AI/ML · REGIONAL SCIENCE · SPATIAL analysis
Hello there!
I’m a Full Professor in Geography & Environmental Studies at TMU. I turn location data into decisions. My work blends GIS/AI, ML, remote sensing, and spatial econometrics to map regional and urban change, health & safety risks, and market dynamics. I build reproducible pipelines and mentor teams—transforming satellite imagery into policy-ready insights with clear, defensible findings and models for governments, decision-makers, and stakeholders. From pixel to policy.
Quick facts: Full Professor (TMU) · Director, Laboratory for Geocomputation · 150+ publications · 5 books · Work used by cities & NGOs · Former President, Canadian Regional Science Association · Former Graduate Program Director, Master of Spatial Analysis · Editorial board member of several journals · Neurodivergence advocate
Let's Work Together
Have a geospatial question or a dataset that needs a story? I collaborate with cities, NGOs, and companies on remote-sensing workflows, spatial ML audits, and location strategy. Speaking and mentoring available.
What I’m working on
Unsupervised Semantic Cartography of Personal Notes via Manifold Learning and Density-Based Clustering
Unsupervised Semantic Cartography of Personal Notes via Manifold Learning and Density-Based Clustering
Unsupervised Semantic Cartography of Personal Notes via Manifold Learning and Density-Based Clustering
What if we could use an unsupervised machine-learning pipeline to map personal notes into semantic clusters? This would involve using sentence embeddings, UMAP for manifold projection, and HDBSCAN for density-based topic discovery, yielding interpretable idea islands for rapid triage, private, local-first analytics, and reproducible knowledge organization.
Entropy-Minimizing Silo Sorting: Benchmarking Classical, Pairwise, and Randomized Heuristics (MRSA)
Unsupervised Semantic Cartography of Personal Notes via Manifold Learning and Density-Based Clustering
Unsupervised Semantic Cartography of Personal Notes via Manifold Learning and Density-Based Clustering
I built a reproducible benchmark that formalizes the “coloured balls into silos” problem as entropy minimization and compares four families of algorithms: (i) conventional alphabetical sorting, (ii) entropy-based redistribution that directly optimizes disorder, (iii) pairwise balancing via iterative adjacent swaps, and (iv) a novel heuristic (Minimum Random Swaps for Alignment).
philosophize this: The Trickster’s Mirror or a repetition of a jungian shadow
Unsupervised Semantic Cartography of Personal Notes via Manifold Learning and Density-Based Clustering
philosophize this: The Trickster’s Mirror or a repetition of a jungian shadow
From 1940 to now, the Joker has been portrayed as a modern trickster and Jungian Shadow. Batman’s inverted mirror, whose theatrical crimes stress-test law, identity, and material comfort. Each era shifts his tone from prankster to terrorist without losing his boundary-violating core. Less villain than instrument, he exposes—through horror and humour. How thin our civilizational mask is.
What my students HAVE WORKED ON
Urban design and cycling safety
Spatial Patterns of Climate Migration
Spatial Patterns of Climate Migration
Anastasiia Smirnova, is a PhD student in the Environmental Applied Science and Management program at TMU. Anastasiia's research explores how urban design impacts cycling safety, aiming to make cities safer and more accessible for diverse communities with varying needs and abilities.
Spatial Patterns of Climate Migration
Spatial Patterns of Climate Migration
Spatial Patterns of Climate Migration
Teagan Soni is a current Ph.D. student in the Environmental Applied Science and Management (EnSciMan) program at TMU, conducting research as a Canadian-Indian scholar. Teagan’s work examines how climate-driven migration impacts socio-economic factors, analyzing spatial patterns and correlations while using model building and quantum machine learning to better predict these trends and impacts.
Transit-Oriented Development
Spatial Patterns of Climate Migration
Transit-Oriented Development
Jacob Klein's study evaluates how Charlotte’s planned LYNX Silver Line can advance economic mobility via Transit-Oriented Development. Results reveal spatial heterogeneity tied to existing infrastructure and zoning, offering a baseline for station-area planning.
Veganism and food deserts
Veganism and food deserts
Transit-Oriented Development
Lindi Jahiu's research theorizes the “vegan food desert” within Toronto, situating it amid identity politics and neoliberal urban restructuring. Using a mixed-methods design grounded in patron Google reviews, we identify suburbanizing vegan food deserts and connections between vegan retailers, physical gentrification, and a gentrifying discourse.
Water quality in Nepal
Veganism and food deserts
Water quality in Nepal
Anugraha Udas’s An Evaluation of Water Quality and Accessibility in Nepal (2022) compares Kaski, Terai, and Kathmandu using a water quality index and distance-accumulation spatial analysis. Findings: Kaski has the highest water quality (second in accessibility), Terai ranks second in quality but leads in accessibility, and Kathmandu scores worst on both. The study calls for examining socioeconomic correlates to guide equitable mitigation and ensure universal access to clean water.