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Undergrad Institution: Private school Major(s): Applied Mathematics and Statistics Minor(s): None GPA: 3.96 Type of Student: Domestic female I got admitted into 4 PhD programs, but keep in mind I applied to 15. Honestly, I’m really excited to be pursuing a PhD! This application cycle was just brutally competitive, and it's only going to get worse. I started out as an English major, but I completely turned things around and dedicated myself to math. I have a good math background at this point; have taken some grad classes. I used 3 math profs as recommenders, which is probably why I didn’t fare that well with stats programs, even though my academics and research experience are decent considering my circumstances. Also, I was a total idiot and forgot to take the GRE, which meant I couldn’t apply to some programs. And I wish I’d applied to Cornell and Michigan, but ah, here we are. It's discouraging sometimes, knowing that previous years were easier thanks to the pandemic. Some programs struggled to attract quality applicants in those years, which meant admissions were way more favorable for weaker applicants due to less competition. For example, I know someone from my school who got into an excellent PhD program during one of those lucky years, despite having low grades in core courses, very little advanced coursework, and no publications. But comparing myself to those years isn’t productive or fair. The landscape has shifted, and I applied in a much tougher, more competitive environment. I basically got what I deserved -- and I can see I didn't have the preparation to get into a top stats PhD program. I feel truly sorry for the strong applicants this cycle who were rejected across the board but would have been accepted had they applied in previous years. GRE General Test: Completely forgot to take it—my mistake, smh. Programs Applying To: Statistics / Operations Research / Applied Mathematics / Wild Card Program Research Experience: Home institution REU (paper published in an undergrad journal) REU in applied math at another institution (presented at JMM) Awards/Honors/Recognitions: Phi Beta Kappa, completed an honors thesis. Pertinent Activities or Jobs: None. Letters of Recommendation: Three math professors (oops / jeez). Math/Statistics Grades: A’s in everything. 2 semesters of undergrad real analysis. Honestly, my stats background is weak, even having taken the probability and math stats sequence. Any Miscellaneous Points that Might Help: Took several graduate-level math classes. Taking measure theory (grad) right now. Applying to Where: Rice Stats: Ghosted UCLA Stats: Ghosted UMD Applied Math and Stats: Ghosted NCSU Stats: Accepted UNC Stats / Operations Research: Accepted CU Boulder (Applied Math): Accepted Home Institution (Applied Math): Rejected CMU Stats: Rejected Berkeley Stats: Rejected Harvard Stats: Rejected Columbia Stats: Rejected -> accepted to MA (can't afford. Nominated for MA2PhD scholarship, which I assume they offer to everyone because it's not very much money -- covers under half of the very expensive tuition). UChicago Stats: Rejected UW Stats: Rejected Yale Stats: Rejected Wild Card Program (Institution and field withheld): Accepted—I'm attending this one. I'm really really excited. This was a direct admit program. I'm SO HAPPY I got into this program. I'm really really excited. I got SO lucky. I actually applied after the deadline because I spoke to the prof who said that I ought to apply, and the application fee was waived.

Contact admissions now. By the way, is it a biostats program? If so, please carefully check the funding details in the letter

Are you international? This cycle is absolutely brutal and I recommend also applying outside the US in the next cycle. But for now, don't lose hope. The cycle isn't over -- I am sure you have not been rejected across the board yet. I'm feeling a similar way, except that I didn't come from a top school.

Hello guys, I'm in a similar boat, but I am a domestic applicant. I got into 2 public schools in the 11-20 range, and some PhD programs in other fields, but I'm not very interested in the research at the stats programs I was accepted to. I feel better knowing others are struggling and maybe it's not my fault, but I can't afford to reapply, so I figure I'll just take one of the offers I got.

Your research is really great, but some programs do filter by GPA. With that in mind, I think you should definitely try at top 20 programs if you have the funds, but it will be on the more difficult side as you have a 3.5 from a not-well-known school. Are there extenuating circumstances for the 3.5? Perhaps a bad semester due to family emergency? If I were you, I would try to get a funded master's to allay the GPA, or I would delay applying until after the real analysis grades come out. Do your advisors have contacts that can help you? This is because many programs do use real analysis as a signal of whether or not an applicant will be able to survive the first 2 years of coursework and quals.

