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Hello everyone, Need help evaluating profile and shortlisting universities. I am aiming for Operation Research(PhD or MS) / Data Science(MS) I have good experience in working on optimization, mathematical modelling and Applied ML I have degree in bachelor in EE GRE: 322(169Q + 152V) (I don't know if this is anymore useful since all Top programs have waived GRE) TOEFL: yet to attempt GPA: 7.85 Under Graduate Research Assistant for 2 years Papers: 4 papers in moderate to good IEEE conferences & 1 paper submitted to top Journal(all first authored) Received 2 grants externally for papers. Invited as a Reviewer in few Top conferences Patent: 1 provisional patent in optimization and time series prediction of cyber physical system 2 relevant internship in analytics and ML (1 famous + 1 not so famous firm) Will have 9 months of Work ex in august 2021 (at the time of Joining) as a analyst in fortune 100 firm Great extra curricular achievements and Leadership position while in my Undergraduate Few good academic projects with grants. I am open to joining applied math/Applied Stats/Applied and computational mathematics kind of programs also. Thanks in advance.

Hi guys(girls), I am applying for the Fall 2019 IEOR Ph.D. program. Is there anyone else also applied to IEOR Ph.D. If you are, you can share your story here. Also, you can ask some questions that you concern about the application, result, programs etc. About me, I have applied MIT(ORC S.M.) Columbia Berkeley Northwestern Umich VT TAM Stanford(MSE) Princeton(ORFE) Gatech. I have got an offer from VT and interviewed Umich and TAM. Since I haven't heard anything from NWU, Berkeley, and Columbia, I think the possibility for me to get admitted is very small (sad story Anyway, good luck with your applications. And thank in advance for your sharing.

Hi all, I am not going to ask you guys to chance me, as I know the application cycle will be an uphill battle for me from a low GPA and non-traditional background. I majored in Economics at an Ivy League with minors in Math and Statistics. I didn't do so well in the Economics with a few C's, a few A's, and mostly B's,(major GPA ~ 3.1) while my Math (mostly A's with an occasional A-), Stat, and other STEM courses such as CompSci and Econometrics was around 3.75. My cumulative GPA including the 'general ed' courses was right below 3.40, with the lowest semester being the first semester of my third year. I finish both my senior semesters with a 3.9. It seems that my GPA progression is hyperbolic and concaved upwards over the semesters. I will have taken up to Real Analysis, scoring A-/A in my math courses from undergrad and graduate institutions. Now, I am enrolled in my final year in a statistics masters program at a mid tier state school (to be specific - mid tier for statistics) and will be expecting a final GPA between 3.8-4.0. I will also be completing a master's paper on the topic comparing multivariate time series models using foreign exchange data (not a publication in a journal). My interest lies in financial engineering and multivariate statistics. My GRE is V:160/Q:166/W:4 (I plan on retaking. Also I am taking the GRE Math subject to hopefully scoring between the 50th to 70th percentile. The higher the better but without the math major, I don't know how feasible it is.) I have around 1 year of work experience in finance and data analytics (business strategy) as I recently finished my undergrad. So my questions for PhD programs are: 1) Besides the big names such as Columbia, Princeton, Cornell, and Berkeley, where else offers such programs with respect to my interest in financial engineering and high dimensional statistics? I'd like to stay on the coasts. 2) Which schools are more reasonable to be set as target schools? 3) Is it worth my while to work towards a post-bac in math to compensate for the GPA and gain the necessary coursework? Any advice would be much appreciated.

