Sergio.zz

Hi everyone, I just received the PhD offer from CMU stats department, and I am so happy with that. However, now I am facing a difficult decision between choosing to stay at University of Toronto for my PhD (where I did my undergrad) or go to CMU for a new adventure. My current research interest is more about: 1. Applied Bayesian inferential methods. 2. Statistical Computations. 3. Machine learning and Data Science. And my future plan is to find a faculty position in statistics. The pros for UofT: 1. I am an international student, so staying at uoft makes it more possible for me to get the PR card in Canada, while the PR card in US is a bit impossible... 2. I did my undergraduate study at here, so I know the faculties at this university very well. And I have been matched with my preferred supervisors whom I have already worked with and felt good working with, while CMU currently did not match me with any supervisor yet. 3. There will be five years of full funding package which includes full-tuition plus 20k stipend per year for UofT, while CMU's offer only describe my full funding package for one year (full tuition + 3.1k stipend per month), and based on their student handbook it seems like the funding from CMU usually only lasts for four years... The pros for CMU: 1. Higher ranking in Statistics, especially in Machine learning and Data Science. 2. Based on the suggestions from my professors, if I want to continue my career in academia, it seems like it would be better for me to not go to the same place for both undergraduate and PhD... But I am not sure how important that factor is 3. Probably the winter at Petersburg will be more approachable than in Toronto... Could anyone give me some suggestion on how to make this choice? Any suggestions is appreciated! Thanks so much!

Update today, just received offer from CMU Stats Department! So happy! It is a hard decision to make between cmu and uoft though... Any suggestion is welcomed plz! Admitted: CMU Stats PhD (full-tuition + 3.1k per month) University of Toronto Stats PhD (full-tuition + 20k per year) Rejected: University of Washington Biostatistics PhD Harvard University Statistics PhD Upenn Biostatistics PhD

Got the first phd offer from UofT stats department! Still waiting for the results from those US schools, but not received any invitation for interviews yet... so I guess most likely I will stay at uoft for my phd.

Undergrad Institution : University of Toronto Major(s): Statistics GPA: 3.99 Minor(s): Mathematics, Economics Type of Student: International, Asian Male Courses taken and taking: Calculus!(97/100), Advanced Calculus (100/100), Probability & Stat I(100/100) , Probability & Stat II(97/100) , Linear Algebra I(100/100), Linear Algebra II(97/100), Chaos Fractals Dynamic system (100/100), Survey Sam & Observational Data (92/100), Meth Data Analysis I&II(both 95/100), Applied Econometrics I(95/100), Forecasting Econometrics(94/100) Stat Machine Learning I (88/100), Statistical Computation(100/100), Meth Multivar Data(83/100), Methods Applied Stat(100/100), Probability I (90/100), Time Series Analysis(86/100), Stochastic Processes (99/100), Theory Statistics Practice(100/100), Intro Real Analysis(Is taking right now) etc (Note: In my University, 90-100 means A+, 85-90 means A, and 80-85 means A-, where A+ and A are 4.0 but A- is 3.7. Most classes have averages C+/B- (around 2.7 to 3.0 approximately) ) GRE General Test: Q: 169 V: 159 W: 4.0 GRE subject test score: N/A Grad Institution: N/A Programs Applying: Statistics/Biostatistics PHD and a few Statistics/Biostatistics Master Research Experience: Actually, not a lot, just some projects that I have done for my classes or for some data competition if they count: 1. Time series analysis on number of active firms in different Canadian Industry. (Submitted for a competition held by Stats Canada, haven't receive any response yet) 2. Using Principal Component analysis and Support Vector Machine Classifier to quantifying and modeling the fatigue level of Canada's soccer's women national team. (Submitted for 2019 ASA DataFest, which is a comparatively famous data analysis competition, won Honorable Mention) plus some projects done during Stats courses Pertinent Activities or Jobs: Don't have some real relevant working experience sadly... Letters of Recommendation: Probably two from two Stats professors(from courses where I scored 100's or almost 100, know me reasonably well), and one from a math professor (also in a course where I scored 100, and I guess also know me reasonably well...) Hopefully that these recommendations letters will be strong as I frequently made appointments with these professors to discuss about my overall career plan and research interest. Research Interest: Bayesian Statistics/Machine Learning/Biostatistics/Times series analysis Applying to where: MS (will only go if all PHD rejected) UofT-Biostatistics, Stanford, Harvard-Biostatistics PhD: UCBerkeley, UWashington-Biostatistics, Havard, Carnegie Mellon, Yale, Duke, UMichigan-Biostats, UofT, UChicago My main worry is that I don't have a lot of real statistics research experience nor relevant working experience, and looking at other applicants profiles, I felt that probably my list of programs are too far for me? Also, I am wondering is that true that comparatively Biostats PHD program has a higher admission rate than regular Stats PHD program? If my list is too hard for me, please give me some suggestions on how to adjust that! Thanks so much!