Rejection from Stanford - Again!

There is nothing special about this write-up apart from ranting about the mischievous black box process of candidate selection at Stanford MSCS and other so-called "prestigious" institutions in the United States. So, if you are among those who have been searching for such rants, welcome to the post!

I never had any academic research experience or publications. I did some work in my final year in undergrad, but it was not too intensive to be called a "research" experience. To make up for the lack of academic research experience, I took up a major research project in industry. At Microsoft, I invested heavily in my research in Blockchain during my internship. I learned all ends of Blockchain and almost became a "pro" in it. When I joined Google Ads Infrastructure, I spent 2-3 years improving the data pipelines for the Ads budget and dropping the latency to hundreds of thousands of servers below 1 second. While I am writing this, the research work is yet to be completed. But, I won't lowball the number of research papers I read, the number of experiments I conducted, the years that I spent just to get the design "right," or the number of people I mentored on the way. I admit that this is nowhere close to Ph.D. research. But comparing industry research to academic research is like comparing apples to oranges. The academicians (aka theorists) only need to prove their results on a minute scale and on a bound setup. On the other hand, engineers need to make their product work on every possible imaginable use-case that the world will try to fit it into. Sadly, this doesn't hold any value in the eyes of the professors. They still see the industry as a shitty capitalistic venture of their "not-for-sale" work.

To cover for my lack of academic research experience, I took graduate classes from Stanford Online. The graduate classes treat you the same as Master's students. Your grades will be relative to all the students. I took 5 courses worth 18 credits, which constitutes about 40% of my actual masters. I received an A/A- in all of them, which means that I was able to perform better than 50 percent of the students in each class. I admit that taking these classes really helped me get a taste of graduate-level academic life and its brutal pressure. This combined with a full-time Senior Software Engineer position at Google grilled my life at a high temperature. I spent all day working at Google and then spent all night studying. There were several times when there was a production issue at Google and a deadline to submit assignments at Stanford. Such moments kept me on my toes. There were times when I hated myself for this decision. Especially, when you know the fact that the Stanford student has the liberty of discussing the homework and participating in group study sessions, and you are all on your own fighting to get the best grades. I have burned all my weekends in the last 2 years to prove my worth. I have submitted all assignments on time, followed up on every score deduction, attended several office hours, and answered questions on forums - all to just prove my worth. I hardly have any friends left. Being an immigrant, it was hard for me to adjust to life in this country. Did I mention that I did all this when the recession in the US began? Every time you go to your office, you wish that your badge works somehow. I had no other option if I was laid off! I had to head back to my home country.

Frankly speaking, the Stanford computer science department has several flaws. They are overly driven by industry trends, which are often influenced by Wall Street. Currently, artificial intelligence is the focus, leading to an excessive emphasis on AI courses in the department. They heavily promote their AI courses online, even attempting to link unrelated courses to the AI field. Other subfields of computer science, such as systems, are underrepresented. The department's decision to cancel CS245 (Principles of Data Intensive Systems) is particularly concerning, as it was one of the few dedicated system courses. It is time for the computer science department to focus on a more balanced approach, rather than simply following trends.

Regarding my application, I had strong recommendations from three individuals: an associate professor from my undergraduate college, a Stanford professor, and a Distinguished Engineer at Google. I excelled in a major project for my undergraduate thesis advisor, performed well in a Stanford course, and significantly improved latency in the Ads ML pipeline at Google. Despite these accomplishments, I was not admitted to Stanford. They are *only* looking for an exceptional prodigy with 10,000+ citations on 240 research papers that they wrote from the time when they were 4 years old, and received recommendations from Yoshua Bengio, Ion Stoica, and Elon Musk.

The admission process at Stanford is opaque, making it difficult to understand the decision-making process. I have heard negative stories about the college admission process in the United States, and my own experience confirms the randomness involved. Unlike my home country's entrance exam, which provides clear reasons for rejection, Stanford's vague statement offers little insight - "Each year the number of applicants far exceeds the number we can admit, which makes the decision process difficult and painstaking. As a result, many strong candidates are denied admission to our program". It seems that factors such as race, international status, and socioeconomic background play a significant role in admissions decisions.

I have now given up on applying to Stanford due to the department's unwillingness to address the flaws in their admission process. The lack of transparency and focus on specific criteria make it a frustrating experience for many applicants. The admission committee are unwilling to take a step to change the ridiculous black-box admission process that has plagued every college in the United States. R.I.P. Leland Stanford.