Research

This project utilizes UAVs for building envelope audits, incorporating thermal, LiDAR, RGB, and hyperspectral sensors. Tools like Metashape, Revit, EnergyPlus, and custom Python/C++ code enable 3D modeling, analysis, visualization, simulation and energy performance evaluation.

This project optimizes façade-integrated microalgae photobioreactors to enhance building performance, reduce energy demand, improve thermal comfort, and generate biomass and thermal energy, using multiple optimization techniques, shading analysis, and hourly thermal simulations.

This project develops and validates new trigonometric shading models for diverse urban environments, outperforming existing techniques and showing that free-form façades and south-facing orientations significantly enhance solar radiation capture compared to flat façades.

This project optimizes thermally active building systems integrating solar technologies, and multiple heat sources, achieving energy savings, reduced costs and emissions, and enhanced thermal comfort, demonstrating their potential for sustainable performance across diverse climate conditions.

This project integrates an optimization method and energy flow model to reduce PV temperature and boost power generation, achieving significant cost savings, and rapid payback by optimizing water flow, pipe spacing, and tilt angle.

This project develops an autonomous façade heat loss inspection method using thermal imaging, YOLOv7 deep learning, and heat flow modeling, accurately detecting anomalies, quantifying heat loss, and identifying critical areas, enhancing monitoring in cold-climate buildings.

This project develops a deep learning method to detect snow coverage on PV panels, improving real-time energy loss estimation, achieving high prediction accuracy, and enabling timely snow removal to maximize solar energy conversion in cold regions.

This project applies Neural Networks to optimize building-integrated photobioreactors, significantly reducing computational time, enhancing efficiency, and addressing limitations of traditional meta-heuristic methods while achieving optimal bioenergy generation throughout the year.

This project investigates microalgae growth on ceramic-based porous substrate bioreactors, analyzing the effects of surface texture, nutrient availability, and environmental exposure using vegetation indices, color kinetics, and microscopy to optimize cultivation efficiency.

This project models microalgae photobioreactors integrated into double-skin façades, using kinetics, shading analysis, and optimization to maximize biomass productivity, validate performance with RGB monitoring, and demonstrate adaptability across diverse cold-climate conditions.

This project develops a parametric workflow to generate 3D grid-based façades, integrating photovoltaic panels and vision glass, and evaluates their impact on daylighting and renewable energy production compared to conventional straight façades.

This project explores additive manufacturing for developing optimized structural joints, using small-scale prototypes and robotic Wire Arc Additive Manufacturing to test integrity, efficiency, and aesthetics, enabling innovative large-scale architectural designs with improved accuracy and manufacturability.

This project evaluates a novel air filtration technology for reducing PM2.5 concentrations in office environments, demonstrating its effectiveness under varying occupancy conditions and improving indoor air quality by enhancing particle removal through inelastic collisions.

This project optimizes building-integrated PV systems, analyzing building form, orientation, and shading effects, and develops mathematical models to enhance energy efficiency, achieve net-zero goals, and maximize solar energy performance through form and tilt optimization.

This project examines lighting design strategies and technologies in the Masdar Headquarters, optimizing daylighting and electric lighting systems, integrating advanced controls, and emphasizing human-centered design to achieve net-positive energy performance and sustainable indoor visual comfort.

This project examines the environmental and health impacts of synthetic materials, highlighting the limited testing of chemicals, their associated risks, and the need for sustainable design and manufacturing practices to minimize negative effects on humans and ecosystems.

This project uses Radiance-Matlab visualizations to optimize daylighting in offices, evaluating lighting indices, illuminance, and exposure duration, and analyzing the effects of façade orientation, seasons, glazing, and task conditions on visual comfort and circadian rhythm.

This project investigates visual discomfort at building entryways caused by abrupt daylight transitions, evaluating design features like trellises, overhangs, and fins, and assessing their impact on luminance ratios to improve occupant visual comfort during transitions.

This project develops a methodology to reduce urban carbon emissions while enhancing vibrancy, combining systematic documentation and parametric modeling to assess buildings’ performance across energy, carbon, water, and systems integration, enabling efficient auditing and improvement strategies.

This project enhances architectural pedagogy by developing methods for effective data visualization, helping students interpret complex, multi-layered datasets from site analysis, and enabling clearer understanding and application of design problems and patterns in their projects.

This project analyzes building geometry and façades to optimize renewable energy production, examining how surface-to-volume ratio, shading, orientation, and panel tilt influence heat gain and solar energy capture through conduction, convection, and radiation.