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Found 3 results

  1. Undergrad Institution: Berkeley Major(s): Math + Computer Science GPA: 3.89 Type of Student: International Asian Male GRE Revised General Test: 170 + 153 + 4.0 Program Applying: Computational Math Phd Relevant Undergrad Courses & Grades: Intro to Analysis (A+), Numerical Analysis (A+), Linear Algebra (A+), Complex Analysis (A-), Abstract Algebra (A), Combinatorics (A+), some lower division courses, and some computer science courses, A+ or A. Graduate Courses & Grades: Numerical solution to DE A&B (A+, A), Real and functional analysis (A, A-), Numerical Linear algebra (A) Research Experience: Undergraduate research for 2 years, using statistics and math modelling, a paper submitted. Just started my "serious" research about preconditioners in compact DG method with implicit Runge-Kutta, exploring AMG now. But it is research, so no specific direction, just mess around, trying new things and see how they work. No result, but enjoy it very much. (It is really fun! Don't know what to expect every week.) Awards/Honors/Recognitions: None. Probably some GPA related things, but not important. Pertinent Activities or Jobs: Tutor in CC. Grader, lab assistant. Any Miscellaneous Points that Might Help: 5 graduate classes related to the thing I am interested in: numerical PDE AB, numerical linear algebra, Real & functional analysis. DRP for two semesters, on spectral method, spectral element method, multigrid. Self-studied DG and Evans' PDE, only some notes and codes, no fancy papers. Recommendation letters should be okay. Any Other Info That Shows Up On Your App and Might Matter: Enjoy numerical PDE (specifically DG) very much! I started my undergraduate as a computer science major, and I switched to math pretty late. Maybe my programming background could be useful? Interested in computer graphics at first (physical simulation specifically), but could not understand PDE, so crazy studying math afterwards. Applying to Where: Dream School (I guess not necessarily the hardest): Rice - CAAM Reach: Brown - Applied math Cornell - CAM UT Austin - ICES Match/Safe: U Washington - Applied math Northwestern - engineering sciences and applied mathematics Rensselaer - Mathematics Any advice will be very helpful for me~ Thank you very much!!! ?
  2. Undergrad Institution: Liberal Arts University (ranked in the top 10 in the US) Major(s): Biology and Psychology Institution since undergrad: Local public university (I have been taking classes there because I was missing a few pre-requisites) GPA (undergrad): 3.355/4.0 GPA (*since undergrad*): 4.0/4.0 Type of Student: Domestic Female GRE General Test: Q: 166 V: 168 W: 4.0 Programs Applying: MS Biostatistics Research Experience: Volunteered/worked part time for 2.5 out of 4 years in undergrad. Worked in 3 different labs, all biology-related. 1 poster presentation at a national conference. Pertinent Activities or Jobs: Since graduating have been working at a major research institution as research coordinator. 1 poster presentation and currently working on a manuscript that involved some use of statistics and SAS (might not be submitted to review by the time applications are in). Letters of Recommendation: Immediate supervisor (strong), collaborator on the manuscript (strong), professor for a biology class (decent) Relevant Coursework: Taken at undergrad institution. Calculus 1: B- Calculus 2: B- Intro to Quantitative Modeling in Biology: A- Statistical Methods and Applications: B+ Psychological Research Methods: B Taken since graduating: Calculus 3: A Intro to Linear Algebra: A Intro to Probability Theory: Still taking it, likely A Applying to Biostatistics Masters Programs (Subject to adding and subtracting *advice welcome*): Berkely Columbia University of Washington University of Michigan UCLA Harvard Boston University Rutgers University of Minnesota University of Pittsburgh Brown University Johns Hopkins
  3. Hello all, A bit more of a non-traditional background here. I was an econ 'math-light' major in undergrad. Started to get interested in statistics after a year long course in econometrics my senior year (lower level - no prerequisites in multivariable calc or linear algebra if you can believe it...). I didn't feel overly satisfied with continuing on a finance track as a profession, and decided to jump into the maths after I graduated. Over the past year plus I have been working from the ground up taking courses in mathematics, statistics, and computer science, and have loved everything I've taken. I also (hope) I've done relatively well in these courses, but unfortunately no matter what I do I cannot seem to get my GRE score up... It seems silly to me that I can take these courses and do well, but somehow struggle with high school maths ?(...and I have done loads of studying, tutoring, and the like in an attempt to pick these scores up). I will certainly be applying abroad to programs that do not require GRE scores. (Please excuse the slightly bitter rant to follow). It does seem a little bit odd that programs across the globe all require around the same basic coursework, but largely only US schools require the GRE. This makes sense to me for the obvious reason of sifting through piles of applications, and for the purposes of having a standard means to equate applicants who come from less familiar universities, but does a high GRE score really translate into an ability to succeed in the masters level? I guess I'm holding onto a prayer that my (super) low GRE scores could be overlooked given what seems like a pretty odd mismatch between my scores and my academic performance? I should also note also that my SAT scores were awful as well, but I don't think that really impeded my performance in undergraduate level mathematics... Am I praying too hard here, or am I just out of reach for US schools (or for that matter am I out of reach for all the schools I listed)? Are there schools that would better fit my profile? Any and all advice is greatly appreciated! Sorry for the essay.. Undergrad Institution: Liberal Arts *Since Undergrad*: Ivy Major(s): Economics Minor(s): Philosphy GPA (undergrad): 3.74 GPA (*since undergrad*): 3.84 Type of Student: Domestic Male GRE General Test: Q: 157 V: 153 W: 4.0 Programs Applying: MS/MA Statistics Research Experience: N/A Pertinent Activities or Jobs: (not sure they are all too pertinent..) 3 summer internships in finance (equity research, insurance brokerage, investment banking) while in undergrad Letters of Recommendation: Linear Algebra (strong), Real Analysis (I think strong pending he says yes! - just asked), Statistical Inference (I think strong pending he says yes! - just asked) Relevant Coursework: Econ: (not sure this will bear any weight): Corporate Finance (3.67), Micro(4.0), Macro(3.3), Int'l Finance(3.67), Intro to Statistical Data Analysis(4.0), Int'l Trade(3.67), Econometrics (4.0) In the past 1.5 years: - Calc I (4.0) - Calc II (4.3) - Accelerated Multivariable Calc (two full Calculus courses (III & IV) taught at this institution and rolled up into a one semester course - 3.3) - Linear Algebra (4.0) - Intro to Proofs (Pass) - Real Analysis (first ~ 6.5 chapters) - Rudin (4.0) - Intro to Java/CS (4.0) - Probability Theory (taught to both undergraduates and graduates with no distinction between the two - 3.3) Currently taking: - Statistical Inference (also taught to both the undergrad's/grad's with no distinction b/w the two - on course for 4.0 to 4.3) - Linear Regression Models (a bit more on the applied side, also taught to both grads and undergads) - Data Structures in Java Next Semester: - Advanced Linear Algebra - Statistical Computing (taught to both grads/undergrads) - maybe Advanced Programming - possibly audit another math course (for personal fun, Analysis and Optimization for example).. Over the Summer: - possibly Time Series Analysis - possibly Statistical Machine Learning - possibly some Python online courses.. Applying to Where (Subject to adding and subtracting *advice welcome*): US: Stanford Berkely Chicago Columbia Duke University of Washington Wisconsin-Madison Cornell Abroad: LSE (Senior year spent here) Oxford U of T UBC McGill Imperial UCL Thanks!!!
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