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  1. Hey everyone! Hoping to get an idea of the strength of my application and chances of getting into some of the schools below for a PhD. Left school to work at a management consulting firm which I believe is a bit untraditional. Would also appreciate any school recommendations/adjustments to my current list, any thoughts welcome! Thanks Undergrad Institution: Top 10 University in Canada Major(s): Data Science GPA: 3.96 (Last 4 Semesters/2 Years), 3.96 (Major), 3.89 (Cumulative) Type of Student: Black International (Canadian) Male GRE General Test: Taking summer 2022 Programs Applying: Computer Science (PhD), Statistics (PhD), Operation Research (PhD) Research Experience: 2 first-author ACM conference papers (1 applied machine learning and has been cited, 1 data/text mining) 1 last-author conference paper (data/text mining; awarded Best Track Paper in Data Analytics and Big Data) 1 journal publication in geospatial statistics (submitted) Other research in applied machine learning and finance (no publication) Awards/Honors/Recognitions: Gold Medal (graduated with the highest GPA in Major, top of the class) Undergraduate Fulbright Fellowship Letters of Recommendation: One strong letter from an Associate Professor in Statistics & Management Science who I wrote the geospatial statistics paper with (not well-known in CS) One strong letter from an Assistant Professor in Data Science & Business Analytics who I published two papers with in data/text mining (not well-known in CS) One decent/strong letter from an Associate Professor in Economics & Statistics who I performed research with (~1yr together) but no publication One strong letter from a Partner at my management consulting firm (relevant for Operations Research programs) Computer Science Courses: Intro CS I & CS II, Data Structures & Algorithms, Software Tools & Systems, Discrete Structures/Discrete Math, Analysis of Algorithms, Databases I, Data Science I Math/Statistics Courses: Probability & Stats I & II, Statistical Programming, Calc I, Calc II, Intermediate Calc I, Intermediate Calc II, Linear Algebra I, Linear Algebra II, Numerical Analysis, ODEs, Modelling and Simulation, Regression, Generalized Linear Models, Advanced Statistical Computing, Statistical Learning Any Miscellaneous Points that Might Help: Particularly interested in doing research within the field of Machine Learning (and potentially NLP), still figuring this out. Not particularly interested in CV or RL. Would have spent >1 year at a management consulting firm at the time of applying and >2 years by matriculation (a advantage/disadvantage?) Applying to Where: In no particular order here, CMU - PhD in Machine Learning University of Washington - PhD in Computer Science Columbia - PhD in Computer Science MIT - PhD in EECS Princeton - PhD in Computer Science Cornell - PhD in Computer Science NYU - PhD in Data Science UIUC - PhD in Computer Science UT Austin - PhD in Computer Science UPenn - PhD in Computer Science UC San Diego - PhD in Computer Science UCLA- PhD in Computer Science Georgia Tech - PhD in Machine Learning UMichigan - PhD in Computer Science CMU - PhD in Statistics University of Washington - PhD in Statistics Stanford - PhD in Statistics* Cal Berkeley - PhD in Statistics UPenn - PhD in Statistics Yale - PhD in Statistics & Data Science Stanford - PhD in Statistics Cal Berkeley - PhD in Statistics UPenn - PhD in Statistics UMichigan - PhD in Statistics CMU - PhD in Operations Research MIT - PhD in Operations Research Georgia Tech - PhD in Industrial and Systems Engineering UMichigan - PhD in Industrial and Operations Engineering Thanks again!
  2. I completed my undergraduate in Electrical Engineering in 2021. Since then I have been working as a researcher in a research unit in India. I also have worked as a research volunteer for two labs until now. My research interests lie in Computational Neuroscience and Brain-Computer Interface. I wanted to apply for PhD in ECE/ Biomedical/Bioengineering department in US. The schools I have shortlisted are Gatech, UC Davis, UCSD, UT Austin, UCSF-UCB joint graduate program, CMU, University of Washington, UMich, Boston University, UPitt. GPA: 3.5 Profile: 2 years of research experience working in a research unit, although not related to the research I want to pursue my PhD in. To compensate for that I remotely worked as a research volunteer for two labs (One in Donders Institute and the other in Georgia Tech) Participated in several international hackathons and came in the top 3. Completed two industrial internships in startups and one research internship in NTU Singapore during undergrad. 3 strong LORs (one from a professor who taught me in undergrad and two under whom I did my volunteer research assistantship) Completed summer schools based on Neuroscience. Unfortunately I don't have any research papers. Which colleges would I have a good chance of getting into and should I add more good schools to the list where I have a good chance based on my profile?
  3. Undergrad: Top4 University in South Korea ( Sungkyunkwan University) Grad: current graduate std in the same university Major: Statistics GPA: 4.21/4.5 (undergrad,96.6%), Major GPA(4.33/4.5), 4.44/4.5( grad,99.5%) Type of Student: international Asian male GRE: Q: 166 (86%) V: 154 (63%) W: 4.0 (54%) TOEFL: (RLSW) 30 26 22 24 = 102 Program: Statistics or biostat PhD Research Experience: 1 published paper in Korean stat journal / 1 paper submitted / 1 paper in preparation two projects funded by national research institution of science 1 selected presentation in Korean Statistical society meeting LOR: One from my advisor(associate prof) in grad school, one from a korean assistant professor in US( I did a project with him or her), one from a professor( I took lectures from her or him) Under grad Courses: Calc 1 (A), Lin Algebra (A+), Analysis1 (A+), Matrix Algebra (A+) , math for statistics(A+: Calculus) , Intro of statistics(B+), Linear regression(A+), mathematical stat(A), statistical programming(B+), statistical Inference(A+: math stat2) , statistical data mining( A+), insurance statistics(A+), stochastic process(A), Experimental Design(A+), econometrics(A+), time series analysis(A+), Multivariate data Analysis( A+), Large data management and visualization(A), statistical simulation(A+), categorical data analysis(A+), spatial data analysis(A) Grad courses: advanced mathstat(A), advanced linear regression(A+), Advanced Multivariate statistics analysis(A+), Advanced math stat2(A+), advanced datamining(A+), Probability Theory(A+), Large sample theory(A+), bayesian statistics(A+), Convex Optimization(current) TA: intro to statistics / datamining / machine learning and statistical modeling/ statistical simulation / sample theory / basic and application of AI / BigData and Machine learning Awards : 5 awards of big data contest / 3 times Dean’s list Notes: What programs would be a reach/match/safety for me? I’m worried about my math background and English standard test scores.
