LexismAI
Legal AIOne workspace.
The whole legal workflow.
An AI-powered workspace for Turkish legal professionals, bringing sourced research, document drafting, and case and office management together.
- Legal research
- Document AI
- Office management
Passionate about the intersection of machine learning and healthcare
I specialise in machine learning, signal processing, and biomedical data analysis, with hands-on experience in comprehensive data processing and visualisation using NumPy, Pandas, SciPy, Matplotlib, and Seaborn.
Currently focused on developing interpretable ML models for early detection of Alzheimer's disease and dementia using EEG data by combining feature extraction, signal analysis, and explainable AI techniques.
Building an AI-powered legal tech platform for Turkish law professionals
BSc at Kadir Has University, Istanbul
BCI & EEG feature selection research at Kadir Has University
Turning ideas into products for legal work, AI security, hospitality, and medication safety.
One workspace.
The whole legal workflow.
An AI-powered workspace for Turkish legal professionals, bringing sourced research, document drafting, and case and office management together.
A safer boundary
between AI and your data.
A local-first security gateway that checks AI inputs, outputs, and tool actions against enterprise policies. Currently a working prototype under evaluation.
A restaurant's character.
On every screen.
Restaurant websites, QR menus, and reservation requests in one dashboard. A digital experience shaped around each restaurant's own identity.
Medication safety.
An explanation behind every alert.
An early-stage clinical decision support prototype matching medication safety rules from official product documents to patient profiles, with source-linked explanations. Built on a limited sample dataset; not yet clinically validated.
Technologies and tools I work with daily
My academic journey and learning path
Computer Engineering (Bachelor's Degree)
Sep 2022 to Jul 2027Core studies in Logic Circuits, C/C++ Programming, Data Structures and Algorithms, and Electrical Engineering fundamentals. Advanced focus on machine learning, computer vision, and biomedical data analysis.
Management Information Systems (Double Major)
Feb 2025 to PresentSpecialisation in web analytics, social media analytics, Python programming, data science, and linear algebra, aimed at developing cross-disciplinary skills in business analytics and information systems management.
Where I've applied and grown my skills
Computer Engineering Intern
Jun 2026 to PresentWorking on site in Gölbaşı, Ankara as a Computer Engineering Intern.
Co-founder
May 2026 to PresentCo-founding an AI-powered legal technology platform, building tools for case research, legislation tracking, document generation, and office management for Turkish law professionals.
Computer Vision Software Engineer
May 2026 to PresentDeveloping computer vision and image detection algorithms for an unmanned ground vehicle (UGV) as part of the university's Teknofest project team.
Research Intern at the BCI Lab
Feb 2025 to PresentDeveloping interpretable feature selection and extraction algorithms for asynchronous Brain-Computer Interface (BCI) systems, with a focus on EEG signal analysis for neurological disorder detection.
Software Engineer
May 2024 to Dec 2025Worked on computer vision and signal processing projects in the drone technology space. Developed real-time AI pipelines and integrated ML models into production systems.
RLHF Expert · Contract
Aug 2023 to Dec 2025Contributed to RLHF model training across mathematics, generalised reasoning, Turkish language, and coding domains, providing expert feedback to improve LLM performance. Remote.
Awards, scholarships, and certifications
Completed three professional certificate programmes from HarvardX covering Python, Data Science, and Artificial Intelligence.
Finalist in the TEKNOFEST Smart Wi-Fi Coverage competition. Awarded the Best Team Spirit prize.
Awarded the prestigious White Doves Scholarship by Kadir Has University, which is granted to exceptional students.