Yidnekachew Awraris | Systems Biology | Best Researcher Award

Posted on by Computational Biologists

Dr. Yidnekachew Awraris | Systems Biology | Best Researcher Award

Assistant professor of biology education at Dilla college of education, Ethiopia.

Dr. Yidnekachew Awraris Kebede is an Assistant Professor of Biology Education at Dilla College of Teacher Education in Ethiopia and a Doctor of Education candidate at Hawassa University. He holds an MSc in Applied Microbiology and has over 20 years of experience in teaching and educational leadership. His research focuses on cooperative learning and science education, with publications in international journals such as Science Education International and SAGE Open. Fluent in Amharic and English, Dr. Yidnekachew is dedicated to improving biology instruction and fostering student achievement through innovative, learner-centered approaches.

🎓 Educational Background:

Dr. Yidnekachew Awraris Kebede began his formal education at Rabel Elementary School, where he studied from 1988 to 1995. He continued his secondary education at Mehalmeda Preparatory and Secondary School between 1996 and 1999 Ethiopian Calendar. Pursuing his passion for science, he enrolled at Debreberhan University, earning a Bachelor of Education degree in Biology from 2000 to 2002 EC. He advanced his studies at Hawassa University, where he completed a Master of Science degree in Applied Microbiology between 2007 and 2009 EC. Demonstrating a commitment to continuous professional growth, he is currently a Doctor of Education candidate in Biology at Hawassa University, with studies spanning from 2021 to 2025. In addition to his academic degrees, Dr. Yidnekachew holds a Higher Diploma License in Education from Dilla University, further strengthening his expertise in teaching and educational practice.

Profile:

Professional Experience:

Dr. Yidnekachew began his career as a Biology Teacher and Head of the Biology Department at Bilate Tena Secondary School, where he served from September 2003 to November 2005 EC. He then joined Dilla College of Teacher Education, contributing as a Lecturer and Mathematics and Natural Science Stream Officer from 2005 to 2013 EC. His dedication and expertise led to his current role as an Assistant Professor of Biology Education at Dilla College of Teacher Education, where he mentors aspiring educators and advances the field of biology education.

Skills and Competencies:

In addition to his academic qualifications, Dr. Yidnekachew is proficient in computer applications, including MS Word, MS Excel, and MS Access. His technological skills support his research activities, teaching, and administrative responsibilities, ensuring effective delivery of educational content and management of academic records.

Interests and Hobbies:

Beyond his professional life, Dr. Yidnekachew enjoys reading books, magazines, and newspapers, keeping himself informed about developments in science and society. He is also passionate about watching movies and soccer. Additionally, he participates actively in charity work, reflecting his commitment to community service and social responsibility.

Publications:

  • Unlocking the Power of Togetherness: Exploring the Impact of Cooperative Learning on Peer Relationships, Academic Support, and Gains in Secondary School Biology in Gedeo Zone
    YA Kebede, FK Zema, GM Geletu, SA Zinabu
    Science Education International, 2024

  • Cooperative Learning Instructional Approach and Student’s Biology Achievement: A Quasi-Experimental Evaluation of Jigsaw Cooperative Learning Model in Secondary Schools in Ethiopia
    YA Kebede, FK Zema, GM Geletu, SA Zinabu
    SAGE Open, 2025

  • Misconceptions as a Barrier to Understanding Biological Science Lessons: A Systematic Review of Pertinent Studies
    GM Geeltu
    Ethiopian Journal of Education Studies, 2023

  • Effects of Cooperative Learning on the Academic Achievement and Attitude Towards Cooperative Learning: The Case of Dilla College of Teacher Education First Year Mathematics Students
    YAKS ZB Tademe Zula Biramo
    Dilla Journal of Education, 2022

Zhang Xiaoming | Pharmacogenomics Modeling | Best Researcher Award

Posted on by Computational Biologists

Dr. Zhang Xiaoming | Pharmacogenomics Modeling | Best Researcher Award 

Associate research fellow at National Institutes for Food and Drug Control, China.

Dr. Xiaoming Zhang is an Associate Professor at the National Institutes for Food and Drug Control, Beijing, with a strong background in molecular biology and biopharmaceutical research. He holds a Ph.D. in Life Sciences from Peking University and has held research positions at both Peking University and the National University of Singapore. His work focuses on the development of innovative reporter gene assays for evaluating therapeutic protein and peptide bioactivity. With multiple first-author publications in high-impact journals and international research experience, Dr. Zhang is recognized for his contributions to translational research and regulatory science.

🎓 Academic Background:

Dr. Xiaoming Zhang began his scientific journey with a Bachelor’s degree in Life Sciences from Hebei University (2003–2007), laying a strong foundation in biological research. Driven by a deep curiosity for life at the molecular level, he pursued his Ph.D. in Life Sciences at the prestigious Peking University (2007–2012), where he delved into advanced molecular biology and genetics. His academic rigor and commitment to scientific excellence during this formative phase established the groundwork for a successful research career.

Profile:

🧪 Professional Experience:

Dr. Zhang’s professional trajectory is marked by steady progress and international exposure. He first worked as a Research Assistant at the School of Chemical Biology & Biotechnology, Peking University (2012–2013), contributing to innovative biochemical studies. In 2013, he joined the Department of Biochemistry at Yong Loo Lin School of Medicine, National University of Singapore, where he served as a Research Fellow for nearly six years. Here, he refined his expertise in translational research and therapeutic bioassays. Since March 2019, Dr. Zhang has been serving as an Associate Professor at the National Institutes for Food and Drug Control in Beijing, playing a key role in therapeutic evaluations and regulatory science.

📚 Research Contributions:

Dr. Zhang is renowned for his pioneering work in the development of reporter gene assays to evaluate the biological activities of therapeutic proteins and peptides. His research spans a broad spectrum—from PEGylated recombinant human growth hormone to glucagon-like peptide-2 analogues, addressing critical needs in drug development. Notably, his recent publications in Journal of Pharmaceutical Analysis, Molecules, and iScience highlight his innovative approaches to bioassay design and therapeutic evaluation. His co-authorship and first-author roles in multiple peer-reviewed journals underscore his direct involvement in impactful discoveries.

🏅 Recognition and Impact:

While Dr. Zhang’s scientific publications speak volumes, his true impact lies in the translation of molecular insights into therapeutic assessment tools. His work contributes significantly to drug safety and efficacy testing, ensuring that biologics are accurately evaluated before reaching patients. As an Associate Professor at a national regulatory institute, his role bridges academic innovation and public health policy, making his contributions both scientifically rigorous and socially relevant.

🚀 Future Potential:

Dr. Xiaoming Zhang’s career demonstrates an upward trajectory with great potential for further leadership in biopharmaceutical regulation and translational research. With continued contributions to therapeutic bioactivity assays, regulatory innovation, and interdisciplinary collaborations, Dr. Zhang stands out as a valuable contributor to global health sciences. He is a strong contender for prestigious recognitions such as the Best Researcher Award, and his journey is a testament to dedication, innovation, and scientific excellence.

Publications:

  1. An improved reporter gene assay for evaluating the biological activity of recombinant human growth hormone
    Journal of Pharmaceutical Analysis, 2025

    • Authors: Xiaoming Zhang, Heyang Li, Ying Huang, Ping Lv, Lvyin Wang, Kezheng Xu, Yi Li, Xinyue Hu, Yue Sun, Cheng-gang Liang, Jing Li

  2. Development of a Mechanism of Action-Reflective Cell-Based Reporter Gene Assay for Measuring Bioactivities of Therapeutic Glucagon-like Peptide-2 Analogues
    Molecules, 2025

  3. A Reporter Gene Assay for Measuring the Biological Activity of PEGylated Recombinant Human Growth Hormone
    Molecules, 2025