  4. Background: International student Female Bachelor's in Statistics with hons: 3.5 gpa( converted from Percentage) from tier 1 public university with coursework in linear algebra, calculas, numerical and real analysis etc. Masters in Statistics: 9.6 cgpa on a scale of 10 from a tier 2 private university with 10 in calculas, algebra, linear models, Design of Experiments, Biostatistics, multivariate analysis, Demography,Statistical Inference. Research experience: 1.Did a thesis project for final semester applying mathematical model to demographic rates. 2.Worked as a research assistant for 8 months at a government organisation but not very relevant experience or publication from it. I've graduated first in class in my master's program and have been awarded a national scholarship based on academic merit. Currently working as a Statistical analyst. GRE: not taking( applying to programs not requiring GRE. LORs: Three from my professors including the professor who was my project guide. I'm thinking of applying to PhD Biostatistics/ Statistics programs. My whatsoever little research experience is related to Biostatistics and it interests me the most. The programs I've selected so far are among the top 10 programs in Biostatistics Kindly suggest some schools which are not very ambitious and some safety schools for PhD Statistics. Thank you. I'm reposting this question since there was no reply on the previous one, maybe I missed some information. Any response is very much appreciated
  5. MS Biostatistics student looking for advice! Undergrad: top 30 LACs -- Statistics, Data Science (summa) Grad: MS Biostatistics Ivy League (not Harvard) Type of Student: International female GRE General Test: Q:170 V: 160 W: 5.0 Applying to: Biostatistics PhD Research Experience: Right now, projects on survival analysis (both applied and methodological) with a senior researcher -- not sure about potential publications! During undergrads, did summer research at a well-known cancer hospital and an institute for applied maths, and 2 year research at school. Letters of Recommendation: Two faculties with whom I'm doing/planning to do research with at grad school; one might be from profs teaching classes or undergrad studies who knows me very well Grad coursework: Same core coursework as PhD students -- using Casella and Berger for Probability and Inference. Have the option of taking the qualifying exam after 1st year (this coming June) with PhD students Publications: one conference paper on machine learning/applied maths from undergrads summer research. one coming up on using nonparametric tests for an applied project. Co 1st author for the former. Plan to apply: UPenn, BU, Columbia, Yale and maybe Harvard -- I want to stay in the northeast, New England preferably Can someone give me advice on the my school list? After my PhD I might go back to Asia where people care a lot about prestige and brand name of the school, rather than dissertation advisors. I realize this list is ambitious and would appreciate if someone can recommend some "safe" schools. Many thanks!
  6. Hi all, would really appreciate some input on both a profile evaluation and advice on whether to pursue a (second) master's, or a PhD. Motivation: I'm a lifelong learner - have always enjoyed my time in education and just learning - and deeply driven to pursuing careers that can shape policy or drive some sort of greater systemic change and public good. Whilst I don't really have an intention to stay in academia or go into teaching, I feel like there's still so much I could gain from having a more robust theoretical foundation in politics and theory, to be able to analyse and grasp policy (as well as human rights/IR issues) with more nuance and depth. In terms of careers, I'd love to end up in public policy, government, non-profits, or perhaps Think Tanks or related research. Basically, I'd love to learn the subject at a higher level than I currently have and I think I could do well and really grow as a person and researcher, but at the same time, I don't foresee a life in teaching or academia for myself, as I don't think that's where I can make the greatest impact. I'm in my mid-20s, and feel like if I want to do a PhD (or a second Master's) then now is really the time, as I think I'd be able to easily make the mind-set shift back into academia. Profile: Undergrad Institution: University College London (UCL), First-Class Honours Majors: Focussed on politics, legal studies, and Italian language primarily, whilst taking classes on Qualitative Thinking, Quantitative Methods, and Interdisciplinary Research Methods. GPA: First-Class Honours as well as a year abroad at UC Berkeley where I had a 4.0 GPA. Master's degree: MPhil in IR & Politics from University of Cambridge (awarded with a high Merit, 2 marks off a distinction). Work experience: Around 3 years professional experience. Most notable roles include Coordinator for Special Projects at a private not-for-profit University in the UK, a Fellow with an International Human Rights Programme (philanthropy related) and I'm now moving onto a role as an Analyst with a socially-minded consulting company. Languages: Italian (intermediate although I have an 'A' in 'Advanced Italian') and Farsi (relatively strong, terrible writing skills) Recommendation Letters: I had a really strong relationship with a UC Berkeley professor (took 2 classes, strong marks, and frequently went to office hours) who I might reach out to, as well as my MPhil Supervisor. Unsure on the third. Research Interests: A mixed bag. My background is in international politics (primarily in the Middle East), but I'm also interested in authoritarianism, labour activism, and human rights. Programs considering: PhDs - Political Science, mostly UC Berkeley Political Science or even possibly Jurisprudence and Social Policy Harvard Government NYU Politics (particularly tempting for the 1-year Master's waiver) Yale Master's Princeton MPA UC Berkeley MPP Harvard MPP I spent a wonderful year at Berkeley, loved the professors and the atmosphere, and know they have a really strong bent towards more social causes. Harvard and Yale are also tempting because of the Carr Center and Schell Center respectively. NYU offers the 1-year waiver for Master's degrees, which is also really appealing. I think I'd love an MPP or MPA - I'm a practical people-person (despite my love of academia) and want to be able to build my professional skills too. I love the whole course structure of the MPP (or MPA) and think I'd learn so much. But funding is a massive issue, especially as an international student, hence why Princeton is top of the list. I know these are massively competitive programs and institutions - as an international student, I think global reputation/brand is unfortunately quite important to me, as is the location. Really happy to consider alternatives though. I've also paid some thought to Columbia, or Chicago. TL;DR: Torn between pursuing a very expensive but fulfilling second Master's degree, or a rewarding but lengthy PhD that might not be hugely helpful to my career. Advice and profile eval would be really helpful please, and happy to add/clarify anything!
