Fall 2022 Profile Evaluation & School Suggestions - Stat PhD

[listar2000]

Hi everyone, I'm a current third-year undergrad and just one semester away from submitting my PhD application. I would say since the second semester of my sophomore year, I've been fascinated by various topics in statistics and worked hard to prepare applying to grad school. However, due to the increasing competition in PhD application and the COVID situation, I find it hard to position myself in the applicant pool and match up with different schools. Any suggestion/comment is appreciated. Thx in advance!

Undergrad Institution: UC Berkeley

Majors: Statistics & Computer Science (B.A. not EECS B.S.)

GPA: 3.94 (Major GPAs 4.0 for both)

Type of Students: International

GRE: haven't taken any but I'm a good test taker, so I just assume I will do well on the general test. Probably would take the math test as well.

Completed Courses (Undergrad, all A/A+): 

• Stat: Probability Theory, Math Stat, Stochastic Processes, Bayesian Statistics, Linear Regression & Application, Programming in R
• Math: Multivariate Calc, Linear Algebra and ODE (proof-based), Real Analysis I and II (measure theory included)
• CS: Intro to AI, Machine Learning, Data Structure, Computer Graphics

(first/second year prerequisite courses like intro to statistics are omitted)

Grad-level Courses : Deep Reinforcement Learning, Analysis of Time Series, Theoretical Statistics (a PhD first year course that I will take next semester)

Research Experience:

• 1 semester biostatistics research with PhD student on dimensionality reduction.
• 1 year (ongoing) long self-driving car project in a Berkeley lab, focusing on the perception and planning modules. Might have a publication in reinforcement learning (not really relevant to statistics IMO) with a PhD candidate before application.
• Honor thesis research & paper with an associate professor on a Bayesian statistics topic (tentative) starting in the summer.

Awards/Honors/Recognitions:

• Dean's honor list (4 semesters)
• CS honor society 
• Regional autonomous racing competition award

Work Experience:

• Reader (grader) for 4 semesters (Stat, Math courses); Tutor for 2 semesters
• Summer SWE Intern at a tech unicorn 

Recommendation Letters:

• One strong recommendation from an associate professor who taught me two courses (1 undergrad + 1 grad) and will be my honor thesis advisor. I think it would be strong since the professor will know both my academic & research capacities very well.
• One "somewhat" strong recommendation from the self-driving lab executive director who knows my work. He is kinda famous in the field but weirdly not on a tenure track (idk how this would affect the letter's influence).
• One average recommendation from an assistant professor who taught me two courses as well.

My Concerns/Questions:

• It seems to me so freaking difficult to have a publication in statistics as an undergrad (except for those who take real analysis in freshman year I guess). Would top statistics programs accept candidates without any publication by the time they submit their materials
• Does extending graduation for one extra semester (to apply a year later) seem to be a good choice if I want to reach a higher-tier program? Or do the programs place higher requirements for super-seniors?

So far my dream schools include Cal, Stanford (I really love the bay area), Duke, and Columbia. School suggestions are very appreciated as well.

 

[ASAP]

How could you achieve almost full GPA in Stat and CS at Berkeley?! My older brother also graduated from UCB CS (he was in the class of 2015 and still loves to wear his Cal hoodie!) and he has always told me how challenging the coursework was. Your accomplishment so far is just unbelievable. This is just my opinion, but, I think you can apply to wherever you may be interested in. GO BEARS!!

[csheehan10]

Yeah I would agree with the previous poster, as long as you don't massively screw things up you should be very competitive for any top PhD programme.

[icantdoalgebra]

You should be a strong candidate for a place like Duke, but for Berkeley and Stanford I'd say you have a decent chance but I wouldn't bet on it (but I wouldn't bet against though).

I was class of 2020 at Cal and it seems like your profile is somewhat weaker than some of my friends, both in terms of coursework and research; none of us got into Stanford or (I think) Columbia, and very few of us got into Berkeley. However this assessment is based on your current position, and a lot can change in the span of a year. 

As for your question about research publications, I'd say the actual research you do matters more than any publication. People with publications tend to better in admissions not because of publications, but because usually those with publications have stronger relationships with the professors writing them recommendation letters. I had zero publications when applying to grad school and I got into places, as did some of my friends.

About delaying applying to a year later, I had asked essentially the same question to a lot of people, and the response I got was mostly "it really doesn't matter". It doesn't seem like they have higher requirements for those who apply the year after graduating but its not like you can do much to strengthen your application further with the exception of finding another research opportunity. 

[listar2000]

5 hours ago, icantdoalgebra said:

You should be a strong candidate for a place like Duke, but for Berkeley and Stanford I'd say you have a decent chance but I wouldn't bet on it (but I wouldn't bet against though).

