Mr. Şüheda Semih AÇMALI | Parasite Detection Award | Best Researcher Award
Mr. Şüheda Semih AÇMALI, Zonguldak Bulent Ecevit University, Turkey
Şüheda Semih Açmalı is a distinguished lecturer specializing in computer technologies. 📚 She holds a Ph.D. in Engineering from Karabük University, where her research focused on swarm intelligence methods and Apache Spark for data clustering. 🎓 With academic positions at both Zonguldak Bülent Ecevit University and Yüksek İhtisas University, Açmalı has contributed significantly to the field. Her notable works include research on energy-efficient deep learning for parasite detection and developing geocomputation tools for landslide susceptibility. 🌍 Currently, she is active in advanced intelligent systems and has a passion for integrating green AI concepts. 📧
Publication profile
Educational Background 🎓
In 2021, Şüheda Semih Açmalı obtained her doctoral degree from the Institute of Graduate Programs at Karabük University. Her doctoral research, under the guidance of Yasin Ortakcı, focused on the implementation of swarm intelligence methods supported by Apache Spark for data clustering. This innovative work represents a significant contribution to the field of data science, highlighting the potential of intelligent algorithms to enhance data processing and analysis capabilities.Prior to her Ph.D., Açmalı completed her master’s degree at the same institution. Her master’s thesis, also supervised by Yasin Ortakcı, was submitted in April 2021. It continued the theme of leveraging advanced computational techniques, specifically exploring the applications of swarm intelligence for data clustering tasks. she earned her bachelor’s degree from the Faculty of Engineering at Selçuk University. This foundational period of her education laid the groundwork for her subsequent research and academic endeavors, providing her with the essential knowledge and skills in engineering and computer science.
Research Focus
Publication Top Notes
Developing comprehensive geocomputation tools for landslide susceptibility mapping: LSM tool pack
Clustering Performance Analysis of Traditional and New-Generation Meta-Heuristic Algorithms
SÜRÜ ZEKASI YÖNTEMLERİ İLE APACHE SPARK DESTEKLİ VERİ KÜMELEME