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Hi! My name is Aashish Bansal and I'm a Software Engineer. Welcome to my Personal Website!
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Aashish Bansal

Software Engineer I-B

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My profile reflects my journey and expertise in the intersection of Technology and Finance. With a background in Information Technology from a top-tier institution, I've cultivated skills in Software Development, Data Analysis, and Financial Modeling. Throughout my career, I've held pivotal roles in renowned organizations, consistently delivering innovative solutions and contributing to business growth. My passion for Technology is evident in my involvement in diverse projects spanning Software Development, Machine Learning, and Data Analysis. I thrive in dynamic environments, leveraging my analytical mindset to tackle complex challenges. Continuously learning and adapting to emerging trends, I'm committed to excellence and making meaningful contributions in the tech and finance sectors. My profile embodies my dedication to professional growth and my drive to make a lasting impact.


Work Experiences

Software Engineer I-B

Bank of America | 2023 - Present

I have worked with the following fields:

  • Change Management (SME Reviewer)
  • NPT Migration
  • Upgrade for Mobile Application using Spring Boot and Angular
  • Unit Testing
  • Vulnerability Remediation
  • Instrumentation as a Service

I have worked with the following technologies:

  • Oracle PL/SQL.
  • Informatica IICS.
  • Angular 11
  • Java Spring Boot
  • Junit, Mockito and Powermock
  • Jenkins

Academic Intern Tech

Bank of America | 2023

I have worked with the following fields:

  • Change Management (SME Reviewer)
  • Feature Development using Swift (iOS Platform)
  • NPT Migration
  • Upgrade for Mobile Application using Spring Boot and Angular

I have worked with the following technologies:

  • iOS Development with Swift
  • Angular 11
  • Java Spring Boot
  • Junit, Mockito and Powermock

Jr. Developer (Team Lead)

River Bend Data Solutions | 2022

I have developed the Development Architecture and Database Architecture for the software helping detect and suggest requirement of an early-stage Medical Diagnosis and Treatment Process. The software also helps in maintaining all patient's medical history which would help the doctor's for future reference. I have worked with the following technologies:

  • Python Deep Learning

Projects

SMS Spam Detection Using Machine Learning Techniques

Open Source (2022)
  • Comparative study on the existing algorithms for learning to predict if a received message is spam or not
  • Attempt to create a new hybrid model using the rarely used algorithms to create an improved decision- making system for prediction
  • User interface built to use to check if a message (given as input) is spam

 

User Validation in Online Class

Confidential (2022)
  • Study on different methods of user authentication while attending an online class
  • Attempt to create a secured system to prevent students from carried out any malicious activity during class to give attendance
  • Secured Facial recognition system to mark attendance to prevent passing credentials for any malicious activity

Patent In-Progress

Fake News Detection Using Machine Learning Techniques

Open Source (2022)
  • Comparative study on recent algorithms to predict if the given input news is fake or real
  • Algorithms analysed to improve the efficiency of learning
  • Improved Neural Network for reduced loss and improved accuracy
  • High training time due to the increased number of required resources for training the model

 

Breast Cancer Detection Using Machine Learning Techniques

Open Source (2022)
  • Comparative study on the recent algorithms to predict if a person is suffering from Breast Cancer
  • