Tien Tran

A Learner

Work Experience

Department of Building and Housing and Inspection logo

Department of Building and Housing and Inspection


October 2019 - May 2020

  • Responsible for digitizing, compiling, and analyzing more than 1000 housing inspection reports for the city of San Francisco.
  • Presented weekly to a panel of senior inspectors, providing critical data on the state of local housing conditions.
  • Developed a keen eye for detail and a deep understanding of the importance of accurate data analysis in informing policy decisions.
JCYC logo

JCYC - Japanese Community Youth Council


August 2020 - August 2021

  • Gaining valuable experience in networking and technical skills in computers through 32 workshops and meetings.
  • Demonstrated strong collaboration and project management abilities by working with fellows to plan and execute successful strategies to meet paper and grant deadlines.
MHS logo

High School's Administration Office

Student Assistant

September 2019 - May 2020

  • Performing a variety of tasks including answering phone calls, responding to emails, filing documents, managing schedules, and assisting with event planning.
  • Demonstrated excellent communication and interpersonal skills while interacting with students, parents, and staff members.
  • Gained valuable experience in office administration, time management, and problem-solving, which will be highly transferable to future roles in any industry.


CAL logo

University of California, Berkeley

Intending Major in Computer Science

August 2021 - Present

Data Structures, Structure and Interpretation of Computer Programs, The Beauty and Joy of Computing, Principles and Techniques of Data Science, The Foundations of Data Science, Designing Information Devices and Systems, Linear Algebra, Discrete Mathematics and Probability Theory, Multivariable Calculus
CCSF logo

City College of San Francisco

High School Dual Enrollment

Spring 2019 - Fall 2020

Pre-Calculus, Trigonometry, Calculus 1, Calculus 2 & Women and Gender Studies
SFSU logo

San Francisco State University

High School Dual Enrollment

Fall 2020 - Spring 2021

Ethnic Studies
UPENN logo

University of Pennsylvania

Online Course

Summer 2023

A Crash Course in Causality: Inferring Causal Effects from Observational Data
Stanford logo

Stanford University

Online Course

Summer 2023 - Fall 2023

Unsupervised Learning, Recommenders, Reinforcement Learning; Advanced Learning Algorithms; Supervised Machine Learning: Regression and Classification

Data Analytics


Housing Price Analytics

What is the price of a 3 Bedroom House?

Python, Matplotlib, Seaborn, NumPy, Pandas, Quantitative Analysis

  • Conducted exploratory data analysis (EDA) on a housing dataset of 204,792 data points and 61S different features using Python and pandas, identifying key features and trends to inform modeling decisions and improve predictive accuracy for house price.
  • Built and fit linear regression models using scikit-learn to predict housing prices based on relevant features, achieving a root mean squared error (RMSE) of 227K, and identified potential areas for model improvement through analysis of residuals and feature importance.

Climate Change Prediction


Python, Matplotlib, NumPy, Quantitative Analysis

  • Conduct an analysis of historical temperature data to identify trends over a prolonged period and utilize this information to make predictions about future weather patterns.
  • Categorize and create visual representations of data from 210 U.S cities for the last hundred years.

Email Classification

No spam please!

Python, Numpy, Pandas, Qualitative Analysis, Mathplotlib, Seaborn

  • Developed and fine-tuned a spam email classifier from a 9,348 emails dataset using natural language processing techniques and machine learning models, achieving an accuracy rate of 96%.
  • Leveraged data engineering strategies to extract pertinent features, such as filtering out common words and identifying distinct syntax patterns between spam and non-spam emails.
  • Additionally, controlled for confounder factors like reply or forward status in emails to enhance model performance and ensure accurate prediction outcomes.
  • Gained proficiency in utilizing sklearn libraries for data processing and model fitting, as well as validating model performance to minimize overfitting and analyzing ROC curves.

Population - Poverty

Poverty is the consequences of overpopulation or what other factors?

Python, Matplotlib, NumPy, Quantitative Analysis

  • Collected and analyzed 43,537 data points from to create visual representations of 12 statistical features pertaining to mortality, fertility, and poverty rates of 197 countries.
  • Utilized graphing and tabling methods to effectively convey trends and changes over time.

Personal Projects


My World Game

Build My Own World


  • Design and implement a 2D tile-based world exploration engine for educational purposes, simulating product development cycles with minimal starter code.
  • Focused on software engineering principles, code management, and problem-solving, while utilizing various data structures and algorithms for simplicity and efficiency.
  • Successfully created a grid-based virtual world that allowed user interaction and exploration, demonstrating project management and creative problem-solving skills.

Word Guess Game

What is the word?


  • In this project, I developed AI-based guessers and word choosers for the game "Awakening of Azathoth," gaining hands-on experience with Java's built-in List and Map data structures.
  • I successfully created three distinct AI guessers that could play the game, along with two innovative word selection classes that elevated the complexity of the problem.
  • This project showcased my ability to utilize data structures effectively, and allowed me to demonstrate my proficiency in Java programming.

Words Map



  • I developed a browser-based tool for exploring the historical usage of words in English texts. Utilizing a subset of the Google Ngram dataset, I built the back-end in Java to analyze word frequencies over time, focusing on individual words (1grams).
  • The project involved implementing various data structures and working with the WordNet semantic lexicon, which groups words into synsets and describes semantic relationships between them.
  • By harnessing the power of WordNet and data analysis techniques, I successfully created a functional tool that allows users to visualize the relative historical popularity of words in a clear and comprehensive manner.



Promise Scholars

Cohort 10

Class of 2021


San Francisco Foundation

Koshland Young Leader Award

Class of 2020


Summer Search

Bay Area

Class of 2021


Hearthstone Housing Foundation

Bay Area

Class of 2021




Technical Volunteer

Spring 2023 - Present


The Berkeley Project


Spring 2023 - Present