    • Authors: Shaowang Hu*, Xiaoming Zhang*, Yi Li, Jing Li, Yingwu Wang, Chenggang Liang

    • (Co-first author)

  4. MLL5 regulates Rhodopsin gene expression by acting as a novel coactivator of CRX
    iScience, 2022

    • Authors: Zhang XM, Zhang BW, Xiang L, Wu H, Zhou PP, Alexander SAS, Zhou P, Dai MZ, Wang X, Xiong W, Zhang Y, Jin ZB, Deng LW

  5. MLL5 (KMT2E): structure, function, and clinical relevance
    Cellular and Molecular Life Sciences, 2017

    • Authors: Zhang XM, Novera W, Zhang Y, Deng LW

  6. Pluripotent Stem Cell Protein Sox2 Confers Sensitivity towards LSD1 Inhibition in Cancer Cells
    Cell Reports, 2013

    • Authors: Xiaoming Zhang, Fei Lu, Jing Wang, Feng Yin, Zhengshuang Xu, Dandan Qi, Yuwen Cao, Weihua Liang, Yuqing Liu, Yundong Wu, Hong Sun, Tao Ye, Hui Zhang

maryam | Computational Neuroscience | Best Researcher Award

Posted on by Computational Biologists

Dr. maryam | Computational Neuroscience | Best Researcher Award 

faculty at Shahrekord University, Iran.

Dr. Maryam Taghizadeh is an Assistant Professor of Communication Engineering at Shahrekord University, Iran. With a Ph.D. from Isfahan University of Technology, her research focuses on signal and image processing, particularly in medical applications such as brain tumor segmentation and autism diagnosis using EEG and deep learning. She has published extensively in reputable journals and has actively contributed to academic conferences as a chair and committee member. Dr. Taghizadeh is also a dedicated mentor, guiding graduate research in biomedical signal processing and AI-driven diagnostics.

🎓Academic Background:

Dr. Maryam Taghizadeh holds a distinguished academic background in Electrical and Communication Engineering. She earned her Ph.D. in Communication Engineering from Isfahan University of Technology in 2014, following her M.Sc. (2003) and B.Sc. (2001) degrees from the same institution. Her educational journey laid a strong foundation in signal processing, communications, and applied research, setting the stage for her impactful contributions in both academia and biomedical research.

Profile:

💼 Professional Experience:

Dr. Maryam Taghizadeh has been serving as an Assistant Professor at the Faculty of Technology and Engineering, Shahrekord University, Iran, since 2014. In this role, she has actively engaged in teaching, research, and student supervision in the fields of communication engineering and biomedical signal processing. Her expertise lies in image analysis, EEG signal interpretation, and the application of artificial intelligence in medical diagnostics. She has led numerous research projects related to brain disorders such as autism and brain tumors, using advanced techniques like deep learning, wavelet transforms, and active contour models. In addition to her academic responsibilities, Dr. Taghizadeh has contributed significantly to the scientific community by participating in the organization of major conferences. She served as the Chairperson of the 3rd International Conference on Pattern Recognition and Image Analysis and has been a Scientific and Executive Committee Member in multiple editions of national and international conferences on machine vision and image processing. Through her research, mentorship, and leadership, she continues to play a vital role in advancing interdisciplinary engineering and healthcare innovation in Iran and beyond.

🧪 Scientific and Research Excellence:

Dr. Maryam Taghizadeh has demonstrated outstanding scientific and research excellence in the interdisciplinary fields of signal processing, image analysis, and biomedical engineering. Her pioneering work in developing automated methods for brain tumor segmentation, EEG-based autism diagnosis, and functional brain network analysis reflects a deep integration of engineering principles with healthcare innovation. She has published high-impact research in internationally recognized journals, such as IET Computer Vision and the International Journal of Neural Systems, showcasing both originality and practical relevance. Dr. Taghizadeh’s ability to apply machine learning, deep networks, and wavelet transforms to real-world medical problems marks her as a leader in AI-driven healthcare solutions. Furthermore, her active roles in organizing international conferences and mentoring graduate students further amplify her contribution to advancing science and fostering the next generation of researchers.

