In my undergraduate studies, I realized a profound predilection towards signal processing (SP) and developed a strong desire to integrate it with nonlinear analysis and machine learning (ML) concepts. I believe this domain has a myriad of applications in Industy, which has engendered from my academic and professional experiences. These have been crucial in shaping my long-term goals, specifically, researching the various untapped areas of core SP and ML. With this motivation, I am currently pursing the Master of Science degree in Electrical and Computer Engineering at Purdue University, West Lafayette, Indiana.

Data Analytics Intern, IIM Lucknow, India

In the early years of college, I realized that framing hypotheses and working with an exploratory freedom complements me immensely. It was only in the summer of the second year that I really began to enjoy and understand the intricacies of electrical and computer engineering. I worked as a Data Analytics intern under the guidance of Prof. Sameer Mathur at the Indian Institute of Management (IIM) Lucknow. The internship exposed me to several unique ways to analyze data and how data-driven decision making could achieve effective results. In addition, I analyzed three Harvard Business Review Case studies exploring disparate scenes, which greatly helped me in developing the skill of hypothesis analysis and the ability to comprehend, assess, and explore pragmatic alternatives. I thoroughly enjoyed the internship, which helped me substantially augment my creativity and critical thinking skills and, efficaciously, steered me towards exploring research projects.

Reasearch Intern, NIT Rourkela, India

During the summer of 2018, I worked as a research intern in the Department of Biomedical Engineering at the National Institute of Technology (NIT) Rourkela under the guidance of Prof. Kunal Pal. My objective was to correlate cardiac electrophysiology and smoking across three stages of menstruation, which could greatly help clinicians in designing effective gender-specific tobacco control policies for smoking cessation among women. I designed an algorithm and incorporated concepts of recurrence analysis, a core mathematical concept of chaos theory, as a method of analysis. The results strongly supported my initial hypothesis of variation in the RRI signals (indicating cardiac autonomic regulation) between female smokers and non-smokers, in various phases of the menstrual cycle. Our efforts in this study were rewarded when a research paper I wrote titled “Recurrence Quantification Analysis of RR Interval Signals of Female Smokers and Non-smokers during Different Phases of Menstrual Cycle’’ was selected to be presented at the IEEE INDICON 2018 conference. Through this project, I learned that one often has to think unconventionally and look into some unexplored areas to tackle intellectual problems and develop practical solutions.

Senior Year Thesis, Manipal Institute of Technology, Manipal, India

I wanted to fathom the study on cardiac electrophysiology and smoking further, and so, I delved deeper into cardiac autonomic regulation (CAR) of female smokers and non-smokers as my senior year thesis. Prof. Kumara Shama was as enthused as I was with the idea and readily agreed to guide me. The aim was to perform a comparative analysis of the previous method with other potential methods and explore CAR alteration to understand future implications better. Hence, I learned and applied various nonlinear analysis concepts such as Lyapunov exponents and Poincare Plots on the temporal RRI Signals data, which directed me towards ARMA modeling, and Empirical Mode Decomposition analysis approaches. I concluded each method’s suitability in the ECG data context through detailed comparison analysis. Overall, the study gave me glimpses of what advanced research entailed and left me with immense encouragement to contribute more to this field.

Project Engineer, Wipro, Pune, India

While working as a Project Engineer at Wipro HOLMES (the AI and Automation platform that develops cognitive solutions for businesses), I was given an opportunity to work on processing client’s employee ID card images using OpenCV and Tesseract OCR, to extract specific text that could be used for authentication. Later, I was tasked with developing ML models for the client’s call transcript auditing platform, using natural language processing (NLP) specifically, fasttext AI and Spacy models to analyze caller sentiment and assess call quality. The goal was to ultimately ease the process of patient claim experience by providing a substantial improvement to the efficacy of call quality assurance through automation and data-driven analysis, thereby aiding the already overburdened healthcare ecosystem. This experience provided me with a chance to collaborate with seasoned professionals and receive exceptional Industry experience.

General Leader and Scripting expert, Security Education For All (SEFA) group, Purdue University, Indiana

During the spring 2022 semseter at Purdue, I was given an opportunity to lead the “Program Analysis as a Service” team (a team of four undergraduate students) under the guidance of Prof. Aravind Machiry to work on integrating security education into programming courses by specifically, focusing on developing frameworks and infrastructure to use existing security tools in the curriculum. For this purpose, a collaborative fuzzing framework to perform automated testing of advanced C++ programming course student submissions was developed, leveraging parallel mode of AFL++ and using Python. A one-click grading system, that performs grading of student submissions with a single click automation was designed by integrating developed fuzzing framework into “Github Workflow”. This experience has given me an opportunity to alter roles from leadership to followership whenever required, and also exploring the field of fuzz analysis.