  7. From: India Background Undergraduate Institute- Top 3 for Math in the country Major- Math Minor - Physics Grades- 9.5/10 Relevant courses(with grades): Analysis 1,2,3(10 in all); Algebra 1,2,3(9,10,8); Probability(10); Calculus(10); Differential equations(10); Complex Analysis(10); Topology(7); Stochastic Processes 1,2(10 in both); Optimisation(10); Game theory(9) + Physics courses(overall physics courses 9.4/10) Masters: Top1 institute for statistics Overall percentage-82 Coursework(with percentage): Regression(62); Statistical Inference(84); Linear algebra and linear model(77); Analysis1(95); Probability(90) Currently taking- Analysis 2, Measure theoretic probability, Optimisation, Multivariate Analysis, Large Sample Methods Courses to be taken - Martingale theory, Functional analysis, Time series analysis, Large Deviations theory, Brownian motion and Diffusions, Weak convergence and Empirical processes, Percolation theory, Advanced functional analysis Projects: No research projects - only reading projects in 1. fourier series 2. mixing times Gre- not taken Toefl- not taken Applying for- Phd Statistics(focusing on probability) Suggest some schools and also any advice is welcome.
  8. Applying for PhD in statistics/biostatistics after working in industry for a few years as a Data Scientist - would appreciate any thoughts, feedback, or advice on programs below given profile/research interests. Undergrad Institution: US Top-5 in Statistics Majors: Statistics, Applied Math GPA: 3.91 Type of Student: International Male Math Courses (All A's): Real Analysis, Complex Analysis, Linear Algebra 1/2, Abstract Algebra, Numerical Analysis, Differential Equations, Calculus 1/2/3, Discrete Math Statistics Courses (All A's): Stochastic Processes, Time Series, Experimental Design, Linear Modelling, Data Science 1/2, Probability Theory, Statistical Computation Computer Science (All A's): Algorithms, Machine Learning, Deep Learning, Databases GRE: 168 Q | 163 V | 5.5 W Research Experience: 2 years in applied statistics (3rd author publication in lower-tier journal - did most of the coding), 1 year in sociology (no publications - mostly database management) Work Experience: 3 years as Data Scientist at large tech company Recommendation Letters: 2 from research advisors (strong letters), 1 from professor with multiple classes and strong performance (mediocre letter) Coding Experience: Python (expert), R (experienced) Research Interests: Causal inference, applications to social sciences (specifically education/public policy), applications to public health policy Programs Considering: UC Berkeley Stats PhD Harvard Stats PhD CMU Stats PhD UCLA Stats PhD UC Santa Barbara Stats PhD Harvard Biostats PhD Penn Biostats PhD Brown Biostats PhD MIT Social & Engineering Systems PhD NYU Data Science PhD Are there programs here which don't sound like a great fit with my interests and profile, or any not here which could be a fit? I recognize my list is a top-heavy, but I'm satisfied at my current industry job and would go back to school only for a relatively well-regarded program, with the end goal of tenure-track professor at a R1.
  9. Undergraduate Institution:Top 3 in math in India Program: B.Sc Hons. Major:Math and Physics Grade: 9.5/10 Type :International Asian Male Courses with grades: Analysis 1(10),2(10),3(10); Complex Analysis(10);Probability(10),Algebra 1(9),2(10),3(8);Calculus(10), Differential equations(10) ,topology(7),optimization(10), Game theory(9), Stochastic processes 1(10), 2(10) Masters Institution: Top stats program in India Major: Statistics with probability specialisation Percentage:84%(At time of application) Math courses with percentages: Analysis 1(95), Probability theory(90), Measure theoretic probability(90), Analysis 2(90), Optimisation(90) Stat courses: Statistical Inference (84), regression(62), Linear algebra and linear models (77) Courses I'll take next semester before the applications: Functional Analysis, Martingale theory, Time Series Analysis GRE(general): 169 Quant, 150 verbal GRE(Math)-Cancelled due to covid Research Project- None (have done some reading projects) LOR: Expecting 2 decent recommendations and 1 strong Programs applying: Phd Math focusing on Probability (Would also like to work on interdisciplinary fields with emphasis on probability if possible) School: Please recommend the range of school I should look for.
  10. Hi, I graduated with a bachelor of technology degree in Electronics from VIT Vellore, India in 2016 and have been working in statistical modelling/predictive analytics related profiles since then. I took various mathematics electives in college and enjoyed learning about different branches, and their applications in industry. I enjoy working on lot of versatile projects but over time, I realized that I am not learning anything in depth. Online courses related to statistics touch topics in a superficial way (no offence) and I would want to study some topics in depth, and pursue research. hence I am interested in applying for masters (thesis based) in statistics/PhD in statistics, starting fall 2022. Interest area - Missing data and methods of imputation, Parametric Methods BTech GPA: 7.92/10 GRE: 165Q, 159V, 4 AW Relevant Courses: Probability and Random Processes (calculus based) - S: Department topper for the course, also worked at TA with a professor in this course Multivariable calculus and differential equations - B Differential and Difference Equations - A Complex Variables and PDE - B Information Theory and Coding - B Applied Numerical Methods - B Numerical Analysis - B As you can see, my grades are average. Back in college I was not planning to study further and did not do much to improve GPA, focused more on only the courses I really liked. Research: - One research internship at a medical devices private firm for 4-5 months post college. It was in their R&D wing, worked on applications of statistics in diagnostic imaging. Not published. Projects: - Plenty of projects related to statistical methods, mostly around building parametric models. Some in traditional ML methods (Not Deep Learning). All done while in industry. None published. Other skills: Python, SQL, R, DBMS,SAS, Implementing models using Python. Remarks: Currently working in the same role. Realistically, I would not be getting a direct PhD (partially or fully funded) because of lack of solid background and no research work. Ques 1 - I'd like to get some input on my decision to start with MS in statistics with thesis work. I am not interested in Business Analytics/Data science programs as I looked at their courses and I have already self-studied most of it during my industry stint, it won't add much. I eventually plan to moving to a PhD in the same (unless I realize I am pathetic at it, then I could try for industry jobs). Ques 2 - I have put together a list, where I have looked into schools' research and their faculty profiles. I liked some good ones but they are out of reach, like UoW. Please suggest some schools accordingly too: My list so far is A - TAMU, Ohio State, UNC chapel hill, NCSU; M - UTD, ASU, Oregon State, Oklahoma State; Safe - Univ of Kentucky Lexington, University of Houston, University of Nebraska-Lincoln Its not a pretty profile but there are all kinds of people in the world, some of us wake up late but we try. I tried asking this ques in other places and got bashed for some reason. Thanks.