I was class of 2020 at Cal and it seems like your profile is somewhat weaker than some of my friends, both in terms of coursework and research; none of us got into Stanford or (I think) Columbia, and very few of us got into Berkeley. However this assessment is based on your current position, and a lot can change in the span of a year. 

As for your question about research publications, I'd say the actual research you do matters more than any publication. People with publications tend to better in admissions not because of publications, but because usually those with publications have stronger relationships with the professors writing them recommendation letters. I had zero publications when applying to grad school and I got into places, as did some of my friends.

About delaying applying to a year later, I had asked essentially the same question to a lot of people, and the response I got was mostly "it really doesn't matter". It doesn't seem like they have higher requirements for those who apply the year after graduating but its not like you can do much to strengthen your application further with the exception of finding another research opportunity. 

Hi Cal alumni @icantdoalgebra, lots of thanks for your detailed evaluation and suggestion. I definitely agree that top 5 programs like Berkeley/Stanford can be extremely hard to get in and that's why they are "dream schools" lol. Duke has the program that I love the most since it's pretty Bayesian so I will spend some time preparing for its application. 

So regarding my last question and your response to it. Would you recommend delaying graduation (and application) for a year if I'm somewhat confident to find research opportunity more directly related to statistics and with a more famous professor, as well as finishing 210A/B in my fourth year with good grades?

Also, another weakness in my profile (IMO) is about awards. I honestly don't have much awards other than some school/regional honors/recognitions. How would you say about it's impact on the application?

Once again thank you for your help!

 

[icantdoalgebra]

Having a award itself doesn't mean much, but usually stronger candidates tend to have more awards. 

As an aside, you should just be focusing on doing good research with your current professor; all the professors in the stats department at Berkeley are highly qualified (that's what it means to be a top department) so even if they aren't Lebron James, a strong letter of recommendation from them will carry a lot of weight amongst admission committees. Fixating on the fame of the professor might turn out to be quite counter-productive to your current research.

As per your point of delaying graduation, I really don't know what the optimal move is. I don't think having good grades in 210A/B will be that much more valuable than just having taken 210A because the grading in grad classes is quite generous. Having another research opportunity to replace a recommendation letter which basically states you did well in a class would be helpful but is it worth delaying graduation for? I have no clue. 

[bayessays]

Who has awards? The department admitting you will look at your achievements in your classes and research and your letters and reward you by deciding to admit you, they're not going to care much about a trophy someone else gave you.  Most applicants probably don't have anything like this, except some meaningless things like Dean's list which you could just determine based on your transcript. Don't worry about this at all.

Don't delay your graduation, your profile is great and you'll get into great programs.

[statsguy]

I saw how admissions worked and there are basically two relevant categories:

• auto-admits (e.g. finish a 4.0 combined BS/MS degree in 3.5 years at an Ivy, two publications in good stats journals, and LORs from superstar researchers)
• extremely-strong candidates (someone like you)

Once you are in the extremely-strong category, there are diminishing returns on improving your application given the time and energy you need to spend. Taking 7 vs 6 advanced stats classes is unlikely to change much, whereas 4 vs 0 makes an enormous difference. I remember one year someone got a major bump for his astronomical score on the comically difficult GRE Math subject test (scored in something like in the 98%th percentile).

Candidate rankings can also be really subjective in this category, and unfortunately a random component comes into the equation. If there are 20 candidates in the "extremely strong" category and there are 10 offers in the initial batch, the initial 10 can look very different depending on the committee because it's so hard to separate applicants in this group. A lot will also depend on who else is applying (there is definitely minor variability from year to year) and where others choose to go. There are some years where we had to send 15 offers to get 10 accepts, some years we had to send 11 offers to get 10 accepts.

There are more uncontrollable things as well which I wont mention here... but you get the idea.

Apply broadly and you should get into at least 1-2 top programs.

 

Edit: I also agree to not delay graduation. It's one thing to switch majors junior year which forces you to delay graduation, but in your case it'll likely just raise the bar higher.

 

Edited February 3, 2021 by statsguy

[supremum]

1. Don't delay. Apply to masters otherwise as a route-to-phd.

2. Do the best in your research, there's nothing much you can do at this point. The rest is just luck.

3. Perhaps try to do something more "hip" with your bayesian research like at the intersection of ML and bayes? Then your application is like stat + ML, which is the ideal combination nowadays.

[Stat Phd]

Honestly, you look pretty strong and should apply to all top stats programs: Stanford, Berkeley, UPenn, Harvard, UW, CMU, etc (but apply to 20 or so schools just to be safe)