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Boka Luo

Worcester, MA, USA

Boka Luo
Address: 41 Maywood St, Worcester, Ma 01603
Email: bk.luo@hotmail.com
Website: https://bkluo00.wixsite.com/mysite
www.linkedin.com/in/boka-luo

SKILLS
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Programming Language:
Python, R,JavaScript,HTML 5,CSS

GIS Software:
ArcGIS, QGIS , GeoDa, AutoCAD

Remote Sensing Software:
ENVI, ERDAS IMAGINE, TerrSet (IDRISI), Google Earth

Other Software:
SPSS, Adobe Photoshop, Microsoft Office Suites
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EDUCATION
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Master of Science in Geographic Information Science
Clark University, Worcester, Massachusetts
Expected May 2019
Current GPA: 4.05/4
• IDCE Merit Fellowship, 2017-2019

Bachelor of Engineering, Land Resources Management China University of Geosciences, Wuhan, China
July 2016
GPA: 84.4/100
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PROFESSIONAL EXPERIENCE
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Graduate Research Assistant (Remote Sensing)
Clark Labs, Worcester, Massachusetts
June 2018- Present
• Updated protocol for image mapping from remotely sensed data
• Tested on feature extraction methods and image processing filters on multispectral SAR data
• Researched on mapping automation through deep learning and model optimization
- Built, refined, debugged and execute scripts across systems for data loading, image processing and deep learning algorithm.
- Visualized data, analyze data and prepare result for presentation
- Applied Python libraries as gdal, numpy, opencv, matplotlib, sklearn and pytorch etc.

Assistant Urban Planner (Internship) Shenzhen Buenavista Investment Consultation Co., Ltd, Shenzhen, China
Aug 2015- Sept 2015
 • Assisted in project planning, including website research, data mining, mapping and analysis
 • Took part in multiple conceptual planning projects of tourist areas
- Applied AutoCAD in land use mapping from surveying maps
- Carried out terrain and spatial analysis in ArcMap on study areas based on national policies and environmental conditions
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RESEARCH EXPERIENCE
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Coastal Aquaculture Mapping
Clark Labs, Worcester, Massachusetts
2018-Present
• Create baseline maps for 8 maritime nations and conduct vulnerability analysis of mangrove conversion to pond in areas of interests
• Research on classification automation for annual global ponds recognition and mapping through deep learning

Cropland Flooding Dynamics in South America: a case study in Santa Fe, Argentina and Rio Grande do Sul, Brazil, 2013-2017 Advanced Remote Sensing, Clark University, Worcester, Massachusetts
2018
• Examined monthly profile of precipitation, crop production and flooding occurrence in Santa Fe and Rio Grande do Sul with TRMM and MODIS data
• Explored inundation time and mapped cropland flooding dynamics in inundated region using Normalized Difference Flooding Index (NDFI) using Python

Comparing three machine learning techniques as MLP, SVM and Random Forest in Land Change Modeling Advanced Raster GIS, Clark University, Worcester, Massachusetts
2018
• Assessed the ability of MLP, SVM and Random Forest to simulate land cover transitions with a case study in Massachusetts

Geo-spatial assessment of flood inundation of hurricane Harvey: a case study in South Eastern Texas 2017
Introduction to Remote Sensing, Clark University, Worcester, Massachusetts
• Assessed the impact of hurricane Harvey through land cover and vegetation degradation of four country subdivision blocks in the Greater Houston Area
• Implemented MLP classification and indices of NDVI, SAVI and NDWI

Exploring the Spatial Distribution and Underlying Causes of Coral Bleaching in Florida Keys National Marine Sanctuary (FKNMS)
Advanced Vector GIS, Clark University, Worcester, Massachusetts
2017
   • Examined spatial variation of coral bleaching in FKNMS through a Getis-Ord Gi* statistic hot spot analysis
• Assessed the relationship between bleaching and water quality variables that may contribute to bleaching using ordinary least square (OLS), spatial lag and spatial error

Fire Risk and Fire Accessibility to Fire Assistance
Computer Programming for GIS, Clark University, Worcester, Massachusetts
2017
• Analyzed accessibility to service facilities from shapfiles of local roads, local boundary, and local facilities.
• Applied python script to develop a tool to automatically produce a map comparison of Fire Hazard Severity Zones and accessibility to fire assistance.

Dynamic Simulation and Prediction of Land Cover Pattern in Guangzhou Based on CA-Markov Model Bachelor’s Thesis, China University of Geosciences, Wuhan, China
2016
• Researched on land cover pattern in Guangzhou of the year 1995, 2005 and 2015 based on Landsat data and socioeconomic data
• Simulated land cover change in Guangzhou during 2005-2015 and predicted land cover pattern in 2025 using CA-Markov model

Evaluation of Eco-city in Shenzhen, China Land Ecology, China University of Geosciences, Wuhan, China
2015
• Collected socioeconomic data of Shenzhen from 2007 to 2013 and created a three-level index system of eco-city evaluation
• Adopted entropy weight method to determine the index weight and calculated the ecological comprehensive index
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RELATED COURSES
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Python Programming
Open Source and Web Mapping
Deep Learning for GIS
Intermediate Quantitative Methods
Principles of Database
Advanced Remote Sensing
Advanced Raster GIS
Advanced Vector GIS
GIS and Land Change Models
Land Data Processing
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OTHER EXPERIENCES
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Vice Director, College Students’ Science and Technology Association 2014
China University of Geosciences, Wuhan, China

Vice President & Vice Director, Micro Blog Association 2014
China University of Geosciences, Wuhan, China

Leading Member, Youth League and Student Work Committee 2012- 2013
Department of Material Science and Chemistry, China University of Geosciences, Wuhan, China

City Volunteer, Volunteer Command Center for the 26th Summer Universiade
2008
Shenzhen, China
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Boka Luo

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