights genes that may serve as biomarkers for diagnosis, prognosis, or targeted immunotherapy in patients with this difficult-to-treat cancer subtype. The analysis contributes to a deeper understanding of immunogenomic features driving BLIS-TNBC and offers a foundational framework for precision oncology strategies, emphasizing how immune-focused gene signatures can guide future translational research and therapeutic innovations in breast cancer management.

Featured Publications

Adel, H., Abdel Wahed, M., & Afify, H. M. (2025). Bioinformatics analysis for immune hub genes in BLIS subtype of triple-negative breast cancer. Egyptian Journal of Medical Human Genetics. https://doi.org/10.1186/s43042-025-00745-0

Afify, H. M., Mohammed, K. K., & Hassanien, A. E. (2025). Stress detection based EEG under varying cognitive tasks using convolution neural network. Neural Computing and Applications, Advance online publication. https://doi.org/10.1007/s00521-024-10737-7

Afify, H. M., Mohammed, K. K., & Hassanien, A. E. (2024). Insight into automatic image diagnosis of ear conditions based on optimized deep learning approach. Annals of Biomedical Engineering. https://doi.org/10.1007/s10439-023-03422-8

Waleed Algriree | Engineering | Editorial Board Member

Published on by Young Scientists Awards

Dr. Waleed Algriree | Engineering | Editorial Board Member

Putra university malaysia | Malaysia

Dr. Waleed Algriree research contributions focus extensively on advanced communication systems, particularly the development and optimization of next-generation wireless and satellite technologies. Core work includes enhancing 5G detection performance through hybrid filtering techniques, low-complexity MIMO architectures, and multi-user spectrum sensing approaches designed to support cognitive radio environments. Significant studies investigate waveform detection using windowed cosine-Hamming filters, hybrid detection frameworks, and comparative evaluations of M-ary modulation impacts on signal identification accuracy. Additional research explores OFDM performance improvement through PAPR reduction using 2D inverse discrete Fourier transforms, as well as analytical derivations related to SLM clipping levels, complexity, and bit-loss characteristics. Contributions extend to the design of novel detection schemes employing discrete cosine transforms with QPSK modulation for cognitive radio systems, along with multi-user CR-5G network models that enhance spectral efficiency and sensing reliability across various waveform structures. Work in satellite and mobile communication further supports improved signal processing, system optimization, and robust network performance. Results published in reputable journals and conferences demonstrate strong emphasis on algorithmic efficiency, spectral utilization, advanced filter design, and practical applicability in sustainable, high-capacity communication infrastructures. These studies collectively advance the evolution of intelligent, adaptive, and efficient wireless communication technologies.

Featured Publication

Algriree, W. K. H. (Year). Advancing healthcare through piezoresistive pressure sensors: A comprehensive review of biomedical applications and performance metrics.

Mujeeb Abiola Abdulrazaq | engineering | Young Scientist Award

Published on by Young Scientists Awards

Mr. Mujeeb Abiola Abdulrazaq l engineering
| Young Scientist Award

University of North Carolina at Charlotte | United States

Mr. Mujeeb Abiola’s research focuses on advancing transportation safety and efficiency through data-driven methodologies and emerging technologies. His work extensively employs large-scale traffic and crash data, including millions of federal highway administration records, to investigate the spatiotemporal dynamics of pedestrian crashes and the evolution of crash hotspots. Utilizing advanced statistical and machine learning models, he has developed predictive frameworks that outperform traditional Highway Safety Manual standards, providing robust insights into risk factors and injury severity in both human-driven and autonomous vehicle contexts. His research on connected and autonomous vehicles (CAVs) has led to the development of traffic control algorithms that significantly enhance safety, operational efficiency, and environmental sustainability in freeway work zones. Furthermore, his studies integrate GPU-accelerated data processing, simulation-based optimization, and multi-level heterogeneity modeling to evaluate vulnerable road user behavior and assess dynamic collision risks. Through simulation platforms such as VISSIM and SUMO, combined with Python-based data analysis and GIS applications, his work systematically addresses complex traffic scenarios, including merging, diverging, and weaving segments, while also accounting for seasonal variations and temporal constraints in crash determinants. His contributions include empirical analyses of autonomous vehicle incidents, methodological advancements in microsimulation accuracy, and development of actionable strategies for real-world traffic management, ultimately aiming to improve roadway safety, inform policy, and guide evidence-based planning in modern transportation systems.

Profile:  Google Scholar 

Featured Publications

  • Abdulrazaq, M. A., & Fan, W. D. (2024). Temporal dynamics of pedestrian injury severity: A seasonally constrained random parameters approach. International Journal of Transportation Science and Technology, 9.

