Dr. Mohammad Ali Nematollahi 📚 is a distinguished Assistant Professor at Fasa University, Iran, known for his significant contributions to mathematics and computer science. He holds a Ph.D. from Sharif University of Technology and has published extensively in top-tier journals, covering topics like spectral graph theory, Seidel energy, and machine learning applications in medicine 🤖🩺. With a strong teaching portfolio, Dr. Nematollahi has inspired many students while maintaining a consistent record of academic excellence 🏆. His numerous awards, including a Silver Medal at the International Mathematics Olympiad for University Students, highlight his dedication and talent. Though his international collaborations could expand further, his interdisciplinary research and exceptional teaching make him a standout candidate for recognition as a Best Academic Researcher 🌐.
Professional Profile
Education 🎓
Dr. Mohammad Ali Nematollahi began his academic journey at Andisheh Magnet High School in Shiraz, where he excelled with top GPAs in both high school and pre-university studies. He then earned his B.Sc., M.Sc., and Ph.D. in Mathematics from Sharif University of Technology, Tehran—one of Iran’s most prestigious institutions. His graduate research delved into Pfister’s Local-Global Principle and the Spectral Theory of Signed Graphs and Digraphs, under renowned supervisors. This strong educational foundation equipped him with a robust understanding of both pure and applied mathematics, fostering interdisciplinary research and teaching excellence. His academic record, marked by consistently high grades and prestigious scholarships, reflects his dedication and passion for learning, setting the stage for a dynamic and influential academic career. 🌟
Professional Experience 💼
Dr. Mohammad Ali Nematollahi serves as an Assistant Professor at Fasa University’s Department of Computer Sciences, where he bridges mathematics and computer science through teaching and research. His academic roles include teaching courses like Graph Theory, Advanced Programming (Python), Foundations of Combinatorics, and Machine Learning Applications 📊. Earlier, he honed his teaching skills as a Teaching Assistant at Sharif University of Technology, covering Calculus, Linear Algebra, and Differential Equations. Dr. Nematollahi’s experience also extends to supervising undergraduate and graduate students, mentoring them in complex research areas. His diverse experience showcases his versatility, making him a dynamic educator and researcher with expertise that resonates across disciplines. 💼
Research Interest 🔬
Dr. Mohammad Ali Nematollahi’s research interests span a fascinating intersection of graph theory, spectral analysis, combinatorics, and applied machine learning. His work on Seidel energy of graphs, spectral characterizations of signed cycles, and circular zero-sum flows has advanced theoretical understanding of graphs 📈. Additionally, his research extends to machine learning applications, notably in medical diagnostics, disease prediction, and sentiment analysis of social media data. This interdisciplinary approach highlights his ability to tackle both theoretical and practical challenges, positioning him as a forward-thinking researcher whose work benefits academia and society alike. His passion for bridging abstract mathematics with real-world problems drives his continuous exploration of innovative solutions. 🌐
Awards and Honors 🏅
Dr. Mohammad Ali Nematollahi’s academic journey is marked by numerous awards and honors, underscoring his dedication and talent. Early in his career, he ranked in the top 0.1% in the Mathematics Nationwide Entrance Exam and secured admission to Sharif University of Technology. His remarkable achievements continued with a silver medal at the International Mathematics Olympiad for University Students, ranking fifth among top talents. He also won exceptional talent scholarships at both M.Sc. and Ph.D. levels. These accolades reflect his academic excellence and unwavering commitment to advancing mathematical knowledge. Each honor affirms his standing as a distinguished scholar whose contributions resonate globally. 🥇
Research Skills 💻
Dr. Mohammad Ali Nematollahi boasts an impressive skill set, seamlessly blending theoretical mathematics and computational techniques. He is proficient in Python, Mathematica, and SageMath, enabling him to model complex systems and analyze large datasets. His expertise extends to machine learning algorithms, supporting research in medical diagnostics and disease prediction. He is also adept at using LaTeX for professional documentation and Microsoft Office for academic administration 📑. His technical skills empower him to tackle multifaceted research challenges, from graph theory to real-world applications. This diverse toolbox allows him to develop innovative solutions, bridging theory and practice with precision and creativity. 🤖