  11. Phd Financial Economics/ Economics Evaluation ( Planning to Apply Fall 2021):GRE: Yet to Take ( Planning to take in June)TOEFL: Yet to take ( Planning to take in June)Undergrad: NIT Durgapur'2017 ( Chemical Engineering)- 8.20/10Grad: IIM Indore'2019 (Top 5 in Management as per NIRF ranking published by Ministry of Human resources India)-MBA ( 3.38/4.33, Top 35 out of 540, Don't have a proof yet but I am trying to get one from Admissions Office)Courses & Grades:1.Mathematics I :Functions of Single Variable,Functions of several variables,Integral Calculus, Multiple Integral, Vector Calculus, A (9/10)2.Mathematics II:Liner Algebra, Ordinary Differential Equations,Fourier series,Laplace and Fourier Transforms,Probability A (9/10)3.Mathematics III:Partial Differential Equations (PDE),Numerical Method,Complex Analysis,Optimization: Mathematical Preliminaries: Hyperplanes and Linear Varieties; Convex Sets, Polytopes and Polyhedra,Linear Programming Problem (LPP)A (9/10)4.Advanced Numerical Analysis: Eigen Values A(9/10)5.Probability & Statistics:Random Variables and Associated probability distribution,Sampling Distributions and Statistical Inference, Hypothesis testing,Simple Linear Regression Analysis A (3.783/4.33)6.INTRODUCTION TO QUANTITATIVE DECISION MAKING:LINEAR PROGRAMMING,DECISION TREES,EXTENSIONS OF LINEAR PROGRAMMING: IPP AND MILP,APPLICATIONS OF LINEAR PROGRAMMING, B (3.367/4.33)7.Microeconomics Introductory Microeconomics Course A (3.867/4.33)8.Macroeconomics Introductory Macroeconomics Course A (3.917/4.33)9.Economics of Strategic Interactions Market Structures and Organization,Review of Competition and Monopoly,Homogeneous Goods,Heterogenous Goods,Concentration, Mergers and Entry Barriers, R&D,Advertising, Quality, Durability and Warranties; readings from Industrial Organisations A ( 4.1/4.33)10.Macroeconomics of Developing economies:Growth Models ( Solow etc)A ( 4.1/4.33)11.Financial Markets & Central Banking:Stabilisation Policies in Closed and Open economy IS-LM Models,Monetary policy transmission mechanism, Credit Channel Expected Inflation and Monetary Dynamics, Optimum Policy Target,I nflation targeting B+(3.433/4.33)12.International Finance:Balance of Payment, Exchange Rate, Drivers of Exchange Rate and,Foreign Exchange Market,International Parity Conditions: Interest Rate Parity,Foreign Exchange Risk Management,Hedging B (3.1/4.33)13.Corporate Finance- Corporate Finance I (A) Corporate Finance II (B)14.Investment Analysis & Portfolio Investments (B)- Portfolio Management15.Equity Financing (B)- IPO/FPO/PE/VC 16.Practicing Corporate Valuation B- DCF/ Relative / M&A17.Corporate & Retail Banking B- RWA calculation, CaR Ratio, Asset Liability Management, Basel NormsResearch Experience:1. IIM Indore: Microeconomics - Course of Independent Study Project- Given Presentation to Economics Department ( Awarded a credit ). Was working on the paper but it is still incomplete not sure if it is going to be completed before I apply.2. IIM Indore: Live Project ( Cost Analysis) with Idea Cellular (before the merger of Idea & Vodafone) -Worked in a group although- Term Paper submitted3. NIT Durgapur: Not relevant to econ research. Have a paper published (co-authored) in chemical Engineering in Springer ( impact factor 1.47) and a chapter (co-authored) in a book.4.NIT Durgapur: Final year Thesis (Chemical Engg) (In a group)Work experience: Deutsche Bank ( almost 2yrs) - Corporate Banking AnalystAlso, I am CFA L1 candidate- Hoping to pass!LORs:1. Microeconomics Professor -IIM Indore under whose supervision I completed the Microeconomics project2. Macroeconomics Professor- IIM Indore- Who took courses3. Statistics Professor - IIM Indore - Who supervised the Live projectConcerns: I know my profile is lacking in the following: RA ships, Not enough math/econ courses. I am planning to take up online econ/math courses ( real analysis, measure theory) and R/ Stata courses as well. Which kind of certifications will be considered by admissions committee ( any course certification from US univs?) Can someone specify some certification courses covering the above topics which can compensate for the lacking in maths/econ courses?I do know I like research , but till now most people have suggested me to go for a Masters rather than a Phd. is there any hope for me to get into a PhD econ program with this profile?Kindly suggest some schools I can apply to for both Phd & Masters in econ/ Financial economics where I might have a chance!Thank You!