I am applying to 16-18 stats/biostats PhD programs and I have 4 recommenders. Which do I choose? 1. Tenured math professor I've known for 3 years. Easily one of my favorite professors. He taught me 30% (unfortunately diminishing now) of everything I know. He was also my REU mentor. 2. Tenured professor who does biomedical engineering. I'm a research assistant in his lab but I feel like I'm not able to commit enough time to this project and I worry that I let him down. He's been understanding though — I remember he was impressed that I was a straight-A student 3. Professor that I did another applied math REU with. Don't think he knows me that well or is that impressed by me lol. 4. My real analysis professor. I've only taken 2 semesters of analysis with him, but I was the best (or at least among the top 3 students) in the course, and I came to office hours every week. He can attest to my mathematical ability and work ethic.

Thank you for the advice. Can you tell me more about what schools in the 10-30 range I ought to consider? I spoke with one of the only stats professors at my school and he gave me some suggestions. Another issue is that my partner is also applying to PhDs (only on the east / west coast) and we would like to end up close together.

Here are my stats: 3.97 GPA; major: applied math / statistics Interests: uncertainty quantification, compressed sensing / signal detection, machine learning (broadly speaking), dimension reduction / manifold learning. Relevant coursework: real analysis I and II (my favorite courses I took in college!), numerical analysis, mathematical statistics and probability (2-course sequence), graduate numerical linear algebra course, ODEs, data science programming, cloud computing, ... (all As). Have taken reading courses on probabilistic machine learning, deep learning. Courses left to take: PDEs, regression analysis, graduate real analysis, differential geometry. T25 undergrad (not known for math) Female domestic applicant Other notes: I switched from English major, originally was on pre-law track. Research experience: all tangentially related to healthcare applications, all related to machine learning. Math REU (NSF funded) (topic: computational math-- diffusion model). Paper approved for publication in SIAM undergraduate journal Math REU ( (NSF funded) at top public school for applied math (topic: harmonic analysis / machine learning for signal processing). Have not finished arXiv preprint yet Machine learning research assistant (topic: uncertainty quantification). Will be one of the last authors on a paper. Honors thesis. Topic: have not decided yet. Schools I will be applying to: Duke stats Rice stats Northwestern stats Columbia stats NYU stats UPenn (Wharton) stats Yale stats University of Washington stats Harvard stats Stanford (I am really interested in Emmanuel Candes's work on conformal prediction as well as compressed sensing, but I'm probably not good enough). Two other girls from my school / department who graduated in past years got into ICME at Stanford. An operations research prof at Stanford looked over my CV and suggested I apply to ICME. REU #2 school (program: applied math / scientific computing) Columbia biostats Harvard biostats (Dare I apply???) CU Boulder (applied math) Columbia (applied math) Rice (applied math) Recommenders: My PI (has ties to Biomed engineering, CS, and stats department at one of the schools I've listed); tenured Math professor from REU #1; tenured Math professor from REU #2 -- works in applied harmonic analysis; tenured. Languages: LaTex, Python (specifically PyTorch), R, MatLab. My question: Which programs are unrealistic for me to apply to? Am I qualified to apply for biostatistics if I have taken almost no biology/science classes in college? My past research has been related to biomedical applications.

I know that logically I should apply to lower-tier schools but I would rather go to a lower-ranked school for applied math than a lower-ranked school for statistics. So I'll be applying to some applied math programs that are lower-tier.

I grew up in a town situated between U of Chicago and Northwestern. I wanted to escape the winters for undergrad but I guess I’m missing home.