Publications Top Notes
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Effective class-imbalance learning based on SMOTE and convolutional neural networks
Authors: JH Joloudari, A Marefat, MA Nematollahi, SS Oyelere, S Hussain
Year: 2023
Citations: 132
Source: Applied Sciences 13(6), 4006
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BERT-deep CNN: State of the art for sentiment analysis of COVID-19 tweets
Authors: JH Joloudari, S Hussain, MA Nematollahi, R Bagheri, F Fazl, …
Year: 2023
Citations: 65
Source: Social Network Analysis and Mining 13(1), 99
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Prognosis prediction in traumatic brain injury patients using machine learning algorithms
Authors: H Khalili, M Rismani, MA Nematollahi, MS Masoudi, A Asadollahi, …
Year: 2023
Citations: 44
Source: Scientific Reports 13(1), 960
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GSVMA: a genetic support vector machine ANOVA method for CAD diagnosis
Authors: J Hassannataj Joloudari, F Azizi, MA Nematollahi, R Alizadehsani, …
Year: 2022
Citations: 26
Source: Frontiers in Cardiovascular Medicine 8, 760178
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Proof of a conjecture on the Seidel energy of graphs
Authors: S Akbari, M Einollahzadeh, MM Karkhaneei, MA Nematollahi
Year: 2020
Citations: 25
Source: European Journal of Combinatorics 86, 103078
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Spectral characterizations of signed cycles
Authors: S Akbari, F Belardo, E Dodongeh, MA Nematollahi
Year: 2018
Citations: 22
Source: Linear Algebra and Its Applications 553, 307-327
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DNN-GFE: a deep neural network model combined with global feature extractor for COVID-19 diagnosis based on CT scan images
Authors: JH Joloudari, F Azizi, I Nodehi, MA Nematollahi, F Kamrannejhad, …
Year: 2021
Citations: 20
Source: EasyChair 6330
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Body composition predicts hypertension using machine learning methods: a cohort study
Authors: MA Nematollahi, S Jahangiri, A Asadollahi, M Salimi, A Dehghan, …
Year: 2023
Citations: 18
Source: Scientific Reports 13(1), 6885
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CCTCOVID: COVID-19 detection from chest X-ray images using Compact Convolutional Transformers
Authors: A Marefat, M Marefat, J Hassannataj Joloudari, MA Nematollahi, …
Year: 2023
Citations: 13
Source: Frontiers in Public Health 11, 1025746
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Association and predictive capability of body composition and diabetes mellitus using artificial intelligence: a cohort study
Authors: MA Nematollahi, A Askarinejad, A Asadollahi, M Salimi, M Moghadami, …
Year: 2022
Citations: 7
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Mixed paths and cycles determined by their spectrum
Authors: S Akbari, A Ghafari, M Nahvi, MA Nematollahi
Year: 2020
Citations: 5
Source: Linear Algebra and Its Applications 586, 325-346
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A short proof of Haemers’ conjecture on the Seidel energy of graphs
Authors: M Einollahzadeh, MA Nematollahi
Year: 2024
Citations: 3
Source: Linear Algebra and Its Applications 695, 75-78
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A cohort study on the predictive capability of body composition for Diabetes Mellitus using machine learning
Authors: MA Nematollahi, A Askarinejad, A Asadollahi, M Bazrafshan, S Sarejloo, …
Year: 2024
Citations: 3
Source: Journal of Diabetes & Metabolic Disorders 23(1), 773-781
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Improving Prediction of Mortality in ICU via Fusion of SelectKBest with SMOTE Method and Extra Tree Classifier
Authors: M Maftoun, JH Joloudari, O Zare, M Khademi, A Atashi, MA Nematollahi, …
Year: 2024
Citations: 3
Source: International Work-Conference on the Interplay Between Natural and …
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Improving a lower bound for Seidel energy of graphs
Authors: MR Oboudi, MA Nematollahi
Year: 2023
Citations: 3
Source: MATCH Commun. Math. Comput. Chem 89, 489-502
Conclusion ✨
Dr. Mohammad Ali Nematollahi exemplifies excellence in academia through his outstanding education, professional experience, research interests, awards, and technical skills. His dedication to advancing mathematical knowledge and applying it to real-world challenges makes him a leading figure in his field. His passion for teaching and mentoring nurtures the next generation of scholars, while his collaborative spirit and interdisciplinary approach enhance the global impact of his research. As a candidate for the Best Academic Researcher Award, Dr. Nematollahi stands out for his remarkable contributions, innovation, and unwavering commitment to excellence. He is undoubtedly a deserving nominee for this prestigious recognition. 🏆