So I've made an attempt at writing an SOP for masters in Data Science based on my profile. I'm not sure if it's effective or if it convesy the value I can bring effectively. I've gone through some good essays and have a decent idea on what should be there.
But any feedback would be much appreciated!
"Try not to become a man of success, but rather try to become a man of value" - Albert Einstein
My career allowed me to explore the vast world of analytics, computer vision and machine learning. It quickly became evident that Data Science would lead the new wave of innovation in industry, and I aim to be a leader and a man of value in it.
Motivation and Purpose
Through my final years of college, and then professional life, I had the privilege to explore and assess where I would fit in industry, and at what capacity. My career helped me explore multiple fields such as image processing, data analysis and machine learning. There is a dearth of cheap technology, and a tremendous scope for research in healthcare - Image processing, NLP, Vision driven robotics etc.
The healthcare industry continues to churn out data like an unstoppable machine, and it requires state of the art technology and engineering to organize and analyze this abundance of information. I dedicated most of my career to solve these problems, and I realized that Data science is the key discipline that will drive development and innovation in healthcare. Problems such as expedited prognosis of biopsies for cancer detection, of blood smears to detect Leukemia etc. require extensive research into how to organize and process the data to provide any insights that is meaningful to the pathologists.
At the University of Minnesota, I find myself drawn towards the research conducted by Dr. Bradley P. Carlin in his studies of Hierarchical modeling and Bayesian analysis, having worked extensively with spatial data myself. I also find strong relations conducted by Dr. James Hodges and his studies in spatial statistics and Bayesian analysis. I would cherish an opportunity to learn from them, and help me achieve my ambitions.
Academic Background
I received my Bachelors' Degree from the prestigious ABC University in Electronics and Communications engineering, with First Class, on August 2014. I developed strong foundations in science and engineering, with my efforts culminating in the publication of an IEEE paper in the ICAECC 2014, titled "PAPER-TITLE", as part of my final year project.
In my second year of college, I was beset with a severe spinal injury that took years to recover from. The direct consequence was a dramatic drop in my grades in my second year because I could neither attend classes nor interact with my professors adequately. However, through perseverance and hard work I managed to not just catch up, but also surpass my peers ensuring graduation in First Class.
Work Experience
My experience in industry played a significant part in helping me narrow down my interests. In COMPANY A, I had the opportunity to work on a variety of projects involving machine learning, computer vision and data analysis. I began my journey deeper into Data Science with the team at COMPANY B.
As a co-founder of COMPANY B, I took upon the analysis wing of a product focused on digital pathology. The main product could accept a blood smear slide, provide visualizations and analyze the slide to provide a CBC and substantial statistical information on every cell present in the ROI, in a manner of minutes. The key objective was to detect and classify over 20 classes of RBCs. To achieve this goal, I had to take a deep-dive into core disciplines of computer vision and machine learning to help extract and classify thousands and thousands of blood cells.
There was a balance leveraged between Computer Science and Data Analysis, to ensure this product met the high standards of the healthcare industry. I spent mornings plotting numerous graphs, violin plots and heat maps for feature engineering and clustering the numerous classes into separate classes and subclasses. I spent evenings in coding out software architectures to utilize the multi-core systems and writing parallel processes that could facilitate the tools given by machine learning and computer vision in an efficient manner.
One of the hardest problems I had to face was the research and development of a classification pipeline that had to classify nearly 10,000 cells while also extracting statistical information of the cell. This involved intelligent use of core Computer Science disciplines such as Graph networks, Tree structures, parallel programming, algorithm optimization etc., and building image processing and machine learning pipelines using these fundamentals. Numerous data cleaning pipelines were developed and tested for effectiveness and efficiency. My efforts culminated in a product that is undergoing live testing in major hospitals and will soon enter the market as a full-fledged solution.
The skills and perspective I have attained, from my venture into building a product for healthcare from scratch, has led me to appreciate the depth and complexity of a problem, and has instilled discipline and methodical thinking for tackling my projects and coursework at the University of Minnesota.
Future career
I am building my profile to be a leader in technology. However, as Albert Einstein rightly said, I need to become a man of value. The experience and knowledge I gained through industry has been invaluable, but it lacks the depth and sophistication that academia possesses. Depth and sophistication that I can get only through working and studying under academic leaders. It is for this reason that I wish to join the master's program for Data Science in the University of Minnesota - to be a leader and to be a man of value.
