keshavchaurasia
Aug 25, 2022
Graduate / SOP for PhD in Computer Engineering - Professor has already onboarded me after conducting interview [2]
Computers are used in unimaginable scenarios, ranging from complex simulations to artificial intelligence and cracking the human genome riddle. The one magic entity that drives all these scenarios is High-Performance Computing(HPC). Its ability to solve real-world problems with vast computations has motivated me to pursue my Ph.D. program in Computer Engineering.
With the scholarship obtained on being in the top 2% out of 15000 applicants, my undergraduate journey provided me with intellectual stimulation and growth in the form of various academic projects and labs. I learned parallel programming, distributed systems, algorithms, and artificial intelligence through computer organization and architecture, big data, and data mining courses.
For the final year project, I worked on real-time network intrusion and malicious URL detection. I worked on the real-time streaming solution using message queuing protocol and a fully-connected neural network model to detect network intrusion. Later, it caught the attention of the data-center company that gave us to work on a proof-of-concept to build SaaS-based suspicious behavior detection of users using their firewall logs. I built a highly scalable application with an autoencoder-based anomaly detection model capable of processing gigabytes of data daily, and this piqued my interest in building large-scale computing.
Throughout my professional experience, I have gained software engineering, data engineering, data analytics, and machine learning skills. At Cloudfactory, I took the initiative to build a skill-based task recommender system using Collaborative Filtering and SVD-based Matrix Factorization algorithm to match potential workers with relevant tasks, which increased the recruitment and onboarding speed by 25%. With Omdena, I am working voluntarily on a credit scoring algorithm to provide creative machine learning solutions for unbanked Nigerians. Instead of traditional credit assessments, we will be using transactional sales of food subscription companies to build a model that can infer if a person is fit to achieve micro-loans for food subscriptions.
My academic and work experiences have kindled my interest in diving deep into the field of algorithms, deep learning, and optimization research. I am fascinated by the immense capabilities of HPC and would like to explore distributed system design, parallel computing, and hardware exploitation for task optimizations. The high-quality pioneering research on HPC in the HPDA lab at XXX will be a great place to learn and work to achieve these goals. Specifically, Dr. ABC's expertise in exploiting emerging hardware to build high-performance systems for graph computing and machine learning profoundly interests me, and it would be a privilege to work under his supervision.
XXX, with its rich blend of computer faculty, intense curriculum, and state-of-the-art laboratories, is the ideal fit to shape my career. I am aware of the challenges and hardships of graduate research and am confident that commitment, sincerity, and passion will guide me through it successfully. I believe that my research experience, coupled with professional exposure, would enable me to excel in my graduate studies and contribute productively to the research.
STATEMENT OF PURPOSE
Computers are used in unimaginable scenarios, ranging from complex simulations to artificial intelligence and cracking the human genome riddle. The one magic entity that drives all these scenarios is High-Performance Computing(HPC). Its ability to solve real-world problems with vast computations has motivated me to pursue my Ph.D. program in Computer Engineering.
With the scholarship obtained on being in the top 2% out of 15000 applicants, my undergraduate journey provided me with intellectual stimulation and growth in the form of various academic projects and labs. I learned parallel programming, distributed systems, algorithms, and artificial intelligence through computer organization and architecture, big data, and data mining courses.
For the final year project, I worked on real-time network intrusion and malicious URL detection. I worked on the real-time streaming solution using message queuing protocol and a fully-connected neural network model to detect network intrusion. Later, it caught the attention of the data-center company that gave us to work on a proof-of-concept to build SaaS-based suspicious behavior detection of users using their firewall logs. I built a highly scalable application with an autoencoder-based anomaly detection model capable of processing gigabytes of data daily, and this piqued my interest in building large-scale computing.
Throughout my professional experience, I have gained software engineering, data engineering, data analytics, and machine learning skills. At Cloudfactory, I took the initiative to build a skill-based task recommender system using Collaborative Filtering and SVD-based Matrix Factorization algorithm to match potential workers with relevant tasks, which increased the recruitment and onboarding speed by 25%. With Omdena, I am working voluntarily on a credit scoring algorithm to provide creative machine learning solutions for unbanked Nigerians. Instead of traditional credit assessments, we will be using transactional sales of food subscription companies to build a model that can infer if a person is fit to achieve micro-loans for food subscriptions.
My academic and work experiences have kindled my interest in diving deep into the field of algorithms, deep learning, and optimization research. I am fascinated by the immense capabilities of HPC and would like to explore distributed system design, parallel computing, and hardware exploitation for task optimizations. The high-quality pioneering research on HPC in the HPDA lab at XXX will be a great place to learn and work to achieve these goals. Specifically, Dr. ABC's expertise in exploiting emerging hardware to build high-performance systems for graph computing and machine learning profoundly interests me, and it would be a privilege to work under his supervision.
XXX, with its rich blend of computer faculty, intense curriculum, and state-of-the-art laboratories, is the ideal fit to shape my career. I am aware of the challenges and hardships of graduate research and am confident that commitment, sincerity, and passion will guide me through it successfully. I believe that my research experience, coupled with professional exposure, would enable me to excel in my graduate studies and contribute productively to the research.