  • Abdulrazaq, M. A., & Fan, W. (2025). A priority based multi-level heterogeneity modelling framework for vulnerable road users. Transportmetrica A: Transport Science, 1–34. https://doi.org/10.1080/23249935.2025.2516817

  • Abdulrazaq, M. A., & Fan, W. (2025). Seasonal instability in crash determinants: A partially temporally constrained modeling analysis. SSRN 5341417. https://doi.org/10.2139/ssrn.5341417

Desen Özkan | Engineering | Best Researcher Award

Published on by Young Scientists Awards

Desen Özkan | Engineering | Best Researcher Award

Dr Desen Özkan, University of Connecticut, United States

Dr. Desen Özkan is an Assistant Professor of Chemical and Biomolecular Engineering at the University of Connecticut, with an affiliate position in the Neag School of Education. He is also the Graduate Program Director for the Engineering Education Ph.D. program. Dr. Özkan’s research focuses on sociotechnical identity development, equity in engineering education, and offshore wind energy. He holds a Ph.D. in Engineering Education from Virginia Tech and has held postdoctoral roles at Tufts University. Dr. Özkan’s work bridges engineering, education, and social justice, emphasizing interdisciplinary collaboration and inclusive curricula. 🌍⚙️📚💡🌱

Publication Profile

google scholar

Education

Dr. Desen Özkan holds a Ph.D. in Engineering Education from Virginia Polytechnic Institute and State University (2020), where she focused on transdisciplinary approaches in interdisciplinary faculty teaching. She has an extensive academic background with courses from prestigious institutions. Dr. Özkan completed projects on offshore wind energy economics at the University of Massachusetts and structural engineering at Tufts University. She also studied environmental chemistry, microbiology, and mathematical modeling at the University of Tennessee. Her B.S. in Chemical and Biological Engineering was earned at Tufts University in 2013. Dr. Özkan’s work merges engineering, education, and sustainability. 🌍⚙️🎓📚

Experience

Dr. Desen Özkan has diverse research experience in both engineering and social sciences. As a Postdoctoral Researcher at Tufts University, she analyzed job development in Maine’s offshore wind industry, producing the report Floating to the Top (2021), and contributed to a study on equity in offshore wind job development, invited by Connecticut State Legislators (2022). At Virginia Tech, she worked on the NSF-funded Revolutionizing Engineering and Computer Engineering Departments project (2018-2019) and contributed to the Science, Technology, and Society department’s undergraduate degree proposal (2019). Additionally, Dr. Özkan conducted water quality research at the University of Tennessee, focusing on wastewater reclamation. 🌊💡🔬

Awards and Recognition

Dr. Desen Özkan has received multiple nominations for Tufts University’s Significant Impact Awards, recognizing her outstanding contributions to STEM education. Her dedication to mentoring and promoting diversity within the field has been a hallmark of her career. Additionally, Dr. Özkan was selected to participate in the prestigious New Energy Summer Summit at Dartmouth, further highlighting her commitment to advancing innovation and sustainability. These accolades underscore her impactful work in fostering inclusive environments and pushing boundaries in science and technology. Her achievements inspire future generations of diverse STEM leaders. 🏆👩‍🔬🌍💡

Conference Activity

Dr. Desen Özkan has presented at numerous conferences, focusing on sociotechnical engineering education and diversity in the field. Notable presentations include “Positionality, Empathy, and Subjectivity in Research” at the 2024 Compassion and Global Citizenship Conference, and “What is a Job? Deconstructing Offshore Wind Jobs” at the 2024 Petrocultures Conference. Additionally, Dr. Özkan co-presented papers on worker safety in offshore wind at the ASEE Annual Conference and explored environmental racism in engineering courses. Her work also includes teaching design through sociotechnical perspectives, with a focus on student experiences in first-year engineering courses. 🎤🌍📚

Research Focus

Dr. Desen Özkan’s research primarily focuses on the intersection of engineering education, diversity, and sociotechnical systems. Her work explores how contextualization and cultural considerations can enhance learning experiences in engineering education. She investigates methods like persona-based curricular design and emphasizes the importance of addressing reality gaps in senior design projects. Additionally, Dr. Özkan examines the positionality of researchers in engineering education and the teacher-learner dynamic. Her research aims to make engineering education more inclusive, effective, and adaptable, particularly for minoritized groups. 🛠️📚💡🎓

Publication Top Notes

Positionality statements in engineering education research: A look at the hand that guides the methodological tools

Contextualization as virtue in engineering education

Using personas as curricular design tools: Engaging the boundaries of engineering culture

Contextualization in engineering education: A scoping literature review

Teacher learner, learner teacher: parallels and dissonance in an interdisciplinary design education minor

