Assoc. Prof. Dr. Emine Baş | Optimization Algorithms | Best Researcher Award
Author at Konya Technical University, Turkey📖
Dr. Emine Baş is a dedicated researcher and academic specializing in optimization algorithms, artificial intelligence, data mining, and machine learning. With a strong foundation in computer engineering and extensive experience in higher education, she has significantly contributed to both academia and applied research.
Profile
Education Background🎓
- Bachelor’s Degree (2006): Computer Engineering, Selçuk University
- Master’s Degree (2013): Computer Engineering, Selçuk University (Thesis: RFID System Implementation and Application)
- Doctorate (2020): Computer Engineering, Konya Technical University (Thesis: Performance Improvements in Continuous and Discrete Optimization Problems Using the Social Spider Algorithm)
Professional Experience🌱
Dr. Baş has been an instructor at Selçuk University since 2007. Initially appointed to Huğlu Vocational School, she transitioned to Kulu Vocational School in 2015, where she continues to educate and mentor students. She also holds administrative roles, such as Deputy Head of the Computer Technologies Department and ECTS Coordinator.
Dr. Baş’s research focuses on swarm intelligence, heuristic algorithms, continuous and discrete optimization problems, artificial intelligence, database systems, machine learning, and big data analytics. She leverages these technologies to address complex optimization challenges and enhance data-driven decision-making.
Author Metrics
Dr. Baş has published extensively in high-impact journals such as Soft Computing and Expert Systems with Applications. Her work has received numerous citations, demonstrating her influence in fields like optimization and algorithm development. Her notable publications include advancements in binary social spider algorithms and their applications in feature selection and optimization tasks.
1. An Efficient Binary Social Spider Algorithm for Feature Selection Problem
- Authors: Emine Baş, E. Ülker
- Journal: Expert Systems with Applications, Vol. 146, Article 113185
- Publication Year: 2020
- Citations: 63
- Summary: This paper introduces a binary social spider algorithm (SSA) tailored for feature selection problems. It demonstrates improved efficiency in selecting relevant features for machine learning tasks while maintaining solution quality.
2. A Binary Social Spider Algorithm for Uncapacitated Facility Location Problem
- Authors: Emine Baş, E. Ülker
- Journal: Expert Systems with Applications, Vol. 161, Article 113618
- Publication Year: 2020
- Citations: 51
- Summary: This study applies the binary SSA to the uncapacitated facility location problem, achieving better performance in terms of cost and computational efficiency compared to traditional optimization methods.
3. Binary Aquila Optimizer for 0–1 Knapsack Problems
- Author: Emine Baş
- Journal: Engineering Applications of Artificial Intelligence, Vol. 118, Article 105592
- Publication Year: 2023
- Citations: 28
- Summary: This paper presents a novel binary variant of the Aquila optimizer, addressing the 0–1 knapsack problem with improved accuracy and computational efficiency.
4. A Binary Social Spider Algorithm for Continuous Optimization Task
- Authors: Emine Baş, E. Ülker
- Journal: Soft Computing, Vol. 24(17), pp. 12953–12979
- Publication Year: 2020
- Citations: 26
- Summary: The research adapts the SSA for continuous optimization tasks, showcasing its potential to solve complex mathematical problems with higher precision.
5. Improved Social Spider Algorithm for Large-Scale Optimization
- Authors: Emine Baş, E. Ülker
- Journal: Artificial Intelligence Review, Vol. 54(5), pp. 3539–3574
- Publication Year: 2021
- Citations: 22
- Summary: This paper enhances the SSA for large-scale optimization problems, improving scalability and convergence rates, particularly for applications with high-dimensional datasets.
Conclusion
Dr. Emine Baş exemplifies excellence in research, academic mentorship, and innovation. Her impactful contributions to optimization algorithms, artificial intelligence, and machine learning position her as a deserving candidate for the Best Researcher Award.
With a strong academic foundation, proven research capabilities, and a focus on solving complex real-world problems, she has laid a robust groundwork for continued contributions to the field. Addressing areas such as broader collaborations and industrial engagement would further elevate her profile as a global leader in optimization and AI.