Hi all, With schools starting to open up their applications in the next 2-3 months, I've been wondering what schools I should aiming for. I want to get into healthcare using math/stats so most of the programs I was considering are bio-statistics or operations research with a focus on health systems. I have a pretty good academic profile but some concerns I have are that 1) my undergrad has zero prestige; 2) my GRE score seems a little low for the top programs; 3) I have no direct healthcare experience (currently work in unrelated economic research). Below are my stats but I'm not sure how competitive my profile would be. Obviously, I would love to get into top schools like Harvard Biostats or Stanford MS&E, but I have no idea whether my GPA/GRE is really enough. Given my profile below, what type of schools should I be aiming for? Am I being delusional for thinking that I should even apply to a place like Harvard? What "tiers" should I be aiming for? Any help would be greatly appreciated. Thanks so much!!! Undergraduate Institution: CUNY - Hunter College Major(s): Math GPA: 4.00/4.00 Type of Student: Domestic Asian Male GRE General: 166Q (90%); 164V (94%); 4.5 AWA (82%) Programs Applying: MS Biostatistics, Statistics, and Operations Research (health systems focus) Letters of Recommendation: 1 from my mathematical statistics class professor; 1 from my epidemiology class; don't know my third letter writer yet. Relevant Coursework: Calculus I, II, III; Linear Algebra; Ordinary Differential Equations; Vector Calculus; Discrete math; Real Analysis I ; Complex Analysis; Abstract Algebra I ; Stochastic Processes; Numerical Methods & Analysis; Mathematical Statistics; Intro to Probability Theory; Intro to Epidemiology Skills: R, Stata, Python, SQL (I have an active Github portfolio with all my code) Relevant Research: None, but I'm not aiming for a PhD Work Experience: Software Engineer for 2.5 years, and now currently doing data analysis doing economics research

Hello. I recently took the GRE and got a score that I thought was pretty good: 166Q / 164V / 4.5 AWA. I would like to aim for a top 10 program and I've heard that 166Q is too low for these programs and that 167/168 on GRE Quant should be the aim. Is this true? Does 1 or 2 points really make that much of a difference for operations research / management science master's programs? It seems a bit ridiculous to study another month or so just to bring up my score by 2 points, but I'm not sure whether this is actually what's required of applicants these days. Any input would be appreciated. Thanks!

Undergraduate Institution: Small Southern University Major: Mathematics Minor: Physics GPA: overall: 3.73 Math: 3.66 (I had one rough semester of mostly B's and one A that I will explain the extenuating circumstances behind) Type of Student: Domestic White Female Courses Taken: Intro to Mathematical Proofs (A), Differential Equations (B), Probability and Statistics (A), Intro to Abstract Algebra I (B), Intro to Real Analysis I (A), Calculus 3 (B), Statics (B), Mechanics (B) THIS Semester (intended grade): Functions of a Complex Variable (A), Discrete Mathematics (A), Computational Tech in Physics (A), Undergrad Research in Statistics (A) ** note that the schools currently on my list will receive this semester's grades as their deadlines will be after grades are due GRE General: Q: 183 (83 %tile) V: 158 (80 %tile) W: 4.0 (59 %tile) (Plan on retaking as my practice tests had my in the 90+% for quant) Subject test: TBD Programs Applying: A mix of OR, Biostat, and one ME MS Research Experience: Currently working on an honors thesis focusing on the PDE heat equation and hopefully finding an accurate experimental way to model it in two dimensions so I can then model via program and mathematically. I am also required to do a senior project which will be based on the combinatorics or a particular board game Awards/Honors/Recognitions: Dean's list a few semesters, Honors graduate, graduating a four year program in only three years, a few university scholarships Letters Of Recommendation: Two confirmed. One from a professor I had for linear algebra, proofs, and abstract. The other I had for calculus three, differential equations, and complex variable and he is also my thesis adviser. Next Semester Schedule: Numerical Analysis, Stochastic Processes, and either Abstract Alegbra 2 OR Nonlinear Dynamics and Chaos (any suggestions here would also be appreciated) Schools: ( I appreciate any and all guidance, especially in this category) ME MS- Boston University's LEAP (engineering masters program for non engineering undergrads) OR Programs (MS unless otherwise noted) NCSU Simon Fraser Ohio State Bowling Green GT- (i have a fee waiver, so why not?) *PHD Biostat Programs (MS unless otherwise noted) Louisville Northwestern Iowa UNC University of Georgia Georgetown Thank you for any and all feedback! *Note that this is only my third year so if i should stay another semester, that's also another option

Hi Everyone! Saw a very informative thread with some active discussion for Fall 17 (link above) so thought I should replicate it for Fall 18. Lets get to know each other better!

Is it a no-brainer (MIT) or am I mistaken? What would you do?

