Chaima AOUICHE | Mathematics and Bioinformatics | Outstanding Scientist Award

Dr. Chaima AOUICHE | Mathematics and Bioinformatics | Outstanding Scientist Award

Dr. Chaima Aouiche is a dedicated academic and researcher in computer science with expertise in artificial intelligence, machine learning, cybersecurity, and bioinformatics. Born on October 24, 1990, in Tebessa, Algeria, she began her academic journey at Larbi Tebessi University and pursued her Ph.D. at Northwestern Polytechnical University (NPU), China. With international exposure, Dr. Aouiche has authored impactful publications on cancer gene prediction, data integration, and AI-based energy systems. She has collaborated across disciplines and countries, contributing to international conferences and peer-reviewed journals. Currently serving as a university teacher in Algeria, she is also a multilingual educator with teaching experience in China and Algeria. Dr. Aouiche combines technical knowledge with strong interpersonal skills and a passion for teaching, traveling, and community service, making her a well-rounded and globally competent scholar committed to innovation and education.

Profile

🎓 Education

Dr. Chaima Aouiche holds a strong academic foundation in computer science. She earned her Bachelor’s degree (2008–2011) and Master’s degree (2011–2013) in Computer Science from Larbi Tebessi University, Algeria, where she was recognized with the “Outstanding Student Award” in 2013. She expanded her horizons by studying the Chinese language for a year (2013–2014) at Northwestern Polytechnical University (NPU) in Xi’an, China. She then pursued a Ph.D. in Computer Science and Technology at NPU (2014–2021), focusing on stage-specific gene prediction, big data integration, and artificial intelligence. Throughout her academic journey, she acquired various global certifications, including Artificial Intelligence Foundations, Advanced Machine Learning, and Deep Learning, further enriching her qualifications. With multilingual skills in Arabic, French, English, and Chinese, she integrates global perspectives into her research and teaching. Her academic path reflects both depth and international breadth.

🧪 Experience

Dr. Chaima Aouiche has a diverse background in academia, industry, and cross-cultural teaching. She began her professional career in project management at MPE-MPI Investments, Tebessa (2011–2013), where she gained hands-on technical and administrative skills. In 2017, she taught English and Arabic in Xi’an, China, enhancing her intercultural communication and educational outreach. Currently, she works as a university teacher in Algeria, engaging in teaching, research supervision, and publication. Her training includes courses in project management, AI, and big data, complemented by technical expertise in programming (Python, Java, R), MATLAB, web technologies, and networking. Her ability to communicate in four languages (Arabic, French, English, Chinese) and her volunteering and mentoring activities reflect her commitment to holistic professional development. Dr. Aouiche’s career is defined by interdisciplinary collaboration, international exposure, and a passion for applied technological solutions, making her an asset in both academia and industry.

🏅 Awards and Honors

Dr. Aouiche’s academic and professional excellence has been recognized through multiple awards and certificates. She was awarded the Outstanding Student Award by Larbi Tebessi University in 2013. Her further accolades include numerous international certifications, such as the HSK 4 Chinese Proficiency Certificate, Artificial Intelligence and Big Data Training (Xi’an Jiaotong University), AI Foundations Masterclass (2023), and Advanced Machine Learning and Deep Learning Certificates (2024). She has also been recognized for her participation in global academic initiatives, such as the International Winter Camp (2017) and the Silk Road Engineering Science Program (2020). In addition to formal honors, her significant co-authorship on high-impact publications in BMC Bioinformatics, Frontiers in Genetics, and IEEE conferences speaks to her professional standing. These accolades collectively highlight her dedication to academic distinction, global engagement, and technological innovation.

🔬 Research Focus

Dr. Aouiche’s research intersects bioinformatics, artificial intelligence, machine learning, and cybersecurity. Her work has emphasized integrating multiple datasets to predict stage-specific cancer-related genes, mapping copy number variations, and modeling aberrant genomic events. She co-authored key studies published in BMC Bioinformatics, Frontiers in Genetics, and Quantitative Biology, which propose dynamic gene modules and data-driven cancer diagnostics. Recent work explores ensemble learning and AI approaches to detect cyberattacks using integrated datasets, showing a pivot toward cybersecurity and smart systems. Additionally, her research extends into renewable energy, specifically applying AI models to optimize photovoltaic systems and MPPT (Maximum Power Point Tracking) control. Her interdisciplinary approach bridges computational biology and engineering, reflecting her adaptability and innovative vision. Dr. Aouiche is particularly interested in applied AI that addresses real-world challenges in medicine, energy, and security, with a growing focus on industry 4.0 applications.

