M.S. in Software Engineering Systems
Boston, Massachusetts
About Chenxu
My background in finance, research software, and graduate teaching.
Background
I develop simulation software and computer vision tools for scientific research.
I studied finance at Southern University of Science and Technology before completing graduate degrees in Finance and Software Engineering Systems at Northeastern University. My quantitative-finance background informs how I think about uncertainty, feedback, and the assumptions behind an analysis.
At Northeastern, I develop Flow-CLD / Loopy-v2 with a research collaboration involving Aalto University. The software turns causal-loop diagrams into executable simulations and supports reproducible model experiments.
At the Rowland Institute at Harvard, I worked on real-time computer vision and projected feedback for behavioral experiments in the Rayshubskiy Lab. These projects connect my interests in reliable scientific software, real-time perception, and reproducible analysis.
Education
M.S. in Finance
Major in Quantitative Finance · Boston, Massachusetts
Bachelor of Economics in Finance
Shenzhen, China
Teaching
As a Part-Time Lecturer and Graduate Course Developer, I contributed to analytical modules, computational exercises, assignments, and assessment design. My materials connect financial reasoning with reproducible workflows and clear communication of results.
My role varies by course: design, teaching, or both.
FIN 6161Investment AnalysisDesign & teaching
Notebook-based assignments and applied labs connect return and risk measurement, portfolio construction, CAPM, and factor models to real market data. Students interpret their results through executive-summary reports.
CED 6230Quantitative MethodsCourse design
Python- and R-integrated learning activities develop statistical reasoning, data analysis, and reproducible workflows. Canvas-ready modules, assignments, and quizzes connect quantitative evidence to decisions.
CED 6150Risk Analytics in Finance and EconomicsCourse design
Updated modules and project-based exercises explore market and economic data, uncertainty, and risk assessment. Programming-supported workflows help connect model outputs to their assumptions and limitations.
FIN 6101Accounting Fundamentals for Financial InstitutionsTeaching
Financial reporting, the relationships between financial statements, transaction flows, and internal controls. Case-based exercises use common-size and ratio analysis to evaluate institutional performance.
CED 6250Derivatives & Alternative InvestmentsDesign & teaching
Course materials and computational exercises cover valuation, hedging, portfolio strategy, financial time series, efficient-frontier analysis, and stress testing with Python and Jupyter.
CED 6210Managerial FinanceCourse design
Instructional materials and applied activities connect capital allocation, risk–return tradeoffs, and performance evaluation with analytical reasoning and clear financial communication.
CED 6910Capstone: Master’s ProjectDesign & teaching
A staged project structure connects problem framing and literature review to data collection, model design, analysis, and presentation. Analytical reports and reproducible repositories support the communication of findings.
Across these materials, students work with data, examine model assumptions, and communicate analytical findings through notebooks, reports, and presentations.
Contact
For research software, quantitative models, or teaching, reach me at zhang.chenxu@northeastern.edu.