Undergrad Institution: Big State School Major(s): Industrial Engineering Minor(s): Mathematics GPA: 3.31 Industrial Engineering 2.88 in Mathematics (Freshman Calculus Sequence is really killing me here, chalk it up to youthful ignorance) Type of Student: Domestic Asian Male Courses Taken: Calculus I (B), Calculus II (C), Calculus III (B), Applied Linear Algebra and Differential Equations (A), Discrete Math (A), Probability (A), Statistics (A) , Operations Research I (A-), Operations Research II (A), Statistical Process Control (A), Discrete Event Simulation (B+), Engineering Design of Experiments (A), Physics (all A's), Vector Statics/Dynamics (C/C, by far my weakest subjects), Digital Logic(B-), Strength of Materials (C), Properties of Materials (A) Courses in Progress: Theoretical Linear Algebra, Applied Regression, Upper and lower division Numerical Analysis Courses I will be taking in the future (These aren't gonna be on my app before applying): Undergraduate Real Analysis, Graduate Generalized Linear Models, Graduate Numerical Linear Algebra, Stochastic Calculus or Abstract Linear Algebra, Intro to ML GRE General Test: Q: 163 (84th percentile) V: 166 (97th percentile) W: 4.0 (60th percentile) GRE Subject Test in Mathematics: No plans on taking it Programs Applying: A mix of Stat, OR and Biostat MS/PhDs Research Experience: n/a (probably a dealbreaker for PhD programs?) May have some work beginning in January, but would be irrelevant for apps. Awards/Honors/Recognitions: Dean's list a few times, but nothing of note Pertinent Activities or Jobs: Did a fair amount of engineering work in industry. Had an 8 month full-time co-op with a major medical device manufacturer, did a major facility redesign at a different medical manufacturer for senior design project, recently had a process engineering internship at a major hospital provider. Letters of Recommendation: Two letters confirmed, one PhD in Biostat the other in Systems Engineering. No idea of quality though; scrambling to find third. No response from faculty member who knows me fairly well, so not hopeful on that front Any Miscellaneous Points that Might Help: I'm mostly interested in pursuing Bayesian methods and computational stat with side interests in ML and stochastic optimization Applying to (far from complete, please let me know if you have any suggestions, this needs to be pruned down): USA: NC State (MSc, Operations Research) OSU (MS, Statistics) Penn State (MS, Statistics) Purdue (MS, Industrial Engineering with OR focus) Purdue (MS, Statistics) UCLA (MS, Biostatistics) UCI (PhD, Statistics) UCR (PhD, Applied Statistics) UIUC (MS, Statistics) UNC (PhD, INSTORE) USC (PhD, Operations Research) USC (PhD, Biostatistics) UC Berkeley (PhD, IEOR) (waste of time?) UCSB (MS, Statistics) UMass Amherst (MS, Statistics) University of Michigan (MS, Statistics) University of Wisconsin at Madison (PhD, Industrial Engineering) UT at Austin (MS, Operations Research) UT at Austin (MS, Statistics) Canada University of British Columbia (MSc, Statistics) Simon Fraser University (MSc, Statistics) Simon Fraser University (MSc, Mathematics (with focus on Operations Research)) University of Alberta (MSc, Statistics) University of Waterloo (MMath, Biostatistics) University of Waterloo (MMath, Statistics)

