DanielWarlock

My plan is to do a bunch of reach schools and 2 absolute safe schools. The schools you listed may not be actually very safe for me since they are still quite good. What about 9 crazy schools plus UIUC and University of Florida? I should be a shoe-in for the latter two schools right? Is university of Florida that easy to get into? I'm thinking replacing UIUC with Chicago if that's the case.

Thank you statfan. I don't have a pure math background in my undergrad so these are mostly engineering's requirement. I thought that taking graduate probability and inference during my masters would help. But yes the competition is stiff and my coursework is definitely not the most impressive. What range/schools would you recommend me to apply to to be safe?

Hello my friend. I'm also applying this year but towards US. I went to UofT for college. I think you did marvellously! Your profile seems to be stronger than mine in a lot of ways. Your performance on Real Analysis is very incredible. I think you should apply to University of Ottawa too. Professor Aaron Smith there works on MCMC stuff but perhaps his main focus is discrete chain and coupling etc but it's all related.

It appears to me that you are not very competitive in terms of academic credentials so you may have trouble applying to most PhD programs or certain "more academic" programs such as Chicago. But your work experience is highly impressive, which is a huge bonus for many data science/statistics master degrees. An example is Harvard. I did my masters at Harvard University so from looking at admitted students, I know they place high regard on industry experiences, as well as prestige of your undergraduate institution. You can apply to Data Science master program at Harvard. Talking to the admission personnels in advance may help (although I didn't). What is your GPA and GRE? These actually matter a lot to admission to a master program contrary to common narratives, probably even more so than research experience unless you have glowing letters or publication. Most people I know here have near-perfect GPA and GRE (exceptions apply). That said, it's not the same as taking crazy graduate level analysis class and get 100. You just need good grades on most, probably not very rigorous, classes you did.

I'm applying to PhD in statistics (primarily) and CSE programs (computational sciences) this year. It'd be very helpful if you can take a look at my profile and give me some advice on programs to apply to, especially ~2 safe schools. My profile: I'm currently doing a master at Harvard (CSE masters, GPA: 4.0/4.0). I did my undergrad at University of Toronto (Engineering Sciences, GPA: 3.92/4.00). No GRE math (I took it without sufficient prep and got a terrible score--76%) and will probably not reveal it to anyone. General GRE: 166(V), 168 (Q), 4 (W). Recommendation Letter: Both professors at Harvard knows me and my recent work very well -- one is my advisor and I have discussed research with the other prof frequently; Nailed their classes (PhD inference II and probability II respectively). My advisor said he wanted me to continue working with him as PhD but cannot guarantee admission. I'd like to say both profs think highly of me but that could be out of politeness. The other one is my old senior thesis advisor, who does not know my recent progress but he is very well known in the community. I think my work with him is somewhat solid but not very good. Work experience: e-trading developer at Citigroup, quant research intern at a pension fund (OTPP). All these are like 2 years ago and I have left finance stuff since. Research: there is probably no time for my work to be peer-reviewed before application. I know this is very bad. I need to rely on my advisors to testify on the quality of the work. Will those guys in the admission committee at least take a look at the preprint or they just don't care? Anyways, two Harvard profs know my most recent work and I have to trust them to talk about it at least a little. School list: These are schools I want to get into--I have not included safe schools. I will probably fail all these. So I need about 2 safe schools--and I will substitute them into the list. What are some of the good choice? Notice that I excluded Stanford statistics because that is a waste of time with my math GRE. I may drop Chicago for some safe schools as they seem to have a penchant for people with crazy math track record incl. high math GRE. Any advice on the list in general is appreciated. List of research article: Li, Yufan., Pillai, Natesh "Regeneration Sampling with Multiple Atoms." preprint (2019). [Link to Article] Li, Yufan., "Markov Chain Monte Carlo Algorithms and Related Convergence Properties." Undergraduate Thesis, University of Toronto, [Link to Article] Li, Yufan., Rosenthal, Jeffery "A Divergent Random Walk on Stairs." arXiv preprint arXiv:1808.10121 (2018). [Link to Article] Li, Yufan. "Improve Orthogonal GARCH with Hidden Markov Model." arXiv preprint arXiv:1909.10108 (2019). [Link to Article] Relevant Courses: I did not take a tons of classes at Harvard because I need to work on research so just the bare minimum: standard phd course on probability and inference. Statistics (Standard PhD Sequence) STAT 210 Probability I (Harvard), A STAT 212 Probability II (Harvard), A STAT 211 Inference I (Harvard), A STAT 212 Inference II (Harvard), A STAT 230 Multivariate Statistical Analysis (Harvard), Ongoing STAT 244 Grad. Linear & Generalized Linear Models (Harvard), Ongoing STAT 220 Bayesian Data Analysis (Harvard), Ongoing Computing, AM 205: Advanced Scientific Computing (Harvard), A CS 207: System Development for Computing (Harvard), Ongoing CS 205: Distributed and Cloud Computing (Harvard), Ongoing Mathematics, MATH 122: Group, Ring Theory & Vector Spaces (Harvard), A MAT 336H1 Real Analysis (UofT), 99 MAT 334H1 Complex Analysis (UofT), 100 MAT309H1 Math. Logic (UofT), 100 APM 384 H1 Partial Differential Equations (UofT), 100 MAT292H1 Calculus III (UofT), 100 MAT195H1 Calculus II (UofT), 99 MAT191H1 Calculus I (UofT), 97 MAT185H1 Linear Algebra, 92