I am a senior studying Computer Science at Columbia University in the city of New York, seeking to become a graduate student in Financial Engineering.
With summer internship experiences in investment banking and industrial research, combined with my interdisciplinary background in mathematics, quantitative economics, and computer science, I am confident to become a creative, passionate, and industrial newcomer in the quantitative finance or technology industry.
Birthday: 08 Nov 1999
Phone: +1 717-961-7914
Degree: Bachelor of Science
Mail: dh3071@columbia.edu
Address: dh3071 Columbia Student Mail, 70 Morningside Drive, New York City, NY 10027
• Major in Computer Science
• GPA:3.63/4.00; GRE 328 (159+169+3.0)
• Transcript
• Double major in Mathematics and Quantitative Economics
• GPA:3.94/4.00 (Mathematics: 4.00/4.00)
• Honors:
      Alpha Lambda Delta
      Dean‘s List all semesters
      The Henry P.Cannon Memorial Prize in Mathematics (Awarded to #1 Sophomore)
• Transcript
• Participated in the due diligence of an IPO project of an IC company, independently wrote the draft of Equity Financing Business Plan, Feasibility Study, and Investment Decision Report and accepted by associates.
• Assisted in the completion of financial verification, employed comparative valuation (P/B, P/S, EV/EBITDA), and based on the assumptions of WACC, FCF, and CAPM, assisted analysts in initially establishing a DCF model to predict the company's financial status in the next five years, and conducted risk analysis such as sensitivity analysis.
• Independently analyzed photovoltaic glass and lithium industries, collected and sorted out various data from Wind and Bloomberg, and completed three Industry Research Reports and presentations.
• Analyzed macroeconomic events and trends (e.g., Annual Government Work Report and Central Economic Work Conference) and monitored industry downside risks and movements. Participated in Monthly Opinion Exchange Meetings and completed meeting minutes.
Some report exaples:
Photovoltaic Glass Industry Analysis Report
Lithium Industry Analysis Report
• In this project, we revisit and analyze the importance of pre-learned visual representations in grasp detection tasks with a pretrained DenseNet visual model and the Cornell grasping dataset.
• Through three abaltion studies, Frozen parameters, Fine-tune pretrained model and Train from scratch with random initialization, we demonstrate an efficient transfer of learning for predicting robotic object grasps from RGB/RGB-D images using DenseNet with both point and rectangle metrics. Our models validated the observation that transfer learning applied to visual representations improves robot manipulation tasks, especially when data size is insufficient.
• This is a full stack project aiming to practice Software as a service (SaaS), a way of delivering applications over the Internet with Implementation in Ruby. Under professor Junfeng Yang’s instruction, our group decided to implement an online repair report system.
• Based on Rails, a web application development framework, this project contains following modules such as logining both for user and manager, uploading a report, updating a existing report, sorting reports by emergency level, searching reports, deleting a report after completion of work. The system also support generating QR code with location information for following user to use in convenience. The project contains fronted part (erb files), backed part (controller file, model file, etc), and also have functional, unit, and integration tests for application quality assurance (cucumber and RSpec) and database migrations with Ruby on Rails and ActiveRecord (employ database after migration and seeding).
• Deployed in Heroku, the project Online Repair Report System has received widespread attention after presentation
• With a group of four under professor Sambit Sahu's instruction, a full-stack programming project, including fronted and backend, has been implemented.
• Based on the AWS platform, a campus second-hand goods trading platform has been developed and has received widespread attention. The project used S3, Cognito, SES/SNS, CloudWatch, RDS (connecting with MySQL database), lambda functions, and other related services.
• Responsible for developing web modules including product uploading, modification, search, and deletion (completed the fronted part and dealt with lambda functions, RDS database, API gateways, s3 bucket in AWS platform) and solved other systemic problems in front-end code.
• This web application is our final project for the User Interface Design course with Professor Lydia Chilton. The project involves building a web application that teaches users about a particular topic through interactive, iterative learning. This website aims to teach users how to analyze balance sheets since it is a valuable topic for young adults to get acquainted with.
• The project includes a flask server, HTML pages, and JS functions. We formed a group of three, and I was responsible for the rules, additional resources, and quiz parts.
• Employed Python and adversarial search algorithm to implement a Squid Game required to defeat the other group's code in Artificial Intelligence course with Professor Ansaf Salleb-Aouissi.
