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I'm applying to top computer science MS programs hoping to study (and research) machine learning

isrxz 1 / 1  
Nov 18, 2017   #1
Hi all, I'm applying to top computer science MS programs hoping to study (and research) machine learning. My SOP is below and I would be so so grateful if you could write any sort of feedback, positive or negative for my essay. I've attached my (pre-EssayForum-reviewed) SOP that I plan to send to Stanford University. I will also be applying to other programs, making the appropriate changes (removing mention of Stanford University stuff and adding related stuff for the next university). It might be a little long, but it fits within the 2 page limit. Here's the SOP. Thank you so much for taking a look, I appreciate it so much.

Machine Learning M.S. SOP

Research in computer science (CS) is revolutionizing the world, bringing civilization to previously-thought impossible bounds: quantum computers with computing power thousands of times greater than classical binary computers are estimated to be practical in the next 5 years while artificial intelligence (AI) has brought about self-driving cars and video game players that rival the world's best human players. I have been totally in awe of the power of AI and highly interested in its mathematical foundations since I started studying at the <my university's name>. More specifically, I have developed deep interests in a number of subfields of machine learning (ML). In particular, I have found natural language processing (NLP) and reinforcement learning (RL) to be extremely interesting, powerful, and applicable to the real world. Hence I wish to continue my studies through Stanford University's M.S. in CS program to grow in my understanding of various fields within ML, thereby enabling me to pursue my career goals of researching the fascinating field of ML. I believe that my university career has reflected my passion for this field of study through both my coursework, research, and extracurriculars.

In my first year, I enrolled in the introductory AI course. I soaked in every topic presented to me and implemented a number of them myself, outside of the required coursework, gaining a solid foundation for further studies. The following year, I took a number of additional courses in fields within AI, including the graduate ML course, and walked away with not only a handful of instructive projects and a better understanding of the mathematical foundations of ML, but also an even deeper thirst for knowledge. By the end of my third and final year, I will have taken the graduate data science course and an online deep learning course by Stanford University's own Dr. Andrew Ng. I have simultaneously complemented my studies of computer science with studies in mathematics, because studying advanced ML techniques has required me to have a strong mathematical foundation. Furthermore, I am able to apply the knowledge I've gained from statistics-flavored math courses in many ML problems, because these problems often times reflect the real world, a highly stochastic environment. As a result of this double major background, I possess a unique mindset giving me multiple approaches for solving ML problems. In summary, I have completed substantial coursework in my area of interest, but my actions outside of academics have also reflected my passion for ML.

Out of interest and appreciation for the study of ML, I have become involved in researching. At the beginning of my second year, I chose to join a ML research lab under Professor <name of well-known professor at my university>. Our research project focuses on the design of a "machine teaching" tool that guides users to learning programming concepts in the most optimal manner. As a research assistant, I had hands-on experience with developing a speech interface for an application that teaches computer programming. In this position, I owned the grammar that dictated the structure of the allowed commands and the translation of speech into actions. Additionally, I pioneered the suggestions tool that provides users with continual feedback as a means of machine teaching, guiding users towards learning to solve the programming problems. Additionally, I handled our database and contributed to the analysis of our data. Furthermore, I played a key role in developing our novel algorithm for inferring intended speech utterances from generally inaccurate speech recognitions. By the time I graduate, I will not only have gained two full years of research experience within the field of NLP, but I will also have developed an even deeper understanding of and interest in ML.

In further progressing towards a better understanding of ML techniques and contributing to the ML field through research, I have started an undergraduate honors thesis under Professor <another professor at my university, less well known than the first that I mentioend>. In developing my thesis, I am conducting original research in the state-of-the-art of reinforcement learning (RL), a special field of ML that is concerned with the development of artificially intelligent agents that learn from their environment. Through this research experience, I have implemented multiple algorithms like the classic Q-learning algorithm, a Deep Q-network learning algorithm, and an asynchronous multi-agent RL algorithm and conducted several experiments evaluating the performance and training times for these algorithms, acquiring a far deeper understanding of RL. By the end of this academic year, I will have completed a research paper detailing my studies of the subject as well as an innovation in the field that improves the training performance of a RL agent and gained a substantial amount of research experience.

