Ahmet Arslan
Associate Professor
Eskisehir, Eskişehir, Turkey
Summary
👤
Senior🎓
Top SchoolAhmet Arslan is an Associate Professor and senior search architect with 12 years of experience specializing in Apache Lucene/Solr and information retrieval. He combines academic leadership at Eskişehir Technical University with practical open-source contributions—most notably enhancements to the widely used Anserini Lucene toolkit that improved indexing, search utilities, and TREC submission workflows. His PhD research on selective term-weighting and a strong teaching record in Java and Spring Boot inform a pragmatic approach to both research and software engineering. Known for integrating tooling into coursework (e.g., GitHub Classroom and automated grading), he brings a rare blend of reproducible IR research, production-focused engineering, and educational innovation.
12 years of coding experience
17 years of employment as a software developer
Bachelor of Science (B.S.), Computer Science, 3.36/4.0, Bachelor of Science (B.S.), Computer Science, 3.36/4.0 at Anadolu UniversityDoctor of Philosophy (PhD), Selective Term-Weighting for Information Retrieval, 3.69/4.0, Doctor of Philosophy (PhD), Selective Term-Weighting for Information Retrieval, 3.69/4.0 at Anadolu Üniversitesi
English, Turkish
Github Skills (4)
lucene10
java10
javas10
information-retrieval10
Programming languages (4)
Github contributions (5)
castorini/anserini
Oct 2015 - Dec 2015
Anserini is a Lucene toolkit for reproducible information retrieval research
Role in this project:
Back-end Developer
Back-end DeveloperContributions:28 commits, 1 PR, 36 comments in 2 months
Contributions summary:Ahmet primarily focused on enhancing the Anserini information retrieval toolkit. Their contributions included adding code for ClueWeb09B baselines, implementing search time utilities, and refactoring the command-line argument parsing. They also made changes to indexing and search functionalities, including modifying the handling of topic files and TREC submission file formatting. These efforts suggest a focus on improving the system's performance and usability for information retrieval tasks.
reproducibleretrievalluceneinformation-retrievaljava
iorixxx/Kemik
May 2018 - Feb 2021
Contributions:79 commits, 18 pushes in 2 years 9 months
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