Statement of Purpose
Describe in your statement of purpose:
Your reasons for applying to the proposed program at Stanford and your preparation for this field of study
Your research and study interests
Future career plans and other aspects of your background and interests which may aid the admission committee in evaluating your aptitude and motivation for graduate study
My goal is to further my understanding of Machine Learning, Artificial Intelligence, And Distributed Systems (Databases). I want to help further advancements in these fields, and I believe that my academic and work experience has given me the education and experience to learn and contribute at a high level. I graduated from one of the top 25 undergraduate computer science programs in the nation.
Afterwards, I worked as a software engineer at Oracle, the second-largest software maker in the world. At Oracle, I maintained the company's complex software system by tuning Oracle database clusters for my team through updating the database indices of various attributes in multiple tables. At Oracle, I built a testing suite that ensured validity of over 10 terabytes of data from such leading multibillion corporations such as KPMG and Pearson everyday. Through such intense work on large-scale software, I was able learn data analytics on a deeper level, including attaining the opportunity to exhaustively study the clandestine, cutting edge data analysis concepts such as K-Means Clustering algorithm. By fully taking advantage of the rare chance to learn such advanced methodologies, I came to realize that I needed to return to higher education to learn from people at the forefront of Artificial Intelligence and Machine Learning.
I wanted to deepen my mastery of real-world large scale data. Thus after learning all that I needed at Oracle, I went on to a new challenge. I began working on a cloud platform at a leading video content revenue security startup company, Verimatrix. There, I spearheaded a project on creating a data ingestion pipeline for analyzing millions of megabytes of log data in Verimatrix's software. I built the data ingestor on top of Amazon Web Service (AWS), which provided Verimatrix's machine learning software with the crucial ability to recognize hackers and security breaches by analyzing patterns in the systems' log activity. At Verimatrix, I employed the availability over consistency concept (PACELC) strategy to solve the rampant outages that plagued the company. My utilization of the strategy guaranteed that none of Verimatrix's customers experienced service downtime. I was thus able to help keep Verimatrix's revenue of over $50,000,000 from huge cable and satellite companies, such as SwissCom, ChungHwa Telecom, and DishTV. In directing these large-scale projects at Verimatrix, I was able to learn advanced distributed systems methodology, which furthered my desire to pursue my masters and learn even more.
I was able to consistently build upon the thorough computer science education I received at the University of California, Santa Barbara (UCSB). At UCSB, I consolidated my fundamentals in Data Structures and Algorithms in addition to studying the most commonly used Cryptographic algorithms used on the web. I also excelled at my Relational Database Course, which was critical in landing me a Software Engineering position at Oracle. Just as importantly, I learned the fundamentals of teamwork as I was able to work efficiently on my specific technological strengths, which enabled my teammates to excel in their own areas of expertise at both Oracle and Verimatrix.
I am currently working at a Startup Incubator, Cogo Labs, as a data engineer. At my current job, I have first hand experience with how Machine Learning (One to One Ad Targeting Recommendation) is changing the email marketing and web advertising landscape. My typical day involves writing evolutionary Spark ETL jobs and legacy Hadoop MapReduce jobs that migrate terabytes of data within minutes. As a result, I encounter issues with scalability and problems with disaster recovery that require a deeper knowledge of databases and innovative strategies for managing distributed systems. To bolster my career without compromising my interest in contributing to Cogo Labs, I believe the Stanford Computer Science program offers the perfect solution to advance my career at Cogo Labs.
Describe in your statement of purpose:
Your reasons for applying to the proposed program at Stanford and your preparation for this field of study
Your research and study interests
Future career plans and other aspects of your background and interests which may aid the admission committee in evaluating your aptitude and motivation for graduate study
deepening my mastery and understanding
My goal is to further my understanding of Machine Learning, Artificial Intelligence, And Distributed Systems (Databases). I want to help further advancements in these fields, and I believe that my academic and work experience has given me the education and experience to learn and contribute at a high level. I graduated from one of the top 25 undergraduate computer science programs in the nation.
Afterwards, I worked as a software engineer at Oracle, the second-largest software maker in the world. At Oracle, I maintained the company's complex software system by tuning Oracle database clusters for my team through updating the database indices of various attributes in multiple tables. At Oracle, I built a testing suite that ensured validity of over 10 terabytes of data from such leading multibillion corporations such as KPMG and Pearson everyday. Through such intense work on large-scale software, I was able learn data analytics on a deeper level, including attaining the opportunity to exhaustively study the clandestine, cutting edge data analysis concepts such as K-Means Clustering algorithm. By fully taking advantage of the rare chance to learn such advanced methodologies, I came to realize that I needed to return to higher education to learn from people at the forefront of Artificial Intelligence and Machine Learning.
I wanted to deepen my mastery of real-world large scale data. Thus after learning all that I needed at Oracle, I went on to a new challenge. I began working on a cloud platform at a leading video content revenue security startup company, Verimatrix. There, I spearheaded a project on creating a data ingestion pipeline for analyzing millions of megabytes of log data in Verimatrix's software. I built the data ingestor on top of Amazon Web Service (AWS), which provided Verimatrix's machine learning software with the crucial ability to recognize hackers and security breaches by analyzing patterns in the systems' log activity. At Verimatrix, I employed the availability over consistency concept (PACELC) strategy to solve the rampant outages that plagued the company. My utilization of the strategy guaranteed that none of Verimatrix's customers experienced service downtime. I was thus able to help keep Verimatrix's revenue of over $50,000,000 from huge cable and satellite companies, such as SwissCom, ChungHwa Telecom, and DishTV. In directing these large-scale projects at Verimatrix, I was able to learn advanced distributed systems methodology, which furthered my desire to pursue my masters and learn even more.
I was able to consistently build upon the thorough computer science education I received at the University of California, Santa Barbara (UCSB). At UCSB, I consolidated my fundamentals in Data Structures and Algorithms in addition to studying the most commonly used Cryptographic algorithms used on the web. I also excelled at my Relational Database Course, which was critical in landing me a Software Engineering position at Oracle. Just as importantly, I learned the fundamentals of teamwork as I was able to work efficiently on my specific technological strengths, which enabled my teammates to excel in their own areas of expertise at both Oracle and Verimatrix.
I am currently working at a Startup Incubator, Cogo Labs, as a data engineer. At my current job, I have first hand experience with how Machine Learning (One to One Ad Targeting Recommendation) is changing the email marketing and web advertising landscape. My typical day involves writing evolutionary Spark ETL jobs and legacy Hadoop MapReduce jobs that migrate terabytes of data within minutes. As a result, I encounter issues with scalability and problems with disaster recovery that require a deeper knowledge of databases and innovative strategies for managing distributed systems. To bolster my career without compromising my interest in contributing to Cogo Labs, I believe the Stanford Computer Science program offers the perfect solution to advance my career at Cogo Labs.