Outside of coursework and academic research, I have also pursued growing the community at the <my university> that is interested in artificial intelligence. To this end, I co-founded the student organization <club name> where we have created teams that work on getting hands-on experience with AI by developing AI-inspired applications. As head of engineering, I lead our teams in applying AI to domains within the interest of our members. As an example, I'm leading one of our teams in creating a facial recognition application to be used as a method for authentication in our members portal. We are also setting up collaborations with research labs on campus to give our members research experience, as research can truly help deepen one's understanding of AI. Furthermore, our club members will be giving talks about their areas of expertise to grow interest in AI within the community at the <my universirty>. Through this experience, I have been able to share my passion for AI with others, making new friends and gaining practical knowledge in the applications of AI along the way.

Through my coursework, research experiences, and extracurriculars, I believe that I have shown myself to not only be deeply interested in the field of ML, but also adequately equipped to study the subject at a deeper level in graduate school. But this may bring about the question of what I plan to do with the knowledge and experience that I wish to gain from Stanford University's M.S. in CS program. While enrolled in the program, I would cherish the opportunity to learn from some of the world's best experts in AI. Not only would I have excellent resources and amazing classmates, but I would also be inspired continually by all of the research that Stanford University is involved in. Hence, I would be so excited to become involved with Stanford Artificial Intelligence Laboratory in researching topics in ML. In fact, I have been communicating with <professor at Stanford> in about a specific paper she co-authored and her continuation of research on that topic. In terms of post-masters career goals, I would love to continue in researching ML, either in industry or academia. This is because I know that ML is so incredibly powerful in terms of the problems it can solve, and using the knowledge, skills, and experience that I will have gained from the program to contribute to this exciting field is the best career I can think of. As such, I know that receiving admission into Stanford University's M.S. in CS program would give me the best tools for researching the next state-of-the-art ML technologies and am so honored for your consideration of my admission into the program. Should I be granted admission into this amazing university, I will undoubtedly carry on the Stanford University tradition of creating world-changing research.
Holt  Educational Consultant - / 12,703 4121  
Nov 18, 2017   #2
David, I am wondering about something. Why are all of your references academic in nature? Haven't you had any professional experience in the field yet? Normally, a person interested in taking an MS course has at least a 2 year professional experience backing his application. It creates a stronger sense of your abilities in terms of course preparation and advanced skills requirements. Everything that I have seen in this essay focuses solely on your undergraduate research accomplishments. I believe that you need to produce more than that in order to prove the basis if your preparation for the masters course. You need to at least prove that you have done 2 years of non college related research in order to enhance your application qualifications.

A deep interest in the field does not constitute a purpose for your desire to acquire a masters degree. Aside from continued learning, how else do you hope to use this masters course within your profession? That is the purpose that you need to highlight here. Simply saying that you want to learn more about the interesting field or you want to grow you understanding of the future applications of Machine Learning is not sufficient. You need to prove that you have a desire to further improve or contribute to the advancement of the field through a particular passion, research, or optimization of a specific set of current performance considerations of machines.

So far, your essay is just a lengthened resume of your college studies. It does not prove that you are capable of accomplishing the requirements and surviving the rigors of MS studies. About the name of the Stanford professor, do not include it. If the professor is not going to be supporting your application through a recommendation letter or personal endorsement of your application, mentioning the name of that person does not serve a purpose. It appears from what I have read that there is no such foundation for your mentioning this professor so it would be best to remove the reference altogether. Name dropping in this instance could hurt your application.
OP isrxz 1 / 1  
Nov 18, 2017   #3
Thank you so much for taking the time to read my SOP and give helpful feedback.

To answer your question of work experience, Im a college undergraduate at the moment and only have a (non-research) internship at a "big 4" tech company. I believe I also discussed my coursework (which I have gotten perfect grades in, which I left out of the SOP because its on my transcript) as an argument for my preparation. As I noted in my essay, I would like to do research in machine learning as a career, but most of these positions require graduate degrees. I also know a number of people who went to Stanford straight after undergraduate.

You're right, I should talk more about how I will use the knowledge I gain!

Thanks for the tip about "namedropping," do you think I should still include the bit about the professor, ommitting his/her name, or dropping the topic altogether?

Again, thank you so much. I will post an updated essay.
keneshuku 4 / 12 1  
Nov 19, 2017   #4
Hi, you can also add group projects in machine learning that you have worked on outside of school (maybe for startups or for a good cause like health),

if you are not held by an NDA probably add some of the mind-blowing projects you worked on during your internship with "the big 4 tech company ". should help strengthen your application.


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