✅ Conclusion

Dr. Chaima Aouiche is an innovative computer scientist and academic whose international education, multidisciplinary research in AI and bioinformatics, commitment to teaching, and dynamic professional experiences make her a valuable contributor to global science and technology.

Publications

Ahmad Kamandi | Optimization | Best Researcher Award

Dr. Ahmad Kamandi | Optimization | Best Researcher Award

Ahmad Kamandi is an accomplished researcher in applied mathematics, specializing in optimization algorithms and numerical analysis. He is currently affiliated with the Department of Mathematics at the University of Science and Technology of Mazandaran, Iran. His work focuses on developing novel algorithms for solving nonlinear equations, variational inequalities, and optimization problems. With numerous publications in high-impact journals, Kamandi has significantly contributed to computational mathematics and machine learning applications. His research interests include trust-region methods, projection-based algorithms, and support vector machines. Over the years, he has collaborated with leading researchers to advance mathematical optimization techniques. Kamandi’s expertise extends to signal processing, image retrieval, and deep learning applications. His academic excellence is reflected in his outstanding rankings and awards during his undergraduate and graduate studies. He actively contributes to mathematical research and continues to push the boundaries of computational problem-solving. 📚🔢

Profile

Education 🎓

Ahmad Kamandi holds a Ph.D. in Applied Mathematics from Razi University, Kermanshah, Iran (2011-2015), where he developed modified trust-region methods for optimization under the supervision of Prof. Keyvan Amini. He earned his M.Sc. in Applied Mathematics from Sharif University of Technology, Tehran (2008-2011), focusing on Lagrangian methods for degenerate nonlinear programming, guided by Prof. Nezam Mahadadi Amiri. His academic journey began at Razi University, where he completed a B.Sc. in Applied Mathematics (2004-2008). His exceptional academic performance placed him at the top of his class in both undergraduate and Ph.D. programs. His expertise spans optimization algorithms, variational inequalities, and numerical methods, forming the foundation for his extensive research contributions. Kamandi’s education has equipped him with the skills necessary to develop innovative solutions for complex mathematical and computational problems. 📖

Research Interests 🔬

Ahmad Kamandi’s research centers on optimization algorithms, numerical methods, and computational mathematics. His expertise includes trust-region methods, inertial projection-based algorithms, and variational inequalities, with applications in signal processing, image retrieval, and machine learning. His work extends to support vector machines, hyper-parameter tuning, and monotone equation solving, impacting fields like AI and engineering. His notable contributions include developing novel inertial proximal algorithms and hybrid conjugate gradient methods. His recent studies focus on binary classification, hierarchical variational inequalities, and the intersection of optimization and deep learning. With numerous publications in leading journals, Kamandi continuously refines mathematical models for real-world applications. His research has practical implications in data science, financial modeling, and computational engineering, bridging the gap between theoretical mathematics and applied problem-solving. His contributions drive innovation in solving large-scale mathematical problems efficiently. 📊

Awards & Recognitions 🏅

Ahmad Kamandi has received multiple academic accolades, highlighting his excellence in mathematics. In 2012, he secured First Place in the Ph.D. Program at Razi University with an outstanding GPA of 19.26/20. In 2010, he was ranked Second in the M.Sc. Program at Sharif University of Technology with a GPA of 18.92/20. His academic brilliance was evident early on when he ranked 73rd out of 10,763 candidates in Iran’s Nationwide Master’s Examination (2008). Additionally, he achieved First Place in the B.Sc. Program at Razi University with a GPA of 16.85/20. These awards underscore his dedication to mathematical research and his ability to excel in rigorous academic environments. His outstanding performance has positioned him as a leading expert in applied mathematics, contributing to the advancement of optimization and computational methods. 🏅🎖️

Publications 📚

  • A novel projection-based method for monotone equations with Aitken Δ2 acceleration and its application to sparse signal restoration

    Applied Numerical Mathematics
    2025-07 | Journal article
    CONTRIBUTORS: Ahmad Kamandi
  • Relaxed-inertial derivative-free algorithm for systems of nonlinear pseudo-monotone equations

    Computational and Applied Mathematics
    2024-06 | Journal article
    CONTRIBUTORS: Abdulkarim Hassan Ibrahim; Sanja Rapajić; Ahmad Kamandi; Poom Kumam; Zoltan Papp
  • A NOVEL ALGORITHM FOR APPROXIMATING COMMON SOLUTION OF A SYSTEM OF MONOTONE INCLUSION PROBLEMS AND COMMON FIXED POINT PROBLEM

    Journal of Industrial and Management Optimization
    2023 | Journal article

    EID:

    2-s2.0-85140006988

    Part of ISSN: 1553166X 15475816
    CONTRIBUTORS: Eslamian, M.; Kamandi, A.