I feel that I am not good enough and I have doubts about getting into any PhD programs, especially given that I have not taken PDEs yet. I did apply to applied math REUs this summer, and I was very lucky to get into a very selective program and 2 other REUs at good schools, but I feel like I am not good enough. Here is my current profile: Current institution: top 25 undergrad but not known for math Domestic female applicant (I'm a US citizen) Current GPA: 3.97 Classes taken: Watered-down multi calculus class (red flag since I need to teach myself vector calculus so I can take PDEs) Real analysis Real analysis II Linear algebra Math of data science Numerical analysis ODEs Graduate math class in subfield of numerical linear algebra Calculus-based mathematical probability, mathematical statistics sequence (non proof based) Cloud computing class Statistical inference intro Reading group on theoretical / statistical machine learning Some programming classes in R and Python, some non-rigorous stats courses Additional notes: Planning to take during the semester I apply: PDEs (undergrad), Numerical analysis (graduate), nonlinear optimization (undergrad), regression analysis (undergrad); planning to take in final semester: possibly measure theory (this is only offered as a graduate course) Research experiences: 2 NSF math REUs (in applied / computational math), about 1 year of machine learning research assistant employment Interests: optimization, statistical machine learning, applied deep learning for scientific computing, signal processing, numerical linear algebra, especially w/ biomedical applications Other: I have extensive PyTorch experience. Historically, students with similar profiles compared to me from my school have gotten into top programs, but they're smarter than me / they have something I lack (like physics background, research is more of a fit, their recommenders have ties to those programs, etc.). I used to be an English major. **Here are some schools I am interested in for applied math:** Brown Rice JHU CU Boulder NCSU UMD USC **Here are some schools I am interested in for statistics:** Duke Rice NCSU Northwestern Columbia Cornell UPenn (Wharton) Yale University of Washington CMU (probably not worth applying here, probs gonna be rejected) I might apply to Harvard, JHU, UPenn, and Columbia for biostatistics. Please, someone slap me in the face with cold hard reality. Which of these schools are unrealistic for me to apply to? What are some lower-tier schools I ought to consider? Thank you

Thank you but I have no shot at getting into Stanford . I do know that over the past 3 years 2 girls from my school and my department got into Stanford, but their research is pretty different from mine. I feel like they are a lot better than I am I thought Rice was a pipe dream I got an interview but didn't get accepted to their stats REU (I already got 3 other offers from math programs though, partially because I am a US citizen).

I feel very depressed about my prospects for applied math PhD programs. I lack guidance on where to apply, and my mentor has not provided much input aside from 'following your heart' and 'apply to top schools'. I spoke to the head of my home institution's department and he said that if I take a second graduate course, I have a very strong profile to apply to top schools (I definitely plan on taking this course). But I feel that I am not good enough and I have doubts about getting into any PhD programs, especially given that I have not taken PDEs yet. I did apply to REUs this summer, and I was very lucky to get into a very selective program and 2 other REUs at good schools, but I don't think I will be so fortunate when it comes to actually applying to PhD programs. Here is my current profile: Current institution: top 30 undergrad but not known for math Domestic female applicant Current GPA: 3.96, expect it to be above 3.85 when I apply, but I will be taking some hard courses next semester Classes taken: * Watered-down multi calculus class (red flag since I need to teach myself vector calculus so I can take PDEs) * Real analysis I * Real analysis II * Linear algebra * Math of data science * Numerical analysis * Intro CS * ODEs * Mathematical probability, mathematical statistics sequence (non proof based) * Reading group on theoretical / statistical machine learning * Non-rigorous programming classes in R and Python, some non-rigorous stats courses * Grad class in computational math topic related to numerical linear algebra * *Planning to take while applying: PDEs (undergrad), Numerical analysis (graduate), nonlinear optimization (undergrad); planning to take in final semester: possibly measure theory (graduate)* * Reading group on statistical / mathematical theory of machine learning (2 semesters) -- covers a LOT of topics Research experiences: 2 summers of NSF math REUs (applied / computational math), \~ 1 year of research assistant employment (in statistical topic related to machine learning w/ BME application). Interests: non-convex optimization, statistical machine learning, applied deep learning for scientific computing, signal processing (???) Other: I have a lot of experience using Python / PyTorch for research. Recommenders: my mentor (tenured prof, computational math) has some connections at some of the schools I am interested in; will also ask my PI (director of AI lab, very seasoned researcher in BME, is also a CS professor) for letters of rec; third recommender is a wild card (maybe REU mentor this summer? we will see) Historically, students with similar profiles compared to me from my school have gotten into top programs, but they're smarter than me / they have something I lack (like physics background, research is more of a fit, their recommenders have ties to those programs, etc.). **Here are some schools I am interested in for applied math:** Brown, Rice, JHU, Duke, Northwestern, CU Boulder, NCSU, UMD, USC, Georgetown, Virginia Tech, UNC, WashU I would particularly like to do research with biomedical applications, so a school that is associated with a medical system is a big plus. **Here are some schools I am interested in for statistics:** Duke, Rice, NCSU, Northwestern, Emory (bio stats) **Here are some schools I am interested in for OR:** Cornell, JHU, Duke, Yale, Wharton, Northwestern McCormick Please, would anyone help me disabuse myself of the delusion that I can get into any of these schools, and provide ideas for safeties? Thank you very much.