• The game is organized as a two-player game on a 7x7 board space. A player moves every turn and then throws a trap somewhere on the board. To win the game, you will need to trap the opponent, that is, surround them with traps from all sides so that they cannot move before they do that to you.
• Employed PostgreSQL in Google Cloud Platform to build a database and connect with fronted HTML pages to form a Hospital Information Management System under Professor Luis Gravano's instruction.
• Our group work was well-received by professors and presented to the whole class at the end of the semester.
• Employed comparative valuation (P/B, P/S, EV/EBITDA) and based on the assumptions of WACC, FCF, and CAPM, to establish a DCF model to predict Marriott's financial status in the next five years under Professor Nadejda Zaets's instruction.
• Calculated and evaluated the company's return on equity, return on total assets, total asset turnover, current asset turnover, asset-liability ratio, earned interest multiple, sales (operating) growth rate, and capital accumulation rate. Predicted the future valuation of the company.
• Analyzed potential application of the SIR model to stimulate and better understand the spread of gossip in society under the instruction of Professor Lorelei Koss.
• Established the Gossip Model using modeling tools developed to understand infectious disease with Python.
• Studied the Anthropomorphized Sensitivity Analysis to illustrate the contextual significance of parameters and translate social characteristics into mathematical language using the Gossip Model, a compartmental model of SIR coded in Python.
• Concluded that the SIR model can be used to simulate more complex scenarios with high realistic validity.
• An in-class research project as my Quantitative Economic major graduation project in class ECON 496 Senior Seminar (Political Economy of Health) with Professor Kongar Ebru.
• My dissertation explored the differences between the medical insurance systems in China and the United States. The main focus is on the difference in the payment of medical insurance for common respiratory diseases during the epidemic.
• By employing Stata and incorporating Congress.dta Dataset, this project aims to find how much party matters by looking at the ideology of members of the 112th Congress in the class of Econometrics with Professor Emily Marshall.
• By plotting scatterplot, histogram, and establishing report with the model specification for the varying-slopes RD models, a substantial bump at the discontinuity, which suggests the party does indeed matter, was found.
• With the assumption where discontinuities exist at the cutoff for child-poverty, median-income, obama2008, and whitepct by our four auxiliary varying-slopes models, a quantitatively analyzed report was built up after exploring the relationship between different variables.
• It concluded that the party does matter since a significant jump in ideology at the cutoff in obama2008 and the whitepct case; however, there is no sign of discontinuities in the child poverty and median income models.
• Analyzed the relationship between Global GDP per capita with thirteen different parameters with Professor Vlad Tarko.
• Established the linear regression model using modeling tools developed to understand relationships with R studio. The Data is retrieved from the Quality of Government Institute (QoG).
Introducted by Alexei Chekhlov (From Columbia University)
• Performed the Markowitz and Index model with ten stocks with twenty years of price data to find the regions of permissible portfolios (efficient frontier, minimal risk portfolio, optimal portfolio, and minimal return portfolios frontier) with additional five constraints. Plot the capital allocation line of the MM and IM model and incorporate five constraints in the plot of the portfolio chart.
• It concluded that the Index model could perform better in low-risk areas since it tends to have higher returns in low-risk areas when seeking an efficient frontier and a lower return as well as a lower loss when seeking an inefficient frontier. The Markowitz model performs better in finding more risk-efficient portfolios for every constraint.
• The differences between these two models might arise from the Index model could be considered to have an improvement over the Markowitz model in a way that it reduces the estimations needed (The correlation between each stock) by relating them to a single index.
Conference: 2022 International Conference on Portfolios, Global Marketing and Economic Environment
(PGMEE 2022) (Accepted)
• This paper assessed the impact of fed rate hikes on the Chinese A-share market, specifically the Shanghai Stock Exchange (SSEC) and Standard and Poor's 500 (S&P 500), a stock market index that reflects the U.S. stock market. A VAR model and an ARMA-GARCH model were established in Stata to analyze the variations in stock prices caused by changes in the foreign exchange rate between CNY (China Yuan) and USD (U.S. dollars).
• Conclusion: With the premise of the rate of stock return based on rigidity in the short period of the firm's product price and omitting other potential outside variables that impact the general stock markets, the research results confirmed previous conjectures and some theoretical judgments, which show a slightly negative net effect caused by a higher exchange rate on the Chinese stock market and a negligible effect on the U.S. stock market.
• Employ python and SSEC closing price data from 2000 to 2022 to explore the application of the moving average method in smart auto investment plans.
