Face Recognition on Robot
Integrated a face recognition model with an age & gender estimation model into a single mobile robot, running real-time inference on a vision pipeline.
Hello, I'm
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I graduated first in my class from the Computer Engineering Department of Manisa Celal Bayar University. As a Senior Software Specialist at Vestel and an AI & Data Science enthusiast, I build machine learning, computer vision and data-driven systems — turning large, messy data into models and products that make decisions. I work fast, take ownership, and care about doing things with diligence and consistency.
Part of the Big Data & AI team, designing and shipping data-driven software — from large-scale data pipelines to machine-learning and analytics services that support production decision-making. Focused on building reliable, scalable systems and bringing AI capabilities into real products.
Worked on the AI subsystems of autonomous robots using the Robot Operating System (ROS). Focused on LiDAR mapping, Hector SLAM and SLAM algorithms. For my graduation project I integrated a face recognition model together with an age/gender estimation model into a single robot.
Contributed to a project under the Presidency. Studied network connections and IEEE standards and delivered presentations on the OSI layers and the differences between IPv4 and IPv6.
Worked in the IT department on company servers and internal applications, completing the internship with presentations on C# and SQL applications and on networking.
Integrated a face recognition model with an age & gender estimation model into a single mobile robot, running real-time inference on a vision pipeline.
Built an indoor mapping and localization pipeline for an autonomous vehicle using LiDAR data and the Hector SLAM algorithm on ROS.
Developed image-processing routines for an industrial setting, applying classical and deep-learning vision techniques to automated inspection.
A Java application project delivering campus bell/ringtone scheduling, built during university coursework.
Processed Brazil's Olist e-commerce dataset (100k+ orders, 2016–2018) through a Spark & Airflow data pipeline on AWS S3 — building ETL DAGs and analytics over multi-marketplace order data.
View on GitHubBuilt a convolutional neural network to classify biscuits by shape (round / rectangular) and type (cocoa / milky), running real-time image classification through an OpenCV pipeline.
View on GitHubA Python tool that analyzes text and PDF files — computing word and character statistics, visualizing the results and running sentiment analysis.
View on GitHubOpen to collaborations and conversations around Big Data, AI and machine learning. The fastest way to reach me is by email.
yunuseysr@gmail.com