🧠 Areas of Expertise:

Dr. Maryam Taghizadeh’s research bridges the fields of signal and image processing, biomedical engineering, and artificial intelligence, with a special focus on medical applications. Her work includes developing algorithms for brain tumor segmentation, autism detection using EEG signals, and analyzing bioacoustic patterns in insects. She has authored and co-authored several impactful papers in reputable journals such as IET Computer Vision and International Journal of Neural Systems. Her research is widely recognized for its innovation in applying deep learning, wavelet transforms, and active contour models to real-world medical challenges.

👩‍🏫 Student Mentorship:

As a dedicated mentor, Dr. Maryam Taghizadeh has supervised numerous master’s theses in areas such as EEG signal processing, autism detection, cognitive brain analysis, and deep learning models for healthcare diagnostics. Her students have explored cutting-edge topics, contributing to the advancement of neuroscience and computational medicine under her guidance.

🌐 Academic Leadership:

Beyond her research, Dr. Maryam Taghizadeh has played a vital role in academic leadership. She has served on the Scientific Committee of the Iranian Conference on Machine Vision and Image Processing and the International Conference on Pattern Recognition and Image Analysis. Notably, she chaired the 3rd edition of the latter and was a member of the executive committee for its 6th edition in 2023, showing her ongoing engagement in shaping research dialogue and collaboration.

Publications:

  • A Review of Coronary Vessel Segmentation Algorithms
    M.T. Dehkordi, S. Sadri, A. Doosthoseini
    Journal of Medical Signals & Sensors, 1(1), pp. 49–54, 2011.
    Cited by: 81

  • Local Feature Fitting Active Contour for Segmenting Vessels in Angiograms
    M. Taghizadeh Dehkordi, A.M. Doost Hoseini, S. Sadri, H. Soltanianzadeh
    IET Computer Vision, 8(3), pp. 161–170, 2014.
    Cited by: 37

  • Diagnosis of Autism Disorder Based on Deep Network Trained by Augmented EEG Signals
    H.A. Ardakani, M. Taghizadeh, F. Shayegh
    International Journal of Neural Systems, 32(11), Article 2250046, 2022.
    Cited by: 17

  • Segmentation of Coronary Vessels by Combining the Detection of Centerlines and Active Contour Model
    M. Taghizadeh, S. Sadri, A. Doosthoseini
    Proceedings of the 7th Iranian Conference on Machine Vision and Image Processing, 2011.
    Cited by: 8

  • A New Active Contour Model for Tumor Segmentation
    M.T. Dehkordi
    3rd International Conference on Pattern Recognition and Image Analysis, 2017.
    Cited by: 6

  • An Effective System to Detect Face Drowsiness Status Using Local Features in a Hierarchical Decision-Making Structure
    M.T. Dehkordi, F.S. Hafshejani, H. Pourghasem
    International Research Journal of Engineering and Technology, 5(4), pp. 646–654, 2018.
    Cited by: 3

  • Bioacoustics of Trogoderma granarium Everts (Coleoptera: Dermestidae)
    P.A. Farsani, N.S. Dehkordi, R. Ebrahimi, A. Nemati, M.T. Dehkordi
    Journal of Asia-Pacific Entomology, 27(1), Article 102189, 2024.
    Cited by: 1

  • An Automated Method for Brain Tumor Segmentation Based on Level Set
    Maryam Taghizadeh Dehkordi
    International Journal of Computer, 30(1), pp. 59–69, 2018.
    Cited by: 1

  • Investigation of Electrical Signals in the Brain of People with Autism Using Effective Connectivity Network
    F. Bahrami, M. Taghizadeh, F. Shayegh
    Journal of Medical Signals & Sensors, 14(8), Article 24, 2024.
    Cited by: 0 (as of now)