Dr. Bahadir Kopcasiz | Computational Methods | Best Researcher Award

Dr. Bahadir Kopcasiz | Computational Methods | Best Researcher Award

Assistant Professor | Istanbul Gelisim University | Turkey

Dr. Bahadir Kopcasiz is an accomplished academic whose expertise centers on Computational Methods, with strong emphasis on nonlinear partial differential equations, soliton theory, symbolic and semi-analytical analysis, and advanced mathematical modeling. He earned his Ph.D. in Mathematics from Bursa Uludag University, preceded by a Master’s in Mathematics from Yeditepe University and a Bachelor’s from Karadeniz Technical University, building a solid foundation for his contributions in Computational Methods. Currently serving as an Assistant Professor at Istanbul Gelisim University, he actively teaches courses such as Differential Equations, Statistics, Probability, and Numerical Analysis, integrating Computational Methods into both undergraduate and graduate programs. His research primarily focuses on soliton solutions in nonlinear Schrödinger-type systems, dynamical structures in quantum physics, and the development of innovative Computational Methods to study complex dynamical systems, with numerous publications in high-impact journals including Archives of Computational Methods in Engineering, Nonlinear Dynamics, and Symmetry. He has also presented extensively at international conferences, showcasing advancements in Computational Methods for applied physics and engineering. Among his recognitions, he received the Best Researcher Award at the International Research Awards on Composite Materials and academic incentive awards from Istanbul Gelisim University, which highlight his outstanding scholarly contributions in Computational Methods. His research skills are distinguished by mastery of symbolic computation, semi-analytical modeling, and integration of Computational Methods with machine learning for dynamic system optimization, as evidenced by his involvement in national projects. In conclusion, Dr. Bahadir Kopcasiz exemplifies excellence in academia through his dedication to advancing Computational Methods, innovative problem-solving, impactful publications, and mentorship, establishing himself as a valuable contributor to mathematics, physics, and engineering research. His Google Scholar citations 337, h-index 12, i10-index 14, showcasing measurable research impact.

Profiles: Google Scholar | ORCID

Featured Publications

1. Kopçasız, B., & Yaşar, E. (2022). The investigation of unique optical soliton solutions for dual-mode nonlinear Schrödinger’s equation with new mechanisms. Journal of Optics, 1–15.

2. Kopçasız, B., & Yaşar, E. (2022). Novel exact solutions and bifurcation analysis to dual-mode nonlinear Schrödinger equation. Journal of Ocean Engineering and Science.

3. Kopçasız, B., & Yaşar, E. (2024). Dual-mode nonlinear Schrödinger equation (DMNLSE): Lie group analysis, group invariant solutions, and conservation laws. International Journal of Modern Physics B, 38(02), 2450020.

4. Kopçasız, B. (2024). Qualitative analysis and optical soliton solutions galore: Scrutinizing the (2+1)-dimensional complex modified Korteweg–de Vries system. Nonlinear Dynamics, 112(23), 21321–21341.

5. Kopçasız, B., Seadawy, A. R., & Yaşar, E. (2022). Highly dispersive optical soliton molecules to dual-mode nonlinear Schrödinger wave equation in cubic law media. Optical and Quantum Electronics, 54(3), 194.

Mr. Demet Yeşilbaş | Biomedical Engineer | Best Researcher Award

Mr. Demet Yeşilbaş | Biomedical Engineer | Best Researcher Award

Mr. Demet Yeşilbaş, Erciyes University, Turkey

Demet Yeşilbaş is a dedicated PhD candidate in Biomedical Engineering at Erciyes University, Turkey. With a robust educational background and hands-on experience in neuroscience, particularly focusing on Internet Gaming Disorder, she excels in the recording and processing of EEG and fNIRS data. Demet has contributed to significant research projects, including multimodal analysis of brain functions in young adults with internet game addiction and the evaluation of daily internet usage effects on cognitive tasks. She has also honed her skills in machine learning during her Erasmus internship at WWU Münster. Proficient in MATLAB and various neuroscience toolboxes, Demet aims to further her contributions to the field of biomedical engineering and neuroscience.

PROFILE

Scopus

Education

PhD in Biomedical Engineering (2020-present): Erciyes University, Turkey. Recipient of the 100/2000 Doctorate Programme Scholarship by the Council of Higher Education (CoHE) & TUBITAK 2211A Scholarship Programme.

Bachelor of Engineering (2015-2019): Erciyes University, Turkey. Completed an Erasmus Exchange Program at Koszalin University, Poland (2018-2019).

Research Interest 

Demet Yeşilbaş’s research interests are deeply rooted in neuroscience, with a particular focus on Internet Gaming Disorder. She specializes in using advanced techniques such as EEG (Electroencephalography) and fNIRS (Functional Near-Infrared Spectroscopy) to explore brain functions. Her work with event-related potentials has furthered the understanding of cognitive processes in individuals with varying internet usage patterns. Additionally, Demet employs machine learning and deep learning methodologies to analyze complex neurological data, aiming to develop innovative solutions and insights into mental health and cognitive behavior. Her multidisciplinary approach integrates cutting-edge technology with neuroscience, contributing significantly to the field.