  12. Hi! I am planning on applying to various Master’s in Statistics programs for Fall 2021, but I am somewhat uncertain of my chances of being accepted into these programs. Type of Student: Domestic White Male Undergrad Institution: Regional university that is top 10 in its region Major: Applied Mathematics and Statistics GPA: ~3.2 Overall GPA, ~3.6 GPA each in upper division coursework and last 60 semester credits of coursework, ~3.7 Major GPA Courses in Major (In order from freshman to senior year): Calc II (B+), Statistics I (B+), Calc III (B), Actuarial Statistics I (B), Actuarial Statistics II (A), Linear Algebra (A), Advanced Probability (B+), Econometrics (A-), Software Application for Mathematics (B), Statistics II (A), SAS Programming and Applied Statistics (A), Statistical and Mathematical Decision Making (A), Applied Mathematics and Statistics Capstone Seminar (A) Programming: I have mainly used Stata, but I also have a small amount of familiarity with SAS and SQL Q: 168 (92nd percentile) V: 155 (67th percentile), 159 (82nd percentile) when super-scored W: 4.5 (80th percentile) Programs Applying: Master's in Statistics Research Experience: I am currently working on a single-authored publication manuscript that is in the revision stage and that was submitted to a low-impact factor journal. I do not anticipate resubmitting my manuscript until after I apply to most, if not all, of my desired programs. I also performed research for my capstone project, which I presented at my school, but I am much happier with my manuscript. Both projects contain significant amounts of statistical analyses. Work Experience: I have approximately 2 years of full-time work experience as a Research Analyst at my alma mater. I also have approximately a year and a half of part-time internship and contract experience performing varying degrees of data analysis. Letters of Recommendation: One recommendation is from the head of the mathematics department at my alma mater who oversaw my math placement test, who I took one of my statistics courses with, and who was slightly involved in one of my internships, another recommendation is from another statistics professor who I took a few classes with and who was my advisor for my capstone course and project, and the last recommendation is from the editor of the journal which I submitted my manuscript to. I am not expecting my letters of recommendation to be anything out of the ordinary, but I am uncertain as to what the strength of two of them will be. Research interests: I am the most interested in environmental statistics and public policy analysis. To a lesser extent, I am also highly interested in data science and Bayesian statistics. School List: University of Chicago Duke University of Wisconsin UCLA UIUC University of Missouri Oregon State UC Santa Cruz Currently, I am also considering Ohio State and Virginia Tech. As far as I know, every school on this list, with the exception of Chicago, Duke, and Ohio State, does not take overall GPAs into consideration, but instead, only looks at grades in math & stats courses and either GPAs concerning last 60 semester hours of coursework or grades in upper-level coursework only. I know that Duke super-scores the GRE, UIUC probably does as well, and Virginia Tech is considering it, whereas either the rest of the schools only take the most recent GRE scores into account or I do not know what their specific policies are regarding GRE super-scoring. I am wondering what my chances of admission are for each of these institutions, and if there are any details that I may be overlooking that may factor into my chances of admission within any of these schools? It should be noted that while evaluating my chances, it has been approximately 8 years since I last took academic coursework of any kind. Are there any schools that I am overlooking that may also be good fits for me, and is there any reason for me to believe that any of the schools on my list are not good fits? Ideally, I would like to join a Master’s in Statistics program that has had a high degree of job placement success in the past compared to other Master’s in Statistics programs, that has the best networking opportunities for Master's in Statistics students and alumni, and that has a mixture of both theoretical and applied statistics courses. I plan on entering industry once I graduate, but a PhD is not completely out of the question.
  13. BS Electrical Engineering from country's top college graduated 2019 with one extra-year GPA 3.0 GRE (168 quant, 155 verbal, 3 analytical) 1 year research experience Decent Letters of recommendation TOEFL 113 No publications so far What kind of grad school can I target? Is it worth applying to U of Alberta in Canada? What can I do to improve my chances now? How can I build a stronger profile going forward?
  14. Hi everyone! I'm reapplying to Neuro PhD programs after an unsuccessful round in senior year of undergrad (F2019). I only applied to Pitt, Vanderbilt (waitlisted for interview slot), Columbia, and Johns Hopkins. 2 years later, I now have some more research experience and focus on what I want to do as I'm in my 2nd year in an NIH IRTA postbac. I'm interested in behavioral neuroscience, neuroendocrinology and psychiatry. Any help in judging my stats against the schools I'm applying to would be seriously appreciated! Stats Undergrad: Dual B.S. degrees in Psychology and Cog & Behavioral Neuroscience with a 3.62 overall GPA (In major 3.92 for Psych and 3.52 for Neuro) at an R1 Mid-Atlantic university. I had Bs and Cs in gen chem and gen bio and never took physics. I took a semester of OChem senior year and got a B-. GRE: 156 Q, 156 V, 5.0 AW (most likely will omit in applications where it's not required) Research: I have completed 2 years of undergraduate research in a drug addiction/behavioral pharmacology lab, including one summer of full time work through a fellowship. By matriculation I will also have 2 years of full time work in a drug addiction/neural circuits laboratory at NIH. I will have one manuscript submitted before applications (2nd author) and have presented 3 posters/conference presentations. White female, US citizen Rec letters: one from my current PI, one from my undergraduate PI, and one from a well known PI/director of my current branch Other relevant info: I have some connections to PIs at a few of these schools and plan to reach out to them after I submit my applications. Schools I'm planning to apply to, in no particular order, all for Neuro PhDs: Yale, UCSD, NYU, WashU, Stanford, Harvard, Icahn/Mt. Sinai, Ohio State, Pitt, Vanderbilt, Johns Hopkins, Michigan, and Brown (13 total) At each of these schools, I've identified PIs who have research closely aligning with my interests. School's I'm still considering applying to: Cornell, CU Boulder, Duke, UVA, UPenn, and MIT (5 total) I don't see putting out more than 15 quality applications and contacting an appropriate amount of PIs (~1-3) at each school feasible. I'm open to any other schools you might think I should consider! Thanks again!
