Profile
- GPA: 4.0
- University: US T30
- Majors: Quant-related
- International: yes
- Internships: 3x: quant (us), quant (China), finance (China)
- Research: Published paper
Prediction Results
- Master of Science in Financial Engineering (New York University): 78% [67%-86%] — safety
- Master of Science in Quantitative and Computational Finance (Georgia Institute of Technology): 64% [29%-89%] — target
- Master of Arts in Mathematics of Finance (Columbia University): 62% [47%-76%] — target
- Master of Science in Mathematics in Finance (New York University): 62% [44%-76%] — target
- Master of Science in Financial Mathematics (University of Chicago): 59% [46%-70%] — target
- Master of Financial Engineering (Cornell University): 57% [40%-73%] — target
- Master of Science in Computational Finance (Carnegie Mellon University): 55% [45%-64%] — target
- Master in Asset Management (Yale University): 50% [29%-72%] — target
- Master of Financial Engineering (University of California, Berkeley): 48% [25%-72%] — target
- Master of Science in Financial Engineering (Columbia University): 48% [39%-57%] — target
- MS in Financial Economics (Columbia University): 37% [11%-74%] — reach
- Master of Science in Mathematical and Computational Finance (Stanford University): 32% [21%-47%] — reach
- Master of Finance (Massachusetts Institute of Technology): 32% [18%-50%] — reach
- Master in Finance (Princeton University): 22% [9%-46%] — reach
- Master of Financial Engineering (Baruch College, City University of New York): 16% [5%-41%] — reach
Command: quantpath predict --profile profiles/data_contrib_issue_3.yaml (GPBoost v2 — retrained 2026-04-02). 15 programs — 5 reach / 9 target / 1 safety.
Actual Outcomes (please update later!)
Auto-generated by quantpath predict
Profile
Prediction Results
Command:
quantpath predict --profile profiles/data_contrib_issue_3.yaml(GPBoost v2 — retrained 2026-04-02). 15 programs — 5 reach / 9 target / 1 safety.Actual Outcomes (please update later!)
Auto-generated by
quantpath predict