Hey New gradcafe user and prospective MS applicant for an MS in Operations Research / Statistics / Management Science for Fall 2018. Please evaluate my profile and whether I'm being too ambitious/do I stand a chance here? Key features of my profile - Low undergrad GPA, high quant GRE score, related work ex Here's my profile followed by an initial university shortlist GRE 324 - Q 166 (91st percentile) V 158 (80th percentile) (Might give again to offset low undergrad GPA) TOEFL - Yet to give Undergrad CGPA - 6.3/10 from the National Institute of Technology Warangal in Mechanical Engg - Top 10 India for engineering Work Experience - 3 years 1.5 years - Data Analyst for a Fortune 200 MNC (1 promotion) + 3 good projects - Quantitative Sales/Marketing analytics 1.5 years - Senior Analyst for a Loyalty Card company (jump in designation from previous org) Fair amount of projects on quantitative modelling work Research papers/Publications: None Certifications: 1. SAS certified base programmer 2. SAS certified statistical business analyst: Regression and Modelling 3. Machine Learning from Coursera Recommendations: 1. HOD from work - ex prof at a premier MBA school in India - Strong 2. Team Leader from previous org - Moderate 3. Professor from college - Moderate SOP structure: Considering that my weakest point is my undergrad GPA, I'll bring in a point about how I messed up the first year but post that my gpa has been increasing plus ever since starting work I've been really driven and talk about my projects as proof. Programs I'm looking to apply for: 1. Statistics (with electives from the CS department) 2. Operations Research Not applying for "Analytics" or "Data Science" masters because I feel such programs have breadth but seriously lack depth. Current university shortlist: 1. Columbia 2. University of Chicago 3. UCLA 4. Georgia Tech 5. University of Michigan 6. John Hopkins 7. University of North Carolina at Chapel Hill 8. University of Illinois at Urbana Champaign 9. Duke 10. Cornell Questions: 1. What is my profile like? 2. How would you categorise the above universities considering my profile as Safe, Moderate, Ambitious and reasons for the same? 3. Thoughts on the SOP structure?

Hi everyone! I wanted to create this thread for (Fall 2017) MS operations research, industrial engineering, management science & engineering applicants to get to know each other a little better. Who else is applied this cycle? What are your research interests, and what are some of the schools that you're looking at? I applied to Columbia, MIT, Michigan, Stanford and Univ of Florida

I have heard from pre-med friends that they have interviews for grad school. Does that apply to PhD programs in Operations Research? I don't think I have seen any thing like that in any of the school websites I visited.

Hi all, I'm looking to pursue masters in the area of operations research and optimization. Pretty keen on doing research and will mostly move into academia (or a research-based job at the least). I've been accepted into the following schools: 1. Purdue MSIE (Thesis track) 2. Columbia MSOR 3. NCSU MOR 4. UIUC MSIE Waiting to hear from UC Berkeley (MS Program) and UMich (MS) I'm extremely confused about which to pick. I've more or less narrowed it down to Purdue and Columbia from my current admits. Purdue seems to have a clear research orientation (but not in optimization), while Columbia has a very heavy focus on quant/applied math (research focus seems lower). The other aspects to consider are the location and cost. In summary, 1. OR / Optimization - Columbia 2. Research - Purdue 3. Location - Columbia 4. Cost - Purdue I'd be grateful for any inputs you can provide! Do I accept Columbia ($4000 tuition deposit) and wait for Berkeley and UMich to make a decision? Oh, and FYI, I need to confirm my decision with Columbia by this Friday! Thanks!

Hello, I'm currently studying Mathematics and Econometrics, and I am very interested in pursuing a PhD and research career in the mathematical aspects of data science (Artificial Intelligence/Machine Learning). I have a decent amount of coding experience in R and Python, but I have not taken any CS classes. Is Operations Research a discipline that would allow me to pursue my research goals? Are there any other types of programs that I should look into? I am currently applying to OR programs, and NYU's Data Science PhD program. Any help you can provide would be a huge help. Thanks!