  15. Hey everyone, I've decided to apply to master's programs in statistics/data science this fall. I'm looking for some feedback on my current school list, as I'm not quite sure how to gauge my chances at some of the schools. Here's my profile: Undergrad Institution: UC Berkeley Major: Statistics GPA: 3.74 Type of Student: Domestic White Male GRE General Test: Q: 166 (87th percentile), V: 166 (97th), W: 5.0 (92nd) Programs Applying: Master's Statistics (maybe some data science programs as well) Research Experience: I had a negative research experience with a professor, and I ended up not passing the "research apprenticeship." Should I address this in my apps? Work Experience: I was a data analyst intern for a baseball team after my sophomore year (used lots of R and SQL). In summer 2019 I was a business analyst for a pro soccer team (mostly used Excel). Was hired to be a data analyst for a pro baseball team this year, but that got canceled due to COVID, hence why I'm applying now. I've been at home for the past few months and have been working on my own personal projects that I've posted on GitHub and a personal website. Awards/Honors/Recognitions: I was a TA for Berkeley's Intro to Data Science course, which involved me teaching weekly lab and discussion sections of 25 students and participating in weekly meetings about content and logistics. I taught topics like python, SQL, pandas, linear regression, and PCA. I did this my last semester. Letters of Recommendation: Should get a strong letter from my Game Theory professor and from one of the professors I TAed for, which will be weaker but still decent. The third letter will probably be the weakest, as I'm asking someone from the pro baseball team that hired me this year (but I never worked for) to speak on my performance in coding challenges/interviews for them. We formed a good relationship at least. Math/Statistics Grades (freshman-senior year in order) Intro to Linear Algebra and Differential Equations (B), Calc III/Multivariable (A), Calc-Based Probability (B+), Computing with Data (basically an R class) (A+), Discrete Mathematics (intro to proof-writing as well) (A), Theoretical Linear Algebra I took one summer at UCLA (A), Intro to Real Analysis (B), Calc-Based Mathematical Statistics (B), Fundamentals of Data Science (the class I TA'ed for) (A-), Intro to Time Series (A), Linear Models - Theory and Applications (A), Game Theory (A), Intro to Machine Learning (very theoretical) (A). Regarding my grades, I definitely didn't do as well as I would've liked in some of the fundamental stats courses (probability, mathematical statistics). But, my senior year I got all As in my stats courses which I hope this shines through. There may be some weak spots in my math grades too, like my Linear Algebra and Diff EQs class, but that was my first semester and I like to think my A in the summer Linear Algebra class makes up for it. Real Analysis was really tough and showed I don't want to do a PhD. Schools: Below is my current list of 13 schools, which is already a lot. If you have any recommendations based on my profile, I'm all ears. Basically, I need to know if it's not worth applying to some, if I have enough safeties, and if I should consider swapping out some for other programs. I'm also interested in applying to a couple schools in Europe... please let me know if you know anything about this in general/ETH Zurich/Oxford. Thank you! - Stanford, MS Statistics - UChicago, MS Statistics - Berkeley, MA Statistics - Harvard, MS Data Science - Washington, MS Statistics - CMU, Master's Statistical Practice - UNC Chapel Hill, MS Statistics and OR (apparently now it's called MS Data Science and Analytics...) - UCLA, MS Statistics - Yale, MA Statistics - Duke, MS Statistical Science - Rice, Master's Statistics - ETH Zurich, MSc Statistics - Oxford, MSc Statistical Science
  16. Hi! I'm a rising senior this upcoming semester and planning to apply for Stats PhD programs (possibly Biostats as well). I'm mostly interested in doing research in bayesian statistics / machine learning and survival analysis, but that could change. I'd appreciate any suggestions on reachable schools with my application. I prefer programs in East Coast, especially New England and West Coast. Thanks for your input! Undergrad Institution: top 30 LACs Major(s): Statistics Minor(s): Computer Science GPA: Current 3.83 (might be able to reach 3.86 by the time applying) Type of Student: International female (attending US college) GRE General Test: Q:170 V: 160 W: 5.0 Applying to: Statistics/Biostatistics PhD Research Experience: have done 1-year research in statistical methodology in multivariate analysis; had to wrap up because of covid. Am doing summer research internship (at a well-known cancer hospital) in survival analysis and longitudinal analysis which I plan to turn it into a senior thesis. Letters of Recommendation: One from my current mentor - a scientist at the research center, one from the former prof that I worked with for my previous research; one from my CS prof. I'm thinking of asking another one from the prof I requested to be my thesis supervisor. Math: Multivariable Calc (A), Linear Algebra (A), Discrete - proof based (A), Probability (A), Mathematical Statistics (A) Statistics: Applied Regression/Statistical learning (A), Methods in Data Science (B+), Nonparametric Stat (A), Experimental Design (B+), Exploration of Time Series (1 cred - A) CS: OOP in Java (B), Data Structures (B), Algorithms (A) Planning on taking: Real Analysis, Optimization, Theoretical Math Stat (grad-level) and Machine Learning this fall. Planning on Applying to: I really have no idea what schools are reachable. I originally planned to become an investment banker and switching to research was a big career change to me. Rankings do not matter to me as much as locations and the working environment. I don't plan to take GRE Subject Test. Can you guys give me some recommendations on schools that I might be able to reach given my application and preference. Thanks for your help!
  17. Undergraduate Institution:Top 3 in math/stat in India Program:Bachelor of Science Major:Math Percentage:74%(Major)(Known for grade deflation) Type :International Asian Male Math/Stat courses: Analysis 1(100),2(71),3(75),Probability 1,2,Algebra 1,2 ,linear algebra ,topology,optimization,differential geometry,differential equation,complex analysis,stat 1,2,3 Masters Institution:Same above Major:Math Percentage:73.6%(At time of application) Math courses:Measure theory,several variable calculus,algebraic topology,functional analysis... GRE(general):will appear,expecting good score in quantitative section GRE(Math)-Cancelled due to covid Research Project-None lor :Haven't asked,expecting average Programs applying: Phd Statistics(Would like to work on interdisciplinary fields with emphasis on probability) School:Please recommend the range of school I should look for with enough flexibility to do intra departmental work.Any suggestion is welcome.
