Hi! I am a PhD student at ETH Zurich and currently a visiting researcher at Stanford. I research at the intersection of architecture, sustainability, and artificial intelligence. Below are some of my past works. Feel free to reach out if you find anything interesting!

​Segment for Solar Facades (S4S) is a deep learning–powered tool that analyzes building façade images to identify suitable areas for photovoltaic installation, integrating solar irradiance data to estimate energy yields with architectural detail.​

This review analyzes trends and applications of AI methods—including Machine Learning, Deep Learning, and Computer Vision—in facade research, highlighting current uses, limitations, and future potential in architectural, environmental, and structural contexts.

This study investigates how building-integrated photovoltaic (BIPV) façades affect outdoor thermal comfort across four urban block typologies in Zurich, revealing that urban form and climate change have a far greater impact than BIPV installation.

This work presents a method that combines open data sources and deep learning to extract detailed architectural façade features for more accurate estimation of BIPV energy potential.

This study introduces a deep learning–based method using GANs and street-level imagery to accurately estimate BIPV façade surface utilization, showing significant discrepancies with existing tools and emphasizing its potential to inform better solar energy planning and policy.

This study uses a parametric simulation approach to assess how varying levels of BIPV façade deployment influence pedestrian-level outdoor thermal comfort across different urban settings, highlighting that factors like ground material and street width have a greater impact than BIPV itself.

This study explores how different urban street network patterns influence the BIPV generation capacity of buildings, showing that irregular urban layouts enhance façade PV potential while roof PV potential remains largely unaffected by morphology.

This study enhances urban building energy models (UBEM) by integrating open data on occupancy and residential layouts, demonstrating that data-rich models significantly improve the accuracy of energy use and thermal comfort..

This thesis proposes a machine learning–based, data-driven method to predict BIPV generation potential on façades and roofs in diverse urban contexts, demonstrating high accuracy and highlighting the influence of urban morphology on solar performance.

This study uses data-driven decision tree models to analyze how varying occupant thermal preferences impact comfort and energy performance in naturally ventilated classrooms, revealing key tradeoffs between occupant well-being and resource consumption in educational buildings.

This study develops artificial neural network models to accurately predict heating demand, indoor overheating, and CO₂ levels in naturally ventilated classrooms, offering a fast, data-driven alternative to traditional simulations for evaluating classroom design and retrofit scenarios.

A hands-on workshop exploring the relationship between urban design and climate using Ladybug Tools

This work explores the interaction between pedestrians and vehicles in urban spaces using geospatial data.

This project explores the design of a flexible house that can be optimized for changing climate conditions to minimize the energy demand.

This work explores the intersection of walking and data within urban environments via mapping the observations related to pedestrian movement, urban form, and environmental factors.

​Express Izmir is an architectural project that transforms a historic industrial site in Izmir into a media-focused campus, integrating preserved heritage structures, reimagined waterfronts, and flexible public spaces to foster creative expression and connect with the city's archaeological landmarks.

Arts & Crafts Centre is an architectural project that envisions a community-oriented space promoting traditional craftsmanship as an alternative to industrial production, integrated into Ankara's historic and natural setting.

Scientific Research Centre is an architectural project that envisions a cluster of research buildings and a library in Ankara's steppes, designed around interconnected courtyards to foster collaboration and reflect the organic growth patterns.

The Watchouse is an architectural project, designed as a minimal living space elevated above ground level, featuring a central vertical circulation core for 360° observation and three distinct frames catering to various spatial needs, with rooftop areas serving as open observation spaces at different levels.