Akhilesh

Enthusiastic Computer Science graduate specializing in Data Science with a focus on Deep Learning and Neural Networks. Former Research Trainee at DRDO, contributing to the development of a deep learning-based cryptanalytic tool for stream ciphers. Have hands-on experience in projects like Spotify Data Analysis and Emotion Recognition using CNN architecture. Published research paper on wheat crop yield prediction using machine learning and another paper presented on deep learning based cryptanalysis of stream cipher Espresso. Eager to work, learn more and apply knowledge and proactive problem-solving approach to innovative projects in the field of Data & AI

• Published Research paper "Wheat Crop Yield Prediction Using Machine Learning", https://ieeexplore.ieee.org/document/10041621, The effectiveness of yield parameters on wheat such as average rainfall, pesticides, and the average temperature on the yearly basis was calculated.
• Research paper presented on "LSTM-based cryptanalysis of Stream Cipher Espresso"

• Development of deep learning based cryptanalytic tool for stream cipher: Worked as a research trainee in the "Development of deep learning based cryptanalytic tool" for stream cipher. worked on implementing code for a cipher and generate data, convert from hexadecimal to binary formats and applied deep learning to check for bias in the cipher's use.
• SPOTIFY DATA ANALYSIS PROJECT: Exploratory data analysis on a data set of Spotify songs to see which attributes and features increase the "popularity" metric. The project has EDA (Exploratory data analysis), and based on the result we have an ML model to recommend songs based on the artist (recommender system).
• Emotion Recognition Project: A live video-based emotion recognition software using CNN architecture built from data set of different emotions.

• Seventh Edge Data Science Certificate
• Hackerrank certificates: Java Basic, Python Basic, SQL Basic
• AWS-Going Cloud Native