Kaan Yarali
About Kaan Yarali
Kaan Yarali is a Machine Learning Engineer with a strong academic background in Electrical Engineering and Computer Science. He has experience working at notable institutions such as Microsoft and Massachusetts General Hospital, and currently contributes to TAZI AI Systems in New York City.
Current Role at TAZI AI Systems
Kaan Yarali currently serves as a Machine Learning Engineer at TAZI AI Systems, a position he has held since 2023. In this role, he focuses on implementing Generative AI solutions, including advanced topic identification techniques. His contributions have significantly reduced the workload of customer call centers by one-eighth, showcasing his ability to enhance operational efficiency through innovative technology.
Previous Experience at Microsoft
Prior to his current role, Kaan Yarali interned at Microsoft in 2017 for three months in Ankara, Turkey. This internship provided him with valuable experience in the tech industry, allowing him to develop foundational skills in machine learning and software development.
Research Internship at Massachusetts General Hospital
In 2018, Kaan Yarali worked as a Research Intern at Massachusetts General Hospital in the Center for Engineering, BioMEMS & Nanoscale Engineering Department. This three-month internship in Boston, Massachusetts, allowed him to gain hands-on experience in a research environment, contributing to projects that intersect engineering and biomedical applications.
Education and Academic Background
Kaan Yarali holds a Master of Science (MS) in Electrical Engineering from Columbia University, where he studied from 2020 to 2022. He also earned a Bachelor of Science (BS) in Electrical Engineering and Computer Science (Dual Degree) from Sabanci University, completing his studies from 2015 to 2020. Additionally, he graduated with a High School Diploma from TED Ankara Koleji in 2015.
Research Assistant Experience at Columbia University
From 2021 to 2023, Kaan Yarali worked as a Research Assistant at Columbia University in the City of New York. During this two-year tenure, he contributed to various research projects, further developing his expertise in machine learning and its applications in real-world scenarios.
Achievements in Machine Learning Solutions
Kaan Yarali has developed machine learning solutions that enhance fraud detection rates and reduce audit time for fintech and insurance companies. His work has generated over $300,000 in business value annually, demonstrating his capability to apply machine learning techniques to solve complex business challenges.