Saeedmakaremi

Saeedmakaremi I'm an urban planner and researcher working at the intersection of cities, data, and intelligent systems. i apply artificial intelligence, machine learning, and spatial data science techniques to explore and address urban challenges, particularly in mobility, energy, and public space. my research and projects focus on transforming complex data into creative applications and actionable insights. Urban data science researcher. saeedmakaremi has 3 repositories available. follow their code on github.

Saeedmakaremi ‏urban planner and researcher working at the intersection of cities, data, and intelligent…‏ · تجربه: ‏zva‏ · تحصیلات: ‏shahid beheshti university‏ · مکان: ‏iran‏ · ‏481‏ رابطه ‏ها ‏در linkedin. نمایه ‏saeed makaremi‏ ‏‏ را در linkedin یک جامعه حرفه ای از ۱ میلیارد عضو مشاهده کنید. 64 followers · 206 following. see photos and videos from friends on instagram, and discover other accounts you'll love. See what saeed mk (saeedmakaremi) has discovered on pinterest, the world's biggest collection of ideas. Proud to share my latest publication in elsevier's energy journal (impact factor = 9, volume 317, 15 february 2025): 📌 doi: lnkd.in d8ftm4tu the study introduces a multi output deep.

Saeedmakaremi See what saeed mk (saeedmakaremi) has discovered on pinterest, the world's biggest collection of ideas. Proud to share my latest publication in elsevier's energy journal (impact factor = 9, volume 317, 15 february 2025): 📌 doi: lnkd.in d8ftm4tu the study introduces a multi output deep. Multi output deep learning approach for ev charging infrastructure analysis, featuring demand forecasting and policy impact assessment. published in energy (2025) and case studies on transport policy (2024). saeedmakaremi ev charging analysis. Overview evprof is part of a suite of packages to analyse, model and simulate the charging behavior of electric vehicle users: evprof: electric vehicle profiling evsim: electric vehicle simulation evprof aims to provide tools for classifying ev charging sessions into generic groups with similar connection patterns named “user profiles”, using the gaussian mixture models (gmm) clustering. A collection of geospatial data viz created for the #30daymapchallenge saeedmakaremi 30daymapchallenge highlights. Day 16 oceania: urban rail stations accessibility analysis in auckland, nz on day 16 of #30daymapchallenge, exploring oceania, i delved into the vibrant….