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PHD EECS, Electrical Engineering, Computer Science, Vision, Machine Learning, Medical Applications

Updated: Jul 7

I was raised in a small village in India by parents who had not benefited from much education. Educating girls was not a priority in my culture, and it took great determination and hard work to achieve what I had. Early on, it was clear that I had a natural facility for dealing with numbers, which quickly developed into a passion for mathematics and, subsequently, computer science. I have never regretted choosing such a fascinating field where many rapid and exciting advances are made.

I was awarded my Bachelor's degree in I.T. at the prestigious Jaypee Institute of Information Technology. I was awarded an Indian Army ‘Bright Student Scholarship’, my father being an Indian Army veteran. I earned my Master’s in Computer Science at the University of Massachusetts, graduating with a creditable GPA of 3.77.

My undergraduate studies centered on mathematics: Calculus, Applied Linear Algebra, Numerical Optimization, and Probability. In my senior year, I worked on developing a ‘Military Simulator’ as my ‘capstone project.’ This was prompted by an interest in military matters arising from my father’s career as a soldier. This project was designed in Unity 3D and involved data extraction from designed simulation systems. I also applied Data Mining techniques to predict the probable outcome of certain events and published two Journal Research papers at IJCA and IJCSIT. These experiences fired my interest in research, which I now passionately hope to pursue within the program.

My internship was spent working under the supervision of Professor XXXX of the Indian Institute of Science Education and Research. During this time, I explored the applications of Tropical Geometry and completed a project on the formation and simulation of phylogenetic trees using hamming distance.

To gain practical experience, after my graduation in June 2014, I joined SAP Labs as a Software Engineer in the S/4HANA suite. I handled the development and deployment of a Product Lifestyle Management application. I then decided to enhance my skills and knowledge in Machine Learning by pursuing a relevant Master’s program, which led to my joining the Computer Science program at the University of Massachusetts.

During my time at UMass, I focused on Data Science and enrolled in courses: Machine Learning, Algorithms for Data Science, Computer Vision, Neural Networks, etc. To explore my domain interest in Machine Learning, I initially decided to work on an NLP-based research project, ‘Concept/Theme Generation,’ under Professor Andrew McCallum’s supervision. After exploring NLP, I focused on computer vision research topics such as Capsule Networks, One-Shot Learning, and Video Summarization. My work on One-Shot Learning involved improving Siamese Networks Architecture embedding learning using Kernel Functions. It was accepted at NeurIPS’18 Workshop as Poster Presentation and will be published in Springer AISC’20 proceedings. At the same time, my work on Video Summarization using keyframe extraction methods has been widely appreciated on Github and was a trending paper on arxiv.

I have also worked on the Multi-Arm Bandit problem besides computer vision under Professor XXXX's guidance. This involved designing an algorithm to find a Supremum (Lower upper bound) on an unknown data sample compared to the Central-Limit theorem. For my internship, I worked at Autodesk as Machine Learning Intern and explored practical aspects of AI. I worked on Revit, modeling software for architects, and improved the recommendation algorithm by modeling a probabilistic graph that traverses using the Bayesian approach. This internship helped me understand one of the practical aspects of AI and the potentially significant effects and potential of machine learning on business success.

Since being awarded my Master’s degree, I have acquired valuable and relevant experience. I worked for eight months as a Machine Learning Engineer on various vision-related projects. I have also worked under the guidance of Dr. XXXX at the Brain Injury Outcomes Lab at John Hopkins on a Brain Injury Segmentation project, during which I was exposed to applications relating to Computer Vision and Machine Learning in the healthcare domain. My interest in this field led me to work with Bayer on CTEPH classification cases using lung scans. I became aware of the limitations of AI in healthcare due to data constraints but decided to explore fields other than Computer Vision and initiated a project with UMass IESL on ‘Disease Progression Using Clinical Observations’ in which we experimented time-series models to predict Sepsis progression using ECG data.

I am the author of a book, ' Hands-on One-Shot Learning’, which is due for publication in February. The book summarizes the latest ‘one-shot’ learning methods in Deep Learning and Probability, and I am confident that it will be helpful to many in the field.

My current goals are: to acquire the considerable skills, knowledge, and experience that the program will provide to maximize my utility, undertake research related to solving practical problems that will benefit many, and t pass on my passion to others. I feel privileged to work in a field that affects, and can improve, many aspects of people’s lives. However, I am also alive to the ethical considerations and dilemmas that may sometimes be faced in using AI.

My particular research interests relate to Computer Vision and Machine Learning. I should be particularly interested in pursuing a project on training a machine to undertake computer vision tasks in a low-data regime with medical applications. I know this will not always be possible, and that classification has been well explored. Still, I think there is significant potential in object detection and segmentation. I am aware that successful research is born of original, critical, and creative thinking together with determination. I know these are unique characteristics, but I feel confident that my academic and practical background assures that I possess them and have the potential to develop and enhance them further within the program and in my future work.

I know that collaboration with others is a vital key to successful research. I am a cheerful, outgoing person who gets on well with others. I have happily studied, worked, and socialized with people of various social and ethnic backgrounds. I am interested in other cultures and ready to share my rich cultural heritage knowledge. I am also an active contributor to ‘Women in Tech’ communities through GHC and WiML. In addition, I taught an undergrad class on the ‘Introduction to Cybersecurity course at UMass to encourage more women to enter the technology field.

I am especially attracted to the EECS Ph.D. Program at XXXX because of its prestigious faculty, its success, reputation in the field, impressive research facilities, and assurance that I shall be among other equally enthused students of this area of study. I believe that my academic and practical background will provide a firm basis for me to excel rather than merely succeed in the program and my career beyond. If selected, I can assure the reader of committed, enthusiastic, and diligent participation in the program.

Thank you for considering my application.

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