Professional Experience

Research Scholar, ERCIYES UNIVERSITY (2022-present): Leading a project supported by Tubitak ARDEB 1001 Research Projects Programme titled “Analysis of Brain Functions of Young Adults with Internet Game Addiction by Electroencephalography, Event-Related Potentials and Functional Near-Infrared Spectroscopy Signals: A Multimodal Approach.”

Researcher, ERCIYES UNIVERSITY (2023-present): Conducting research on “Evaluation of the Effects of Daily Internet Usage Time with Functional Near-Infrared Spectroscopy, Electroencephalography, and Event-Related Potential Signals during Different Cognitive Tasks.”

Erasmus Intern, WWU MÜNSTER INSTITUTE FOR BIOMAGNETISM AND BIOSIGNAL ANALYSIS (2021-2022): Worked on detecting spikes in EEG data and received machine learning education.

TOP NOTABLE PUBLICATIONS

Dr. Soumitra Nath | Biotechnology | Best Researcher Award

Dr. Soumitra Nath | Biotechnology | Best Researcher Award

Dr. Soumitra Nath, Gurucharan College, Silchar, India

Dr. Soumitra Nath is a distinguished researcher and academic in the field of biotechnology and bioinformatics. He completed his Ph.D. in Microbiology from Assam University, Silchar, with a focus on the role of cadmium and lead tolerant bacteria in sustainable rice cultivation. Dr. Nath has a comprehensive educational background, including a B.Sc. in Zoology, Biotechnology, and Chemistry, and an M.Sc. in Biotechnology. His expertise is further augmented by advanced and postgraduate diplomas in biotechnology and bioinformatics. Dr. Nath has been recognized with a prestigious Summer Research Fellowship and has substantial experience in computer applications and programming languages. He is currently involved in research and academic activities, contributing significantly to his field.

PROFILE

Scopus

Orcid

Education

Dr. Soumitra Nath completed his CBSE 10th standard education from Kendriya Vidyalaya, Panchgram in 2003, achieving a first division with a percentage of 73.8%. His subjects included English, Hindi, Science, Social Studies, and Mathematics. In 2005, he completed his CBSE 12th standard from the same school, also in the first division, with a percentage of 61.4%. His subjects were Physics, Chemistry, Mathematics, Biology, and English.

Dr. Nath pursued his Bachelor of Science (B.Sc.) at Karimganj College, affiliated with Assam University, Silchar. He graduated in 2008 with first-class honors in Zoology, along with studies in Biotechnology and Chemistry, securing a percentage of 65.25%. Following this, he earned his Master of Science (M.Sc.) in Biotechnology from the Department of Biotechnology, Assam University, Silchar, in 2010. He graduated with first-class honors and ranked second in his class, achieving a percentage of 76.75%.

Dr. Nath then completed his Pre-Ph.D. coursework at the School of Life Sciences, Assam University, Silchar, with a CGPA of 7.05. This coursework was completed in 2011 and he was awarded his Ph.D. in 2014. Additionally, Dr. Nath holds an Advanced Diploma in Biotechnology, which he earned from Karimganj College, Assam University, Silchar in 2009 with a first division and a percentage of 60.14%. He also completed a Postgraduate Diploma in Bioinformatics from the Department of Life Science, Assam University, Silchar in 2010, securing a first division with a percentage of 67.2%.

Professional Experience

Dr. Soumitra Nath completed his Ph.D. in Microbiology from Assam University, Silchar, with a thesis titled “Role of cadmium and lead tolerant bacteria in sustainable cultivation of rice,” awarded on 22nd September 2014 under the supervision of Dr. Indu Sharma. Dr. Nath has a robust academic foundation and practical experience in the field of biotechnology and bioinformatics. He was awarded the Summer Research Fellowship in 2017, jointly by three national science academies of India, and conducted research at the National Institute of Immunology, New Delhi, from 18th May 2017 to 15th July 2017.

Research Interest

Dr. Soumitra Nath’s research interests primarily lie in environmental microbiology, specifically in the role of heavy metal-tolerant bacteria in sustainable agriculture. His Ph.D. thesis focused on “Role of cadmium and lead tolerant bacteria in sustainable cultivation of rice.” He is also interested in biotechnology applications in agriculture and bioinformatics.

NOTABLE PUBLICATIONS

Advancements in food quality monitoring: integrating biosensors for precision detection
Algal-based membrane bioreactors for effective removal of hazardous and toxic contaminants: A comprehensive review
Microbial fuel cell: A state-of-the-art and revolutionizing technology for efficient energy recovery