  18. Type of Student: International south asian Undergrad and grad Institution: Top public university in Bangladesh Major: Applied Statistics GPA: 3.97 , class topper (BSc) GPA: 4.00 , class topper (MSc) GRE General Test: 152 V/ 163 Q/ 4.0 AWA IELTS: 8.0 overall Programs Applying: Statistics/ Biostatistics PhD Research Experience: 1. One project on structural equation modeling with application in econometrics ( published) 2. Thesis on bias reduction with penalized likelihood approach for small or rare event data in AFT models (under review) Teaching experience: Lecturer at a university Awards/Honors/Recognitions: Dean's award, CASc (ISCB41), CFDC (ISCB40), other departmental awards Letters of Recommendation: Two from my project and thesis supervisors, one from one of my professors Math/Statistics Grades: Calculus (A+), Real Analysis (A+), Mathematical Analysis (A+), Basic and Linear Algebra (A+), Statistics (A+), Probability (A+), Statistical Inference I (A+), Statistical Inference II (A+), Regression (A+), Multivariate analysis (A+), Design of Experiments (A+), Econometrics (A+), Generalised Linear models (A+), Bayesian Statistics (A+), Survival Analysis (A+), Longitudinal data analysis (A+), Machine Learning (A+) Programming/ Software skills: R, STATA, MATLAB, Python (basic) Research Interest: Mixed effect models, Survival analysis, Statistical Learning, High dimensional data analysis Note: Weak points: GRE scores (though not planning to retake), limited research experience Schools: I am confused about the competitiveness of my profile for stat/biostat PhD as an international student. Any suggestion about the range of schools I might have a good shot at would be very helpful. Here are some schools I am planning to apply, 1. JHU (Biostat) 2. Upitt (Biostat) 3. Uflorida (Stat) 4. Purdue (Stat) 5. TAMU (Stat) 6. UCI (Stat) 7. UCSB (Stat) 8. UMass amherst (Stat)
  19. Type of Student: International (Canadian) Undergrad Institution: Top 5 Canadian University Majors: Honours program in Comp Sci. + Stats Minor: Physics GPA: 3.75 GRE: 160V/164Q/4.5 Research Experience: 3 REU's, two of which resulted in honours theses (one CS thesis and one Stats thesis). Although I have no publications, one of the REUs resulted in a paper that is currently being worked on and will probably be submitted post-application, if that matters. Also, I wrote a "project paper" that uses tools from stochastic PDE's, analysis, and topology to prove the behaviour of stochastic algorithms which impressed a prof. I was thinking of creating a personal website to showcase these theses, projects, etc. Graduate Courses: I will be graduating with 8 graduate courses (2 of which are PhD courses): Time Series(A), Generalized Linear Models(A), Mathematical Topics in Machine Learning(A), Applied Machine Learning(A), Regression and ANOVA(A), Reinforcement Learning,(*) Computational Statistics(*), Probabilistic Algorithms(*). * denotes currently enrolled Relevant Undergrad Courses: Honours analysis I (A), Honours Analysis II (B), Honours Linear Algebra (A-) Honours Stats (B+) Abstract Algebra I (A), Other: Awarded a fellowship to conduct research over the summer. Elected into student council twice and volunteer teaching music lessons to elementary kids. Letter of Recommendations: I currently have 4 professors who said they are very happy to write letters for me. Two of which said they will write "excellent" letters for me. All the profs are well-known in their respective fields. Notes: Hey guys! I'm mainly applying to PhD programs in statistics and concentrating on the following programs (they may be a reach but fingers-crossed): 1. CMU 2. UCLA 3. University of Washington 4. Yale 5. University of Toronto In short, I think my weak points are my GPA and GRE. I'm hoping my letters and the fact that I performed well in advanced courses can compensate for them. I essentially completed a masters degree during my undergrad so I feel like I wouldn't get much out of applying to a masters program. If anyone could give their opinion on schools I am competitive for and what other programs I should look into, that would be greatly appreciated! I'll take any information on biostatistic program stoo! My backup is a masters at my current institution which I am confident I can get into. Thanks and good luck to everyone else applying!
  20. Student Type: International asian female Undergrad: Top 5 U.K School Major: Mathematics with Economics GPA: 4.0/4.0 Math & stat modules: Analysis I (A/A*) Analysis II (A/A*) Complex Analysis (A/A*) Real Analysis (A/A*) Probability and Statistics(A/A*) Linear Algebra I (A/A*) Linear Algebra II (A/A*) Linear Algebra III(A/A*) Mathematical Methods I (=Calculus)(A/A*) Mathematical Methods II (=Calculus II)(A/A*) Mathematical Methods III (=Calculus III)(A/A*) Economics I(=Micro and Macro)(A/A*) Economics II(=micro and macro)(A/A*) Maths and Stat modules for next year: Measure Theory, Further Probability(deeper knowledge after measure theory), Stochastic Process, Linear PDE, Programming R, Decision and Risk, Econometrics and Quantitative finance GRE: going to take in sep/early oct Research: Did a research about operator recurrent neural network (RNN) approach to an inverse problem for the wave equation with my personal tutor at university for this summer(3 months) Work Experience: Did spring internships at Goldman Sachs - Markets Division and Citadel Securities Letters of Recommendation: One from my personal tutor who supervised me for the research, one from my departmental tutor ( I got a undergraduate departmental prize in my first year for top 10 students so i think he will write a good letter for me) , and one from my lecturer who knows me quite well(I got 98.9% for this module) Miscellaneous stuff : I got undergraduate departmental prize and work as a mentor at Economics and finance society for spring internship applications for the first year students. Applications: MIT, Stanford, Princeton, UCB, UCLA, Caltech, Michigan, Yale, Georgia Tech and Columbia for mostly statistics/applied mathematics/Operational research
  21. Hello everyone, I am aiming for my masters in Fall'21. Can someone please evaluate my profile and help me understand where I can improve to build a stronger application. Also, it would be really helpful if some one can tell me if I have any chance of getting an admit in the below mentioned universities.. Universities list: CMU, Masters in Computer Vision UCSD, MSCS UCLA, MSCS Waterloo, CS UBC, CS Georgia Tech, CS UC Irvine My profile details are given below: Undergraduate: One of the top-10 private university from India in Computer Science Undegrad GPA: 9/10 GRE: 164 Q 153 V 4 AWA LOR's: 2 strong LORs, 3rd one is not as great as the first 2 Projects: Have a few strong projects in the field of Computer Vision and Machine Learning. Internships: 2 internships from good companies in Machine Learning for a month each Achievements: Kaggle Competitions Expert and Kaggle Notebooks Master, have won a few hackathons Research: 2 projects in total. (1 Major Project another personal project under professor) Links that can give more details about me: My portfolio: https://nd7.me/ My resume: https://drive.google.com/file/d/1w6I6fCkWTpuumVoiz3_Z8apsoneqHDkv/view My kaggle: https://www.kaggle.com/nitindatta My Github: https://github.com/NitinDatta8
  22. Student Type: Domestic White Male Undergrad: Top 5 U.S Public School Major: Statistics and a foreign language GPA: 3.5 (Statistics major GPA is 3.3) Math & stat classes: Calc I&II (high school), Calc III (B+), Differential Equations (B+), Linear Algebra (B), and a few more basic ones. I never got less than a B on any Stats or Math class, but I ended up with quite a few B+s. GRE: 167 Q, 161 V, 3.5 W Research: Did an independent research project with a professor my senior year. Not published or anything. Also participated in SIBS and a few other research projects, but none other that are Stats related. Work Experience: Have worked in marketing for a start-up since graduating. It's a very small company, so I've been able to do projects that involve data analysis (such as forecasting revenue based on marketing spend per channel, and regression analyses to predict different metrics, and I've created Shiny apps in R to help my non-programming teammates with various projects) Letters of Recommendation: One from my current boss, one from the professor I did research with, and one from my workplace mentor (who gets feedback from everyone I work closely with) Applications: I haven't narrowed down my list 100% yet, but I'm most interested in NC State, UW Madison, Emory, Washington, Minnesota, Michigan Looking at my application, I'm mainly worried about my low major GPA. I'm hoping that my decent GRE score, work experience and LOR will compensate for it. I know that MS programs are less competitive than PhD programs, but I'm not sure just how competitive I am. Any advice or insights would be highly appreciated!
