Misconceptions about pursuing graduate study

"I'm not smart enough" or "I have bad grades"

Smart is a stupid word. There's this misconception that one must be "smart" to pursue a PhD. Having met plenty of people whom I consider (far) smarter and brighter than me, yes, you must work hard if your goal is to get into a PhD program. But it's ok to struggle in linear algebra (I did!), calculus (I did!), or discrete II (I did!). If you have a goal, a plan, belief, and the work ethic to match, it doesn't really matter if you aren't the quickest or brightest in the room, since you'll be putting many hours outside of the room studying and developing understanding regardless.

PhDs and (research-based) master programs are research-based degrees. While a good GPA may be a slight positive indicator for admissions, what ultimately matters is your research experience and research potential. Here is what various CS professors have to say on gpa:

• "GPA: warning sign if too low, but usually don't care. It's rare that someone with strong research credentials has a dangerously low GPA, and even if that were the case, I wouldn't care much. A high GPA from a highly-selective university is a slight positive signal, though." --- Prof. Philip Guo, CS @ UCSD (source)
• "When applying to a Ph.D. program in CS, you’d like your grades in CS and Math and Engineering classes to be about 3.5 out of 4.0, as a rough guideline. It does not help you, in my opinion, to be closer to 4.0 as opposed to 3.5. It’s a much better idea to spend your time on research than on optimizing your GPA. At CMU the mean GPA of students admitted is over 3.8 (even though we don’t use grades as a criterion), however students have also been admitted with GPAs below 3.3, since research is what matters, not grades. A GPA of 4.0 alone with no research experience will not get you into any top CS program. Keep in mind that GPAs are evaluated in the context of the undergraduate program. A 3.4 GPA from a topranked CS undergraduate program like CMU counts the same as a 3.8 or 3.9 GPA from a less well-known CS undergraduate program." --- Prof. Mor Harchol-Balter, CS @ CMU (source, this whole thing is a really good read, highly recommend.)
• "GPA? I don't care if it's 2.0 or 4.0. I won't even look at it. The school you went to? I'll judge you the same whether you went to Nowhere State U or a top-ten school. Transcripts? Never seen one. GREs? Irrelevant. Where you work/worked? Unless it's a research lab, it's not important. I don't think these items have much predictive capacity as to whether or not someone can complete a Ph.D." --- Prof. Matt Might, previously CS @ University of Utah (source, Note that Prof. Might here also talks a bit about GPA cutoffs during the admissions process, which very well may pose issues.)

All these examples were taken from this advice compilation site.

Do keep in mind, however, that a great GPA can really be a boon for you to acquire summer internships. I know of at least two internships from the research internship master list which I put together which look through their applicants ordered by GPA. It sometimes pays to have a good GPA!

"Ok, won't I be poor af though?"

For STEM PhD students, every reputable (translation: mid to top tier) university will fully pay your tuition and provide a living stipend of somewhere between 20-35k based on location. However, you may be required to serve as TAs for some semesters, similar to how you may have had graduate TAs during your time at UTD. Now, I do understand that 20-35k is not by any means comparable to CS salaries in industry. My friends and peers had starting (new-grad) salaries / total compensation (TC) at FAANG level or above companies (facebook, amazon, google, quantitative hedge funds, etc.) of between 120-205k+. Even non-FAANG Dallas area companies pay between 85-120k for new grads. This is something that you will have to accept. One can argue that CS new grad salaries are extremely inflated, but it does not change the reality that you will be earning much less than your peers for the next 4-6 years.

Once you do get a CS PhD, you are still welcome in industry, and may even get a starting TC slightly higher than new-grad BS students. Yet, if a high salary is your goal, it is certainly faster to avoid the PhD all-together and just start working right away. Put it this way: at the given salary levels, the opportunity cost of a PhD in CS is somewhere between $400k to $800k (pre-tax, assuming some level of promotion after 2 years). With these kind of figures, it is clear that you should not pursue a PhD (at least in CS) for the money.

Nonetheless, you will not be poor. Prof. Dave Andersen (CMU) put this really helpful guide together for a perspective on CS PhD finances. tldr: expect to not pay any tuition, have something like a 2.5k stipend, and be able to earn 20k+ each summer if you want to pursue an outside summer internship. This leaves you with enough money to live and max out your roth IRA each year! (see also this quora post).

"What if I have a financial burden during my undergraduate?"

I personally see this as one of the most legitimate and pressing issues with regards to getting more students from non-traditional backgrounds involved in research. If you are funding your own undergraduate education without the help of your family and/or need to work part time to pay for your rent and bills, doing (unpaid, at least to start with) research at your university for 20-30 hours a week may not be a viable option.

Nonetheless, there are some things that you may want to consider if you are planning to pursue a graduate education under these circumstances. First, summer research opportunities like NSF REU Programs allow you to pursue research full time while paying for your summer accommodations and typically offering stipend of around $6k. In fact, REUs as defined by the NSF are created and targeted towards minorities and students who otherwise may not have had the opportunity to pursue research during the academic year, due to perhaps attending a liberal arts college with low research output, or needing to work part-time during the school year to pay bills. Here is the statement from the official solicitation:

"REU Sites are an important means for extending high-quality research environments and mentoring 
to diverse groups of students. In addition to increasing the participation of underrepresented groups 
in research, the program aims to involve students in research who might not otherwise have the 
opportunity, particularly those from academic institutions where research programs in STEM are 
limited. Thus, a significant fraction of the student participants at an REU Site must come from 
outside the host institution or organization, and at least half of the student participants 
must be recruited from academic institutions where research opportunities in STEM are limited 
(including two-year colleges)."

(source: NSF REU Program Solicitation)

As a UTD student, you might also consider opportunities which fully pay for your rent during the school year, like being a University Village Peer Advisor. Furthermore, consider working student jobs on campus. This will ensure that you do not waste extra time commuting to and from your work, and before after your shifts you may even be able to hop into your lab and squeeze some research time in.

Of course these are not ideal scenarios, and you will likely have to work even harder to continue being competitive with your more privileged peers. Nonetheless, I would highly recommend discussing these kind of issues with your research advisor (professor), they may end up being very helpful in how they would like for you to work and interact with the lab. And if they are not accommodating, find a new research advisor who will be (they exist! there are many wonderful people at UTD :)).

Finally, and perhaps most importantly, there are sections of the PhD application where you may share your experiences and/or lack of opportunities due to financial struggles. Graduate schools are self-interested and looking to boost their diversity, representation of under-represented groups, etc. If you fall into this category, by all means take advantage of it and share your story. It can only help you if you believe your application is weaker because of a lack of opportunities. Nonetheless, ask your research advisor, they will know best how to "frame your story".