Anonymous04

Student Type :- International Asian Male Undergrad Institute:- Regional College in India (pretty well known as one of the premier college in the State) Degree:- 3 Year B.Sc in Statistics Major:- Statistics, Minor:-Mathematics Major Percentage:- 100/100 Some Relevant Courses (Secured full grades in almost all courses):-Stat. Methods Sequence, Stat. Inference Sequence, Probability Sequence, Calculus, Mathematical Analysis, Linear Algebra, Numerical Analysis, Differential Equations, Abstract Algebra, and many other applied Statistics courses Other Relevant Information:- (1) Selected for 2 prestigious Summer Research Fellowships in India during 2nd year of undergrad. (2) Graduated with highest marks amongst all the students from all Science/Arts departments in my College. Awarded Gold Medal from the Chancellor Grad Institute 1:- ISI, Kolkata Degree:- Master of Statistics Concentration:- Applied and Computational Statistics Overall Percentage:-72/100 Relevant Courses (marks in brackets):- Stat. Inf-1 (58/100), Linear Algebra & Linear Models (84/100), Analysis-I (51/100), Regression Techniques (73/100), Probability Theory (75/100), Multivariate Statistics (75/100), Non-parametric & Sequential Methods (74/100), Large Sample Theory (69/100), Sample Survey & Design (64/100), Measure Theoretic Probability (66/100), Stat. Inf-2 (77/100), Pattern Recognition (70/100), Stat. Computing-I (91/100), Martingale Theory (73/100), Time Series (90/100), High Dimensional Statistics (58/100), Resampling Techniques (84/100), Game Theory (86/100), Stat. Computing-II (71/100) Other Information:-Did a 6 months project on 'Random Truncation Modelling of Air Traffic Control Data'. I secured 84/100 in the project. My project supervisor will be my main recommender in my PhD application. Grad Institute 2:- University of Paris Saclay/University of Paris Dauphine/Sorbonne (one among these) Degree:- 2nd year Master's Diploma (called M2 in France) in 'Applied Mathematics' Current GPA:- 14/20 Relevant Courses:- Advanced Learning (11/20), Convex Optimization (12/20), Optimization for ML (12.5/20), Graphical Models (13/20), Statistics for High Dimensions (12/20), Biostatistics (15/20), Applied Bayesian Statistics (15.5/20), Bayesian Nonparametrics & Bayesian ML (16.5/20), Machine Learning for Medical Data (17/20), Seminar on 'Machine Learning for genomics' (19/20) End-of-studies Master's Project:- Currently working with one senior professor on the topic 'Machine Learning Methods for GWAS and subsequent control of False discoveries.' I am not sure if I can get reco from the professor as he rather wants me to continue with him for PhD. Other Information:- Got a very selective fellowship from a French Maths Foundation to study my master's in France. GRE:- Not appeared yet, but practice test reveals around:- 170 Q, 152 V Other LORs:- One assistant professor from my alma mater in Paris who taught me a course. Rest all are from ISI. Possibly in some places I will add one from my undergrad alma mater too. Programs Aiming- Biostatistics:- UNC, UCLA, UMinnesota, Emory, Brown, Boston, UPitt, Penn State Statistics:- NCSU, UT Austin, UC Irvine, Colorado State, Rice Am I competitive enough for the schools I listed? Any specific suggestions or advice will be greatly appreciated. Thanks in anticipation.

I am foreign applicant (Asian) and have my previous master's degree from an Asian school which sends many students to top US schools. In particular, students having similar profile like me from my earlier institution could get into schools like Iowa State, FSU, UF, Ohio State etc. I will apply to PhD next year. Currently 23 years old. LORs are good and mostly will be from my earlier master's institute. I do not have any job. Currently doing an advanced master's degree (in DataScience + ML) in an European country (in one of the top university of the country; and with got a very competitive scholarship for all my expenses). I could get an competitive scholarship during my undergrad for an internship; but it was not any major work. In my earlier institution I had one master's project. Seems like in my current institution I will be able to do some more research projects.

Thanks for your suggestion. I was also thinking on doing some research projects to enhance my CV.

I already have a stellar academic background from my undergrad and master (with many courses on theoretical and applied Statistics, Probability and even courses like like Analysis, two courses on Measure Theoretic Probability, Advanced Linear Algebra etc. Marks are okayish, mostly A, and B here and there.) Presently I am doing one more master degree (just for fun as I got a generous scholarship and did not have to pay any tuition etc.) In my current master I am taking some more advanced classes like Probabilistic Graphical Models, MCMC Theory, High Dimensional Statistics, Non-Parametric Bayesian Methods, Convex Optimization Theory, Advanced Machine Learning; and even taking some more applied courses like Statistical Methods for Ecological Data, Spatial and temporal data, Machine Learning for medical data, Biostatistics, Clinical Trials etc. I was just curious about one question. Are performances in these recent courses are going to be a determining factor if I apply to PhD? Most of the important courses that is required for getting a good PhD are already covered in my previous undergrad and master. Actually I have to give time to some other activities due to some personal problems, and I want to relax little bit on my current courses (which might result one or two low grades in some of these recent courses and I am studying just before exam, and some of the courses will also have tough exams). If any of these courses are going to matter for my PhD application, could you tell me which? So that I can focus on those in the only free time I get. What my personal instinct says, Courses on Convex Optimization might be important and I should focus on it to get a good mark. Any suggestions?