· Hi all, I've been a lurker on here for a while, and I wanted to get a better gauge about what schools I can/should apply to for a PhD in either Statistics or Operations Research. I'm interested in statistical simulation problems that arise naturally in Actuarial Science. On a more practical side, I am interested in bringing the simulation and statistical techniques from Financial Engineering to Actuarial Science. I’d love to hear your thoughts. EDUCATION: o Major: Actuarial Science and Mathematics with a minor in Computer Science from University of Wisconsin o GPA: 3.73 overall, 4.0 in Actuarial Science classes, ~3.8 in Math classes o Relevant Courses: Calc III (AB), Intro to Probability (A), Proof-based Linear Algebra (AB), Stochastic Processes (A), Real Analysis I (AB), Stochastic Calculus (AB), Mathematical Statistics (A), Intro to Computer Science (A), Actuarial Mathematics I and II (both As), Loss Models (A), Interest Theory (A) o Currently in Linear Programming, Numerical Analysis, Real Analysis II, Regression, and Data Structures o I plan to take Measure Theory and possibly an Integer Optimization course next semester RESEARCH/RELEVANT ACTIVITIES: o Currently involved in a research project with an Actuarial Science professor comparing Machine Learning methods with more traditional GLM as applied to Actuarial Science. I oversee the coding (in R) and the conceptual picture for the ML side of the work. We will likely not have a paper until the end of the school year. o Programming: Proficient in R, MATLAB, and Java o Two actuarial internships, one at a smaller life insurance company, another at a bigger property/casualty company doing insurance claim modeling in R using Markov Chains. o I've also graded for two different Actuarial Science classes, and tutored introductory Statistics and Calculus, as well as passed three actuarial exams. GRE/Letters of Rec: o GRE: 164Q, 162V, waiting on writing o I have one excellent letter of rec from an Actuarial Science professor who I have graded for and who I am working with. Two other letters of rec, one from a professor I am taking a class with now and took a class with last semester who knows I am a good student, another Stats professor who I had a class with who I have asked for help with graduate school. Likely that they might not be particularly stellar except for the first one. Schools: Statistics PhD: o University of Wisconsin o UC-Berkeley o Duke o Wharton o John Hopkins o UNC-Chapel Hill INSTORE o CMU Operations Research PhD: o Columbia IEOR o Princeton ORFE o Stanford OR (dream school) o Cornell OR Do I have a chance at these schools I've listed? Is it too top heavy? What should I add/take off? Also, should I retake the GRE? I really don’t want to if I don’t have to…. But I will if my chances are far too low.

Hello, I'm currently studying Mathematics and Econometrics, and I am very interested in pursuing a PhD and research career in the mathematical aspects of data science (Artificial Intelligence/Machine Learning). I have a decent amount of coding experience in R and Python, but I have not taken any CS classes. Is Operations Research a discipline that would allow me to pursue my research goals? Are there any other types of programs that I should look into? I am currently applying to OR programs, and NYU's Data Science PhD program. Any help you can provide would be a huge help. Thanks!

Dr. Kai Pan, Assistant Professor in the Department of Logistics and Maritime Studies at the Faculty of Business of The Hong Kong Polytechnic University, is looking for highly motivated PhD students beginning Spring or Fall 2017. The successful candidates are expected to conduct cutting-edge research in the area of operations research, smart grid, supply chain, and transportation. Candidates with Industrial Engineering, Math, CS, EE or other relevant backgrounds will be considered, and an earned Master degree is preferred. Strong mathematical background and programming skills will be a plus. Previous research experience on the related areas will also be a plus. The successful candidates will be provided by competitive financial support with full scholarship. Hong Kong PhD Fellowship (around HK$20000 monthly) will be one option, as otherwise the support will be in the form of research assistantships and/or teaching assistantships (around HK$15000 monthly). Dr. Kai Pan is working on stochastic and discrete optimization, data-driven optimization, dynamic programming, and their applications on smart grid operations, supply chain management, and transportation (see detailed description at here). If interested, please send your CV/resume (including GPA, GRE/TOEFL scores), scanned copy of transcript, and relevant publications (if applicable) to Dr. Kai Pan at kai.pan@polyu.edu.hk. Also, please email Dr. Kai Pan for any further related questions regarding his recruitment on Ph.D. students. About PolyU: The Faculty of Business at The Hong Kong Polytechnic University is ranked No. 64 in the world in the latest UTD (University of Texas at Dallas) Top 100 Business School Worldwide Rankings (the most authoritative business school ranking in the world) based on research published in 24 top business journals for the period of 2011 to 2015. Both the maritime studies and shipping research of the Department of Logistics and Maritime Studies are ranked No. 1 in the world, with the port research ranked No. 4. QS World University Rankings by Subject 2016 show that PolyU’s Business & Management Studies ranks 39th and Statistics & Operational Research ranks 46th in the world. About Hong Kong: Located on China's southern coast, Hong Kong is a unique place and a free land where East meets West and old meets new. A former British colony and current Special Administrative Region of China, Hong Kong is home to an exceptional culture and highly independence. Having inherited ancient Chinese heritage and experienced a period of Western, colonial influence, Hong Kong is a multifaceted city where English and Cantonese, “Feng Shui” and football, towering skyscrapers and historical sites exist side by side.