  23. Hello all, I'm a current final year biotechnology student and will be graduating in '21. I plan to do masters in US. However, after doing some research & going through universities and their courses, i have begun to develop interest in courses which are completely different from my undergrad. For e.g, i like Masters in Business Analytics (MSBA), Masters in Management Information Systems(MIS). I'm kind of reluctant to apply for MIS, MSBA...because 1)i feel my chances of getting selected in good schools are close to NIL (because my undergrad isnt't in the relevant area) 2) Should i apply for courses outside Biotechnology (considering i'm applying right after undergrad- fresher) or should i take work exp and then apply for MIS/MSBA? What are my chances of getting into courses like MIS, MSBA..?? Profile- 8.5/10 Biotech undergrad, have knowledge in C, Java (worked on a project) & Python. Also done courses on Clinical Data analytics. It would be of so much help if anyone could give suggestions/ideas with regards to my profile. It would help in getting clarity. Thank you so much, cheers!!
  24. Hello all, I'm a current final year biotechnology student and will be graduating in '21. I plan to do masters in US. However, after doing some research & going through universities and their courses, i have begun to develop interest in courses which are completely different from my undergrad. For e.g, i like Masters in Business Analytics (MSBA), Masters in Management Information Systems(MIS). I'm also inclined towards Health Informatics (MHI) but not many universities offer them. I'm kind of reluctant to apply for MIS, MSBA...because 1)i feel my chances of getting selected in good schools are close to NIL. 2) Should i apply for courses outside Biotechnology( considering i'm applying right after undergrad- fresher) What are my chances of getting into courses like MIS, MSBA..?? Also, will it be diificult to find job after masters considering i won't have exp in related fields? Profile- 8.5/10 Biotech undergrad, have knowledge in C, Java (worked on a project) & Python. Also done courses on Clinical Data analytics. It would be of so much help if anyone could give suggestions/ideas with regards to my profile. It would help in getting clarity. Thank you so much, cheers!!
  25. Hi All, I'm a pretty non-traditional applicant to Stats PhD programs -- I have a few questions, and am interested to see what y'all think of my chances! Student Type: Domestic White Male Undergrad: Top 10 overall (Private) (US News Rankings) Major: Physics (Chemistry minor) GPA: 3.88 Math Coursework: Calc 2-3 (A), Linear Algebra (A), Diff Eq (B), Complex Analysis (A), Numerical Analysis (A), Geometry Seminar (A) CS Coursework: Intro Programming (A-), Computer Architecture (A+ -- taken post-grad to prep for CS grad school) Other: Upper-level undergrad physics: Quantum I (A), Classical Mechanics (A-), Thermal Physics (A), Special/General Relativity (B+), Nonlinear Dynamics (A); Intro and Organic Chemistry Sequence (all A's) Graduate: Top 15 Computer Science MS (Public) (actually entering second year in the PhD program, but have decided I'm more interested in stats) Major: Computer Science GPA: 4.0 Coursework: Intro Artificial Intelligence (A), Intro to Theory of Computing (A), Intro to Algorithms (A), Probability Theory (A), Analysis I (A), Stochastic Processes (A), Linear Optimization (A), Machine Learning (Fall 2020), Nonlinear Optimization I (Fall 2020), Undergrad Math Stats (Fall 2020) GRE: Took in 2013, so it's expired and I'll have to retake. Scores then were V: 164, Q: 170, A: 5.0 GRE Math Subject: N/A Research: Publications: First author for a journal article on biological optics from undergrad supervised by a biology prof (cited 14 times as of posting this), Summer research on reinforcement learning under a physics postdoc (paper posted on Arxiv -- cited 2 times), worked on uncertainty quantification for ML methods in computational materials science since January 2020 -- hoping to get a paper by the time I submit applications this winter Misc: I'll be doing some data analysis for an education research group this fall -- (trying to apply ML methods to say something meaningful about user data for online education games) Letters of Recommendation: Planning to ask my three research supervisors (1 biology professor, 1 research scientist at Facebook now, 1 materials engineering professor). 2nd and 3rd should be strong. I think 1st should be strong too, but it's been a while since undergrad... I might ask my supervisor for my education research this fall if it goes well? Should I also ask a math professor? I don't think any of them would have a ton to say, other than "he did well in my class," which I'm thinking already comes across from my grades? Research Interests: Roughly: Developing applied/computational statistics methods for problems in the natural and social sciences Miscellaneous: I took 5 years between undergrad and my current grad program. In that time, I taught high school math and physics and got a MA in Teaching (3 years), and then worked for an education technology company designing online K-12 science/math curriculum (2 years). I really enjoyed both of those, but decided to go back to school because 1) I didn't see myself being satisfied in those career paths for an entire career, 2) I missed being in school and learning cool stuff all the time, and 3) especially after the reinforcement-learning research experience, I definitely bought into the "big data" hype, and wanted to be a part of it. I managed to sneak into a solid CS program, but once here I quickly gravitated toward the theory/math/stats side of things, and started considering mastering out and looking into stats. (As you can tell from my undergrad coursework, getting into top stats programs would have been tough without the probability/stats/analysis background that I've gotten in my current grad program.) Schools: Duke, UNC, NC State, Wisconsin, Michigan, Harvard, Texas A&M Questions: Thoughts on getting rec letters only from scientists in Bio, Physics, and Engineering? I'm aware my background is a pretty non-traditional -- I feel like it's given me a chance to grow personally and professionally, but any takes on how an admissions committee might view it? How much explanation do I need about transferring from CS PhD program to stats? Is just saying something like "I decided I want the rigorous theoretical foundation I would get through a Statistics PhD" sufficient? (Or, can I just frame it as an MS program I'll finish in May 2021 and leave it at that?) General thoughts on my chances at the schools I listed? Or suggestions for others? Thanks!
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