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Chittagong University of Engineering and Technology (CUET)
Data Scientist
June 28, 2026 – Present
Lamun365.github.io
December 14, 2025 – December 15, 2025
Lamun365.github.io — GitHub repository
View ProjectTraffic-Signal-Control-Optimization-for-Heterogeneous-Traffic-Using-Reinforcement-Learning
December 13, 2025 – December 13, 2025
Traffic-Signal-Control-Optimization-for-Heterogeneous-Traffic-Using-Reinforcement-Learning — GitHub repository
View ProjectExplaining-Household-Access-to-Heavy-Rail-Services-Using-Interpretable-Machine-Learning
December 2, 2025 – December 3, 2025
ML models (RF, SVM, KNN, XGBoost) predict household heavy rail access using NHTS 2022 data. After preprocessing and 5 fold tuning, models reach about 96 percent accuracy. SHAP shows proximity to stations, vehicle availability, and urban density as key drivers, giving interpretable insights for transport policy.
View ProjectOptimizing-V2V-Communication-Delay-Prediction-in-CAV-Vehicles-through-SUMO-and-ns-3-Simulations
December 2, 2025 – December 2, 2025
Integration of SUMO mobility and ns3 wireless simulation is used to predict V2V delay in CAV platoons. Using 802.11p data and ML models like RF and XGBoost, delays are predicted from speed, distance, and RSSI. Results show accurate delay prediction for safer and more efficient CAV networks.
View Projecttrip_mode_choice
September 18, 2025 – September 18, 2025
trip_mode_choice — GitHub repository
View Projectco2-drone-sumo-ml-tigerpass
September 18, 2025 – September 18, 2025
co2-drone-sumo-ml-tigerpass — GitHub repository
View Projectfirst_static_website
August 11, 2025 – August 11, 2025
first_static_website — GitHub repository
View ProjectExplainable-Machine-Learning-for-Understanding-Trip-Mode-Choice
April 21, 2025 – December 2, 2025
Explainable-Machine-Learning-for-Understanding-Trip-Mode-Choice — GitHub repository
View ProjectCultural Fit Analysis
The candidate's projects show a strong focus on academic and research-oriented data science problems, particularly in transportation and communication. This indicates a potential fit for roles requiring analytical rigor and problem-solving. However, the projects are all personal and lack team collaboration context, making it difficult to assess cultural fit comprehensively. The experience level of 0 and a future-dated role also limit the assessment.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's experience level is listed as 0, and the only listed 'experience' is a future role as a Data Scientist starting in 2026, which cannot be evaluated.