I am Alina Vivien Shults, a Master of Urban Design student at The University of Hong Kong with a background in Urban Planning from the Higher School of Economics. My work sits at the intersection of urban design, spatial analytics, environmental psychology, and AI-assisted research. I have experience with GIS, remote sensing, Space Syntax, urban data analysis, and design communication. I am currently a research assistant at HKU, working on urban light pollution and night-time environments. My broader research interests include neuro-urbanism, elderly-friendly streets, high-density public spaces, and how emerging AI tools can help designers and policymakers make more evidence-based urban decisions.

I am interested in Generative UI, LLM-driven frontend development, agentic interfaces, spatial AI, and decision-support tools for cities. I would like to learn how to build interfaces where AI dynamically generates the right UI for the task: maps, sliders, forms, evidence panels, comparison views, or design recommendations. I am especially interested in applications for elderly-friendly streets, urban heat, walkability, public space evaluation, and human-centred urban design.

Currently I am working on AI-assisted urban analysis projects, combining GIS, remote sensing, spatial indicators, and LLM-based interpretation. My recent work explores elderly-friendly street assessment using Street View Images and LLMs, urban heat/cooling analysis with NDVI/LST data, and interactive spatial storytelling. I am also interested in prototyping agentic interfaces that turn complex urban data into maps, evidence cards, rankings, and design recommendations.

Egor Bogautdinov is a Middle Geospatial Data Scientist at OZON.ru, with 5 years of experience. He holds degrees from The University of Hong Kong, Higher School of Economics, National Yang Ming Chiao Tung University, and Free University of Bozen-Bolzano, with studies in Urban Analytics, City/Urban Architecture, Transportation/Mobility Management, Economics, and Geography. Egor is also a Research Assistant at The University of Hong Kong. He is employed, open to work, and seeking full-time opportunities, with a preference for email contact and open to introductions for partnerships.

Geospatial data science, spatial modeling, scalable analytics for last-mile and pick-up networks, location intelligence, geoprocessing automation, urban analytics, machine learning and computer vision for urban datasets, distributed training, network optimization, spatial data pipelines, PostGIS, and partnerships.

Current projects include developing a **vehicle_counter** module using CV for transport modeling and maintaining **qgis_algo_tester** for geospatial automation. At OZON.ru, work focuses on building scalable spatial data pipelines and ML models for last-mile network expansion. Other active repositories include **geocoding_gkh** and **kindergarten_accessibility**. Technical stack involves Python, PostGIS, geopandas, and MATSim for simulation, alongside SQL-driven location intelligence.