Today, I met with my friend Wu Hao, who is also a UofT Alumni and my neightbour — we lived only 3-min walk from each other. We finally dined out for the first time together after 1 month and a half since we moved to SF. After dinner, we also took a walk nearby for an hour — the night at SF in this late August is so chilling that we had to go back home early.
At dinner, I asked Wu Hao about his grad school experience at Stanford. He brought up a point that at the first year he was solely focusing on taking courses and doing projects, as most of peer students were doing so, then he realized that it is actually more critical to build connections and exploit startup/entrepreneurial resources at Stanford. So he spent more time at the second year to social with others, exchange startup ideas, participate in school events, and incubate his venture — getting more immersed into the startup ecosystem at Stanford. He said he wouldn’t be able to easily get the investment opportunities and raised sufficient seed money for his startup if he wasn’t at Stanford. There are people who are willing to fund you and help you grow simply because you are a Stanford student. The ecosystem here is way more mature, supportive, and sustainable than in Toronto. So he encouraged me to be full-time if I get accepted into Stanford and fully leverage the opportunity to build connections and leverage all the resources in the ecosystem. That being said, he thinks the schools at the East coast can also be good options — surely the startup ecosystem there is less mature and more sparse, making it more difficult for finding right partners and hiring great talents; on the other hand, the players at the east coast are now more desperate to catch up and thus more willing to bet big on valuable startups and founders, so there could be more seed fundings for students at equivalent top schools.

Today I dived deep into the question whether I should pursue a PhD or a MS. To pursue a PhD, a natural question for myself is which specific research group and a professor I should apply to. So I did some research online to look through the websites of Stanford, Berkeley, MIT, and CMU. I browsed through every Professor in the area of my interest and their corresponding research topics, first at Computer Science, then Computational Science/math as well as operations research. My initial vague description of my interest is “applying machine learning techniques into large scale system design in industries like manufacturing, supply chain, and maybe transportation”. However, the research topics I found in CS department are rarely around these traditional fields: the related topics I found were reinforcement learning in agents, machine learning in MRI, or self-driving robotics. For computation science or operations research, on the other hand, the related topics were more theoretical than I was looking for: convex optimization or partial derivative equation at certain problem space. There’s really very few research lab that lies in the middle area that I am interested in.
Then I also searched for some high quality blogs regarding suggestions of selecting and preparing for PhD programs, mostly written by post-doc or professors at the top CS schools. The common takeaways from these articles are 1) the PhD programs are meant to be focus heavily on depth, instead of width as BS/MS programs do; 2) PhD is mostly about research; if your life after PhD is not to do research, then it is a waste of time to take PhD. Based on these two messages, the PhD is not the right way for me. The master program fits my goal better in terms of to learn the best CS and AI courses and build connections that help me to start my own ventures. I used to mis-interpret the value and goals of the PhD programs, which misled me at the decision between PhD vs. Master. Now by clearing articulate their differences in value proposition and purpose, this is no longer a hard-to-make choice for myself.
Another valuable takeaway from reading those blogs is that I found my previous application strategy was not efficient, or in some perspective, totally wrong. I tried to emphasized every possible advantages I had: research experience, publication, strong recommendation, work experience. However, for MS programs, especially the industry-oriented ones, the most important criteria of the admission committee on a candidate is whether the candidate could finish the course-work successfully; whether the candidate has the sufficient CS foundation, intelligence, and initiative to finish the challenging courses in the program and graduate successfully. Therefore, I should tail my statement of purpose and other materials more towards this aspect. Instead of trying to list out all the advantages but academic strength, I should prioritize my interest towards CS and my competence to finish Stanford’s MS-level courses.