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.
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.
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.
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