Akshay Hebbar

Introduction

© 2023 Akshay Hebbar. All rights reserved.

Hello and Welcome to my personal website!
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I am thrilled to have you here. My name is Akshay Hebbar, and I am a passionate and driven individual with a background in Computer Science and a focus on cutting-edge technologies. On this platform, I aim to share my journey, experiences, and projects that have shaped my career so far.

Hailing from a humble background, I started my tech journey in my 11th grade when I received my first personal computer in 2011 and yes! it came with a CRT monitor. I have started my programming voyage from TURBO C and have moved all the way up to Java, Python, Frameworks and Machine Learning.

Graduating with a Master's in Computer Science from Syracuse University and a Bachelor's from Visvesvaraya Technological University in Bengaluru, India, I have honed my skills in areas such as Algorithms, REST API's, AI, Data Science, and more. Throughout my academic journey, I have delved into fascinating courses like Data Mining, Reinforcement Learning, and Natural Language Processing, among others and have had the chance to learn from some incredibly passionate people.

Throughout my professional journey, I have embraced challenging projects and actively participated in various innovative endeavors. From crafting and deploying Spring Boot microservices to creating cutting-edge Machine Learning models, I have continuously sought opportunities to make meaningful contributions to the ever-evolving world of technology.

As you navigate through this website, you'll discover a compilation of projects that reflect my love for problem-solving and my eagerness to explore new frontiers. I am always eager to collaborate, engage and learn from like-minded individuals, so feel free to connect with me through my social channels or contact me directly. Let's embark on this technological journey together and make a meaningful impact on the world of Computer Science.

Please do check out some sample of my work here.

I am a native ಕನ್ನಡಿಗ currently residing in New York. Click here to know more about the language

Academics

Masters of Science in Computer Science
Syracuse University, College of Engineering and Computer Science
New York, USA August 2021 - May 2023

Courses

• Artificial Intelligence
• Principles of Operating Systems
• Design and Analysis of Algorithms
• Social Media and Data Mining
• Natural Language Processing
• Reinforcement Learning
• Data Science
• Evolutionary Machine Learning

Bachelor of Engineering in Computer Science and Engineering
B.N.M.I.T (Affiliated to Visvesvaraya Technological University), College of Engineering and Computer Science
Bengaluru, India August 2012 - May 2016

Courses

• Algorithms
• Data Structures with C
• Object Oriented Programming with C++
• Discrete Mathematics
• Computer Architecture
• Operations Research
• Computer Graphics
• Computer Networks
• Database Management Systems
• Software Engineering
• Web Programming
• Java Programming

Projects

GitHub Monte-Carlo Tree search guided Genetic Algorithm
Paper

• In this research, we investigate the possibility of applying a hybrid approach to optimize neural network weights
• Genetic Algorithms are a class of optimization algorithms that perform heuristic search and span out as tree
• Thus, we apply MCTS on genetic tree structure to navigate/guide the heuristic search process of opimizing the neural network weights
• Dataset: Diabetes Classification

GitHub Credit Card Fraud Detection

• Developed a set of Credit Card Fraud detection models and analyzed their relative performance.
• Pre-processed the data with EDA (Exploratory data analysis) and PCA (Principal component analysis)
• Re-balanced the dataset using undersampling (Reservoir sampling) and oversampling (SMOTE) techniques and performed hyperparameter tuning using GridSearchCV
• Applied following machine learning techniques to detect fraud:
  1. Support Vector Machine
  2. Logistic Regression
  3. Decision Tree
  4. Random Forest XGBoost
• Dataset: Credit Card Fraud

GitHub GPT2PDF

• Developed a chrome extension using Javascript to download ChatGPT coversations.
• Included an injected download button on the chatGPT platform to download specific conversations as pdf files
Download Extension

GitHub Text to Image GAN

• Developed and trained a Generative Adversarial Network (GAN) to generate flower images from text inputs
• Preprocessed images as numpy arrays and image description into embeddings and appened them to image data
• Trained the Generator and Discriminator networks on the flowers-102 dataset and word embeddings from glove 300D
• Dataset: Oxford Flower 102 and Glove 300D

GitHub Tweetrimony

• Developed a social media mining application in Python to match users based on their social media actvity
• Generated demographic information using username and tweet history
• Preprocessed data by filtering non user accounts and analyzed tweet sentiments with polarity and subjectivity
• Generated a hash mechanism of multiple secret keys to access data when rate limited
• Datasource: Twitter API, tweets

GitHub ChainReaction AI game

• Developed a two player chain reaction board game in Python with A.I agents as opponents.
• Applied the concepts of adversarial tree search strategies and CNN based approaches in generating the A.I. agent
• Player strategies include:
  1. Minimax: Tree based AI
  2. UCT: Uniform Cost search/Random search
  3. CNN based approach with data augmentation

Work Experience

TruWeather Solutions July 2022 - Present
Data Scientist

• Designed solution architecture for wind data prediction and deployed LSTM model to AWS with an accuracy of 93%
• Pre-processed Openfoam simulation data in the shape of input feature vectors
• Exposed a REST API via AWS Lambda, enabling real-time wind data predictions with an average response time of 5 seconds
• Developed Python scripts to analyze and preprocessed OpenStreetMap 3D data for use in CFD simulations, resulting in better accuracy and simulation time.
• Performed EDA on Lidar and CFD data, improved results with interpolation of grid points and incorporated geological data using geopy
• Enhanced python code for finding the optimal sensor placement locations using entropy formula mentioned in this journal
• Conducted CFD wind flow simulations with OpenFOAM on HPC instances using SLURM commands and analyzed the results to identify key factors impacting wind patterns, resulting in a 25% reduction in error compared to previous simulations

DIEMLife Inc February 2022 - July 2022
Backend Engineer Intern

• Implemented a fresh SQL schema with graph structure in MySQL to store and map existing users to their health data
• Developed and deployed a Spring Boot microservice on an AWS EC2 docker instance, enabling the retrieval of user health details from Google Fit and mapping activities
• Created REST APIs for seamless access of stored activity and health data from the frontend
• Developed functionality for fetching user activities list and persisting the same in database increasing user engagement by 10% in the platform.
• As the sole Backend Engineer at the startup, I served as the single point of contact and managed all aspects of backend development

Envestnet Yodlee July 2016 - May 2021
Senior Software Engineer

• Experience working with cross-functional teams and collaborating across teams for product development
• Actively contributed to designing and developing a microservice architecture using Java, Spring Boot, JPA/JDBC and MongoDB (NoSQL) in an Agile environment
• Designed SaaS application for account reconciliation with multithreaded producer-consumer architecture and distributed system using kafka and kubernetes to improve performance and application scalability (~150K refreshes per day)
• Introduced the concept of synthetic transactions for better account reconciliation process increasing data quality by 24%
• Developed splunk analytics dashboards and maintained 95% user data quality while helping detect missing account information
• Analyzed banking and investment data to build and replace data models, and monitor OLTP data
• Liased with banking clients, gathered requirements and developed OFX and OpenBanking solutions
• Implemented an additional webscraping agent for the aggregation platform
• Developed industry standard code with JUnit test cases and created CI/CD pipelines using perforce and Jenkins.
• Led the team in creating transaction type prediction application in python with K-means clustering as part of hackathon.

Contact

Socials

• Twitter
• LinkedIn
• GitHub
• Instagram

Elements

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    i++;
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