• Find a result that long-term investments need to consider the economic cycle, which can improve the overall rate of return. Besides that, with a uniform investment strategy, the overall rate of return is almost the same for different investment frequencies within a particular investment duration.
• By exploring the 500-day moving average investment strategies of Alipay, F&C, and Efund, we find that strategy of Alipay only triggers the deduction when it encounters some long-term and substantial market fluctuations, which might be slow to react to market variance. But for an overall stable rebounding upward market, the strategy instead performs better.
• Responsible for planning and organizing a number of large-scale activities such as Mid-Autumn Reunion, Spring Festival
Reunion, Cherry Blossom Spring Outing, and Badmiton Tournament with good feedback.
• Responsible for managing and operating the official WeChat public platform, regularly releasing original tweets and photo albums.
Mathematics and Statistics
MATH 171 Multivariable calculus
MATH 211 Discrete math
MATH 225 Probability and Statistics I (Minitab)
MATH 241 Numerical methods (Matlab)
MATH 262 Linear Algebra
MATH 270 Integration and Infinite Series
MATH 271 Differential Equations (Python)
MATH 351 Abstract Algebra (Latex)
MATH 361 Real Analysis (Latex)
MATH 325 Probability and Statistics II (R studio)
MATH 472 Complex Analysis (Latex)
STAT 4221 Time Series Analysis (Columbia) (R studio)
APMA 4200 Partial Differential Equations (Columbia)
IEOR 4106 Stochastic Models (Columbia)
Economics
ECON 268 Intermediate Macro
ECON 278 Intermediate Micro (R studio)
ECON 288 Contending Economic Perspective
ECON 298 Econometrics (Stata)
ECON 314 Economy of Disasters
ECON 373 History of Economics Thoughts
ECON 496 Senior Seminar (Political Economy of Health)
IEOR 2261 Financial Accounting (Columbia) (Excel)
ECON 4415 Game Theory (Columbia)
ECON 4280 Corporate Finance (Columbia)
Computer Science
COMP 131 Introduction to Java (Java)
COMP 232 Data Structure and Algorithm (Java)
COMP 356 Programming Language Structure (C/Racket/Prolong)
MATH 314 Computational Complexity
COMS 3157 Advanced Programming (Columbia) (Linux/Unix/C)
COMS 3261 Computer Science Theory (Columbia)
CSEE 3827 Fundamental of Computer (Columbia) (MIPS)
COMS 4111 Introduction to Database (Columbia) (PostgreSQL)
COMS 4170 UI Design (Columbia) (JavaScript/JQuery HTML/CSS)
COMS 4701 Artificial Intelligence (Columbia) (Python)
COMS 4151 Software as a Service (Columbia) (Ruby)
COMS 6998 Cloud Computing and Big Data (Columbia) (AWS/Python/MySQL)
COMS 6998 Robotic Learning (Columbia) (Python/Pybullet)
Online Courses
Operating Systems - Peking University (Coursera)
Beginning C++ Programming - From Beginner to Beyond (Udemy)
Quantitative Finance & Algorithmic Trading in Python (Udemy)
Data Science: Statistics and Machine Learning - Johns Hopkins University (Coursera/Specialization)
      Regression Models
Applied Data Science with Python - University of Michigan (Coursera/Specialization)
      Introduction to Data Science in Python
Financial Engineering and Risk Management - Columbia University (Coursera/Specialization)
      Introduction to Financial Engineering and Risk Management
Spring 2023 Courses
COMS 4705 Natural Language Processing (Columbia) (python)
COMS 4732 Computer Vision II (Columbia) (python)
COMS 4995 Applied Machine Learning (Columbia) (python)
COMS 6113 Topic in Database Management Systems (Columbia)
Distribution Courses
PHYS 131 Introduction Physics I
PHYS 132 Introduction Physics II
CHEM 131 General Chemistry with Lab
ARTH 101 Introduction History of Art
COMP 108 Arts of East Asia
PHIL 101 Introduction to Philosophy
......
Programming Languages
Java
C/C++
JavaScript/JQuery
HTML/CSS
Python
MATLAB
R/R-studio
MySQL/PostgreSQL
Assembly (Mips)
Stata
Ruby
Racket/Prolong
Minitab
Latex
Languages Skills
Mandarin (native)
English (fluent)
Certificates
Quantitative Finance & Algorithmic Trading in Python (Udemy)
Introduction to Data Science in Python (Coursera)
Introduction to Financial Engineering and Risk Management(Coursera)
Other Information
Wind/Bloomberg (basic)