Curriculum Vitae
Education
Master of Science in Electrical Engineering and Computer Science (EECS)
Massachusetts Institute of Technology
2024 - 2026 (Expected)
- Focus on machine learning applications in urban systems and human mobility
- Research in computational methods for urban planning and transportation analysis
- Member of the City Form Lab, working on pedestrian activity modeling and social behavior detection
Master in City Planning
Massachusetts Institute of Technology, Department of Urban Studies and Planning
2024 - 2026 (Expected)
- Specialization in urban science, spatial analytics, and transportation planning
- Interdisciplinary program combining urban planning with computational analysis
- Research focus on sustainable and equitable urban development through data-driven approaches
Research Experience
Graduate Research Assistant
City Form Lab, Massachusetts Institute of Technology
2024 - Present
- Developing machine learning models for pedestrian activity estimation and social behavior detection
- Analyzing urban visual content using computer vision and deep learning techniques
- Working on neighborhood archetypes for energy modeling and transportation equity assessment
- Collaborating on interdisciplinary projects combining urban planning with computational analysis
Research Assistant
University of California, Berkeley
2022 - 2024
- Conducted research on urban systems and human mobility patterns
- Developed foundational skills in spatial analytics and urban data analysis
- Contributed to projects on sustainable urban development and transportation planning
Publications
Journal Articles
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Conference Proceedings
- [PLACEHOLDER: Author(s). (Year). Title. In Proceedings of Conference Name (pp. Page numbers). Location: Publisher.]
Skills
Technical Skills
- Programming: Python, R, JavaScript, SQL
- Machine Learning: TensorFlow, PyTorch, Scikit-learn, Computer Vision
- Data Analysis: Pandas, NumPy, Matplotlib, Seaborn
- GIS/Mapping: ArcGIS, QGIS, PostGIS, Leaflet
- Web Development: Jekyll, HTML/CSS, GitHub Pages
Research Methods
- Quantitative analysis and statistical modeling
- Spatial analysis and network analysis
- Machine learning and deep learning applications
- Urban data collection and processing
- Interdisciplinary research collaboration
Honors and Awards
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Teaching Experience
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[Course Name], [University Name]
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Professional Service
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Professional Memberships
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