Hey guys, I plan to apply to the Masters OR program at Gatech and I'm wondering if you guys can give me some advice/what are my chances of getting in? GPA: 3.7 GRE: 158Q 158V out of 170 Co-op experience at Delta Air Lines and ~1 year of research experience. What are some other programs that I should apply to? Particularly the ones with financial aid. What are some other general advice that you have?

Hi All I applied for MS in IE at Purdue and Georgia Tech and now i am waiting for the results. Please post any info about admissions (acceptance/rejections/waitlists) in these programs. This might help all others who are desperately waiting for their results. Regards Raghav

Hello everyone, Every where I look, the management sciences (and or operations management) areas of management PHD state GRE scores in the 90th. Where are the schools that accept us, the mortals? Also, any suggestions as to good programs in that area? All the best, Felipe

I am applying for Operation Research and some statistics programs Below are my profiles, can you help me to take a look and comment on my chances of getting in? I welcome suggestions for other schools as well. My plan is to either get into a phd or to getting into a prestigious master's program. My biggest disadvantage is that I am on an accelerated graduation program, so I did not take as many courses as others, the courses below are the courses completed by the end of my sophomore year. I would really appreciate your help, thanks! Undergrad Institution: Carleton College (top 10 liberal arts college) Major(s):Mathematics Minor(s):None GPA in Major: 3.91 Overall GPA:3.82 Length of Degree: I completed a 4 year degree in 3 years. Position in Class: Near top Type of Student: International student GRE Scores: Q:800 V:740 W: Not out yet Courses: Math: Probability, Algorithm, Advanced Algorithm, Real Analysis, Abstract Algebra, Advanced Abtract Algebra, Advanced Linear Algebra, Topology, Surfaces Computer Science: Data Structure Economics: Price Theory, Econometric Research Experience: I have done Markov Chain Monte Carlo simulations on gravitational waves for my physics professor for two year, hopefully we can get something published before application. Awards/Honors/Recognitions: Dean's list for Freshmen year. Starr Scholarship holder Pertinent Activities or Jobs: Calculus Tutor for one year, Grader for courses like (topology, discrete mathematics, caculus), Mathematica lab assistant. Any Miscellaneous Accomplishments that Might Help: In freshmen year, I was ranked 700 in the putnam contest. Applying for [ MS ] or [ PhD ] at: Cornell Applied Probability (MS/PhD) Columbia OR(Financial Engineering)/Stats Stanford OR(M.S) Princeton OR(PhD)

I am applying for Operation Research and some statistics programs Below are my profiles, can you help me to take a look and comment on my chances of getting in? I welcome suggestions for other schools as well. My plan is to either get into a phd or to getting into a prestigious master's program. My biggest disadvantage is that I graduate with a 4-year degree in 3 years, so I did not take as many courses as others, the courses below are the courses completed by the end of my sophomore year. I would really appreciate your help, thanks! Undergrad Institution: Carleton College (top 10 liberal arts college) Major(s):Mathematics Minor(s):None GPA in Major: 3.91 Overall GPA:3.82 Length of Degree: I completed a 4 year degree in 3 years. Position in Class: Near top Type of Student: International student GRE Scores: Q:800 V:740 W: Not out yet Courses: Math: Probability, Algorithm, Advanced Algorithm, Real Analysis, Abstract Algebra, Advanced Abtract Algebra, Advanced Linear Algebra, Topology, Surfaces Computer Science: Data Structure Economics: Price Theory, Econometric Research Experience: I have done Markov Chain Monte Carlo simulations on gravitational waves for my physics professor for two year, hopefully we can get something published before application. Awards/Honors/Recognitions: Dean's list for Freshmen year. Starr Scholarship holder Pertinent Activities or Jobs: Calculus Tutor for one year, Grader for courses like (topology, discrete mathematics, caculus), Mathematica lab assistant. Any Miscellaneous Accomplishments that Might Help: In freshmen year, I was ranked 700 in the putnam contest. Applying for [ MS ] or [ PhD ] at: Cornell Applied Probability (MS/PhD) Columbia OR(Financial Engineering)/Stats Stanford OR(M.S) Princeton OR(PhD)