Teaching Statement

Teaching philosophy

I believe the most durable learning happens when students build things, break them, and understand why. My teaching philosophy is centred on three convictions: learning through making, disciplinary integration, and radical accessibility.

Learning through making. I am a hands-on educator. In every course I teach, students produce artefacts — parametric models, simulation outputs, trained ML models, live dashboards, or physical prototypes. Abstract concepts become concrete through construction, not repetition. I lead by example: I code alongside students, debug in real time in front of the class, and treat the studio or lab as a shared workspace rather than a lecture theatre. This is not a preference — it is a pedagogical conviction grounded in evidence that active learning produces deeper retention and stronger problem-solving skills.

Disciplinary integration. The most important problems in the built environment sit at the intersection of fields. Thermal comfort is simultaneously a physics problem, a behavioural-science question, a data-engineering challenge, and a design constraint. I teach students to hold multiple disciplinary lenses simultaneously — combining humanistic insight with quantitative rigour, engineering analysis with design sensibility, and physical simulation with AI. This is the professional reality of working on complex buildings and cities in the 21st century.

Radical accessibility. Knowledge should reach as many people as possible. Through the open edX MOOC Data Science for Construction, Architecture and Engineering — which I co-developed and supported at NUS — I have helped bring computational methods to global learners across multiple cohorts. This experience has sharpened my ability to explain complex technical ideas clearly, patiently, and across cultural and linguistic contexts — a skill I bring into every classroom.

Teaching and supervision experience

Continuous, formal involvement in university teaching and student supervision since 2009 — spanning classroom delivery, curriculum authorship, project assessment, and graduate mentorship across five institutions in two countries.

Misr Higher Institute for Engineering and Technology (MET), Mansoura, Egypt (2009–2011). Teaching faculty in architectural engineering. Delivered studio and lecture courses to undergraduate cohorts immediately after my own undergraduate degree, building the foundation of pedagogical practice that would carry through every subsequent role.

Kafrelsheikh University, Egypt (2011–2018). Teaching Assistant, then promoted to Assistant Lecturer. Delivered lectures, studio instruction, and assessments to cohorts of 60+ students per semester in architectural design, computational design, working drawings, shadow and perspective, and graduation projects. Supervised undergraduate graduation projects from proposal through final defence. Authored the full department curriculum in computer applications and computational design — a programme that remained in institutional use after my departure.

The American University in Cairo (2017–2018). Teaching Assistant and Research Assistant. Supported studio delivery and formal student assessment; contributed to applied built-environment research supervised by faculty.

National University of Singapore — BUDS Lab (2018–2022). Research Associate with active teaching-support responsibilities. Evaluated student projects, assisted in graduate research assessment, and mentored undergraduate and MSc students through final-year research projects — several of which resulted in conference paper publications.

National University of Singapore — Urban Analytics Lab (2023–2025). Postdoctoral Research Fellow. Formally co-supervised 5+ MSc and PhD students on GNN, GeoAI, and street-view imagery dissertations. Provided day-to-day research direction, writing feedback, and methodological guidance, and contributed to thesis assessment panels.

NUS edX MOOC (2020–2022). Co-developed and supported delivery of Data Science for Construction, Architecture and Engineering to a global audience across multiple cohorts, including content design and learner assessment.

Courses I am prepared to teach

I am immediately ready to develop and deliver:

  • Digital Twins for the Built Environment — from BIM integration and IoT data pipelines to live simulation and agentic systems.
  • AI and Machine Learning for Architecture and Urban Design — GNNs, reinforcement learning, computer vision, and generative AI applied to design problems.
  • Building Performance Simulation — energy, thermal comfort, daylighting, and CFD using industry-standard tools (EnergyPlus, OpenFOAM, ANSYS, Radiance).
  • Computational and Parametric Design — Grasshopper, Python, and algorithmic thinking for architectural problem-solving.
  • Data Science for Construction and Facilities Management — IoT analytics, predictive maintenance, and data-driven decision support.
  • Indoor Environmental Quality (IEQ) and Occupant Wellbeing — thermal comfort, air quality, acoustic and visual comfort; measurement and modelling.

Assessment and student development

I design assessments around real problems with real outputs: building-simulation reports, trained models evaluated on actual datasets, design proposals justified through quantitative performance analysis, and final projects co-defined with industry partners wherever possible. In graduate supervision I am a demanding but collaborative mentor. I expect students to own their research questions, but I invest heavily in developing their writing, presentation, and critical-thinking skills alongside their technical capabilities. My goal is not to produce assistants — it is to produce independent researchers who go on to lead their own groups.

I am committed to bilingual instruction. Teaching in Arabic where appropriate — particularly for foundational concepts — dramatically lowers the cognitive barrier for students whose first language is Arabic, an advantage I can offer that few internationally trained faculty can match.