But any feedback would be much appreciated!
Statement of Purpose
"Try not to become a man of success, but rather try to become a man of value" - Albert Einstein
My career allowed me to explore the vast world of analytics, computer vision and machine learning. It quickly became evident that Data Science would lead the new wave of innovation in industry, and I aim to be a leader and a man of value in it.
Motivation and Purpose
Through my final years of college, and then professional life, I had the privilege to explore and assess where I would fit in industry, and at what capacity. My career helped me explore multiple fields such as image processing, data analysis and machine learning. There is a dearth of cheap technology, and a tremendous scope for research in healthcare - Image processing, NLP, Vision driven robotics etc.
The healthcare industry continues to churn out data like an unstoppable machine, and it requires state of the art technology and engineering to organize and analyze this abundance of information. I dedicated most of my career to solve these problems, and I realized that Data science is the key discipline that will drive development and innovation in healthcare. Problems such as expedited prognosis of biopsies for cancer detection, of blood smears to detect Leukemia etc. require extensive research into how to organize and process the data to provide any insights that is meaningful to the pathologists.
At the University of Minnesota, I find myself drawn towards the research conducted by Dr. Bradley P. Carlin in his studies of Hierarchical modeling and Bayesian analysis, having worked extensively with spatial data myself. I also find strong relations conducted by Dr. James Hodges and his studies in spatial statistics and Bayesian analysis. I would cherish an opportunity to learn from them, and help me achieve my ambitions.
Academic Background
I received my Bachelors' Degree from the prestigious ABC University in Electronics and Communications engineering, with First Class, on August 2014. I developed strong foundations in science and engineering, with my efforts culminating in the publication of an IEEE paper in the ICAECC 2014, titled "PAPER-TITLE", as part of my final year project.
In my second year of college, I was beset with a severe spinal injury that took years to recover from. The direct consequence was a dramatic drop in my grades in my second year because I could neither attend classes nor interact with my professors adequately. However, through perseverance and hard work I managed to not just catch up, but also surpass my peers ensuring graduation in First Class.
Work Experience
My experience in industry played a significant part in helping me narrow down my interests. In COMPANY A, I had the opportunity to work on a variety of projects involving machine learning, computer vision and data analysis. I began my journey deeper into Data Science with the team at COMPANY B.
As a co-founder of COMPANY B, I took upon the analysis wing of a product focused on digital pathology. The main product could accept a blood smear slide, provide visualizations and analyze the slide to provide a CBC and substantial statistical information on every cell present in the ROI, in a manner of minutes. The key objective was to detect and classify over 20 classes of RBCs. To achieve this goal, I had to take a deep-dive into core disciplines of computer vision and machine learning to help extract and classify thousands and thousands of blood cells.
There was a balance leveraged between Computer Science and Data Analysis, to ensure this product met the high standards of the healthcare industry. I spent mornings plotting numerous graphs, violin plots and heat maps for feature engineering and clustering the numerous classes into separate classes and subclasses. I spent evenings in coding out software architectures to utilize the multi-core systems and writing parallel processes that could facilitate the tools given by machine learning and computer vision in an efficient manner.
One of the hardest problems I had to face was the research and development of a classification pipeline that had to classify nearly 10,000 cells while also extracting statistical information of the cell. This involved intelligent use of core Computer Science disciplines such as Graph networks, Tree structures, parallel programming, algorithm optimization etc., and building image processing and machine learning pipelines using these fundamentals. Numerous data cleaning pipelines were developed and tested for effectiveness and efficiency. My efforts culminated in a product that is undergoing live testing in major hospitals and will soon enter the market as a full-fledged solution.
The skills and perspective I have attained, from my venture into building a product for healthcare from scratch, has led me to appreciate the depth and complexity of a problem, and has instilled discipline and methodical thinking for tackling my projects and coursework at the University of Minnesota.
Future career
I am building my profile to be a leader in technology. However, as Albert Einstein rightly said, I need to become a man of value. The experience and knowledge I gained through industry has been invaluable, but it lacks the depth and sophistication that academia possesses. Depth and sophistication that I can get only through working and studying under academic leaders. It is for this reason that I wish to join the master's program for Data Science in the University of Minnesota - to be a leader and to be a man of value.
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