I do not think professors from Statistics department would deny for recommendation. In the mean time you might discuss with your Economics professor also to get to know if they are encouraging you to apply for Statistics Program. If you are deferring for one year and can take all these courses I feel that you would be able to apply straight to a Statistics PhD program. In US most of the PhD program do not assume that you have a master's degree. There are master level coursework which you have to complete before you actually start working towards PhD. This is the normal route for any PhD program. Some program even allows you to obtain your MS degree by completing some more coursework. There is not any problem with applying for a double master but it might result some additional years for finishing your PhD.

Hello. Nice to see that you two are moving towards Statistics. I really forgot the maximum limit of the courses you are allowed to choose from MStat course list. However, I am afraid that you can take all of Analysis-I & II; Measure Theoretic Probability; Linear algebra & linear model as your credit courses during your MSQE. My suggestion will be to take Analysis I which will be delivered this fall (and I guess it is going to start soon. Stay tuned) and then try to take Measure on your last semester. But yes, if it is not too much for you, perhaps you can try taking the other two as non credit (provided your schedule allows you to do so). However, note that if you apply this year you will be able to show only two courses (viz. Analysis-I & Linear algebra) on your transcript as the other two will be delivered in the next spring. But that should not be a big problem. In fact most of our MStat seniors without measure theory have got selected in universities like Iowa State, Ohio State, Minnesota, UC Davis etc. But they had year long sequence of courses like Statistical Inference, Mathematical Statistics, a course on linear algebra & model and many more. So my personal felling is that it would be much more easier for you to get selected into a top 40 Economics PhD program this year rather than Statistics PhD. (Considering the universities where your seniors are accepted for Economics PhD, I suppose you already know why I am telling this) So, you are correct that attending an MS Statistics course would place you in a good competition for top PhD program. If you want to get in a Statistics PhD this year my advice will be to talk with your close professors (possibly your future recommendator) and ask them if they have any good university in their mind where you would be accepted with the background you have. They will be able to guide you properly whether you should apply for MS first. Taking subject GRE will be a very good option be it MS or PhD application. But I feel if the situation continues in this way it would be difficult to conduct the test this year as it is paper & pen based. Stanford has already waived subject GRE this year which was previously mandatory. I think you should get enough posts here which would tell you which MS program you should aim for. Alternatively, I hope some other would post it as a reply to your post. In US, funding may be a problem for the applicants of this year, specifically for overseas students. This is not my comment but the the graduate chair of one of the universities made this comment when we tried to contact him. So in such a situation the funding condition for MS programs (which usually faces dearth of funding) is still unclear. You should check out with the universities once you select them. For thesis based master's I feel that Canadian universities provide guaranteed funding. So you might be interested in applying in some of the universities like UBC, Waterloo, Alberta etc.

Dear All, I need a little helping hand from you. I suppose some of the users in this forum have a good idea regarding which universities have expertise on which field. So could it be possible for you to tell me which of the following universities' Statistics departments can be considered as a good option for a student who would like to end up doing PhD in the broad area of Computational Statistics. More specifically in the following areas:- Statistical aspects of Machine Learning (Statistical Learning), High Dimensional Inference & Data Analysis, Bayesian Computation, non-parametric methods, Topological+Functional Data Analysis, model-selection (say LASSO, penalized optimization related works). I would not expect but if anyone can provide a ranking (based on say the amount of people associated in these areas, reputation of the department considering these topics, Or the possibility of hosting a great research community in these areas in near future), it will be highly appreciated. I beg your pardon in advance as the list is not small and it may not be possible for someone to know about every nook and corner of each department. So, replies from several from users will be grateful who can at least tell what the department is good at. I hope the answers would surely help lots of people who are basically aiming for good (not the very top ones) universities in the above areas. The list follows. (1) University of Minnesota-Twin Cities, (2) The Ohio State University, (3) Iowa State University, (4) Pennsylvania State University, (5) University of Georgia, (6) UC Davis, (7) UCLA, (8) UC Irvine, (9) UC Riverside, (10) Rutgers University, (11) University of Connecticut, (12) University of Iowa, (13) University of Colorado, (14) Colorado State University, (15) Oregon State University, (16) Temple University, (17) Virginia Tech, (18) George Washington University, (19) University of South Carolina, (20) University of Texas-Austin, (21) Northwestern University, (22) University of Pittsburgh, (23) Rice University, (24) Florida State University, (25) University of Florida, (26) University of Illinois-Urbana-Champaign