Reality gaps in industrial engineering senior design or capstone projects

Perspectives of Seven Minoritized Students in a First-Year Course Redesign toward Sociotechnical Engineering Education

TABASUM GULEDGUDD | Engineering | Best Researcher Award

Published on by Young Scientists Awards

TABASUM GULEDGUDD | Engineering | Best Researcher Award

Ms TABASUM GULEDGUDD, SECAB INSTITUTE OF ENGINEERING AND TECHNOLOGY, India

Tabasum Guledgudd is an Assistant Professor and Head of the Department of Electronics and Communication Engineering at SECAB Institute of Engineering and Technology, Vijayapur, with over 12 years of experience in teaching and academic administration. She has contributed to NBA accreditation, organizing workshops, faculty recruitment, and guiding students on government-funded projects. Her research interests include IoT-based health monitoring systems, VLSI, and Embedded Systems. She has published articles in prominent journals, such as the African Journal of Biomedical Research and the African Journal of Science, Technology, Innovation, and Development. She is also actively involved in workshops and FDPs. 📚💡🖥️🎓

Publication Profile

Orcid

Academic Profile 

Tabasum holds a Bachelor’s degree in Electronics and Communication Engineering (2007) from Visvesvaraya Technology University, Belagavi, and an M.Tech. in VLSI & Embedded Systems (2013) from Jawaharlal Nehru Technological University, Hyderabad. Currently, she is pursuing her Ph.D. (Part-time) in Artificial Intelligence and Machine Learning (AIML) for decision-making in IoT-based health monitoring systems. She successfully completed her comprehensive viva in 2018. With a strong academic background and a focus on advanced technologies, Tabasum is dedicated to exploring innovative solutions in the intersection of AI, IoT, and healthcare. 💻🤖📡📊🎓

Employment Record

Ms. Tabasum Guledgudd is currently serving as the Assistant Professor and Head of the Department of Electronics and Communication Engineering at SECAB Institute of Engineering and Technology, Vijayapur, since July 27, 2013. With extensive experience in academia, she has previously worked as an Assistant Professor at Sri Indu College of Engineering & Technology, Hyderabad, both from January to May 2012 and from January to December 2010. Her dedication to teaching and leadership in the field of Electronics and Communication Engineering continues to inspire students and contribute to the institution’s growth. 📚👩‍🏫📡

Research Experience

Ms. Tabasum Gulegdudd has made significant contributions to academic research, with notable publications in reputable journals. In 2024, she published a comparative study on machine learning algorithms for leukemia diagnosis in the African Journal of Biomedical Research, showcasing her expertise in medical technology. Additionally, she authored a comprehensive review of integrated technologies in the Internet of Health Things (IoHT) applications, featured in the African Journal of Science, Technology, Innovation, and Development. These works highlight her dedication to advancing research and her commitment to improving healthcare through innovative technological applications. 📚💻🩺📈

Previous Employment 

Tabasum Guledgudd is an experienced academic professional who previously served as an Assistant Professor at Sri Indu College of Engineering & Technology, Hyderabad, from January 2009 to May 2012. Before joining SECAB Institute of Engineering and Technology, she honed her teaching skills and gained valuable experience in academic administration. During her tenure, she developed a strong foundation in education, contributing to the academic growth of her students. Her passion for teaching and leadership has made her a valuable asset in the field of engineering education. 📚👩‍🏫🏫🌟

Current Employment 

Ms. Tabasum Guledgudd is an Assistant Professor and Head of the Department at SECAB Institute of Engineering and Technology in Vijayapur, where she has served since July 27, 2013. Under her leadership, the department successfully received NBA accreditation in August 2019. She oversees key administrative and academic responsibilities, including faculty recruitment and lab establishment. Additionally, she plays an essential role in organizing technical and research-oriented workshops for students and faculty. Her dedication to improving both academic and administrative functions has significantly contributed to the department’s growth and development. 🎓📚🏫🔧👩‍🏫

Research Focus

Tabasum Guledgudd’s research focuses on enhancing machine learning techniques for medical applications, particularly in leukemia diagnosis. Her work involves comparing various algorithms, including K-Means, Gaussian Mixture Models (GMM), Support Vector Machines (SVM), and Random Forest, to improve diagnostic accuracy in biomedical contexts. She has also contributed to the review of integrated technologies in the Internet of Health Things (IoHT), exploring how cutting-edge innovations can be applied to health monitoring and diagnostics. Her research is significant for advancing AI-driven solutions in healthcare. 💻🩺📊💡

Publication Top Notes

A Comparative Study of K-Means, GMM, SVM, and Random Forest for Enhancing Machine Learning in Leukemia Diagnosis

A comprehensive review: State of art integrated technologies in IoHT applications