Nikhil Anu

I was first exposed to computer science in my 11th grade and right away I knew that this is what I wanted to do. I started off with learning python, and the power to build almost anything from scratch was very exhilarating. But once I entered college I began to dwell deeper into computer science. My college’s coding culture rubbed off on me and my peers helped me to learn and grow much further. Then my interest in coding grew from a mere leisure to a full fledged burning passion. I started learning algorithms and data structures in detail and started participating in coding competitions. I started building a few projects such as a Telegram bot that gives the weather of any city. This custom made Telegram bot provides weather information including Temperature, Atmospheric pressure, humidity and sky description. The user has to input in a City name and the bot returns the weather information. Then I built an attendance manager that uses a QR code to track attendance, so basically every student will have a unique QR code. Once this Qrcode is scanned the details of the student will be save to an excel sheet. Then I started web development and learned front end and backend in a span of two months and I made a couple of sample websites. Then I went into iOS app development and learned Swift and made a few apps. From there onwards there was no turning back. I started doing courses on machine learning. I was particularly interested in natural language processing. So I started learning more on NLP and I really wanted to pursue it further. I worked as an intern in my second year at the Reasoning and Data Analytics for Security Lab at the University of Houston. The project work involved working on Automatic Text summarization using Data Mining and to characterize if there are statistically significant differences between the human summaries and the original articles being summarized. Also worked on some Natural Language Processing tasks relevant to phishing detection. I wrote a research paper statistically analyzing how humans summarize documents using the DUC dataset. Tested the best constituency parsers for conducting the experiments. The parameters used for the analysis were syntactic categories, voices and part of speech tagging. I really liked the project that I worked on and I ended up making an iOS app that summarizes documents fed into it. This app utilizes NLP techniques to summarize a given document or text data. It then calculates the word and sentence optimization and gives an insight into the effectiveness of the generated summary. I then started collaborating with my peers to make bigger projects . We made a bill splitting bot on telegram. This was a challenging real world project and my learning curve shot up as I had to look up on many new topics and interleave all the concepts flawlessly to get a highly functioning real world application that anyone can use and this was the first time I really focused on writing clean and highly readable code. For this project I learned to use telegram api, Opencv, postgresql, named entity recognition and many more. So what the bot does finally is that the user takes the photo of the bill and each person lists the item he ate from the bill. The bot will split and specify each person’s share and who he has to give the money to. I then wanted to contribute to the open world community and I participated in the Hacktoberfest and I made a couple of pull requests on github. In conclusion I really enjoying doing my work and I wish to make a better impact on the world using my skills.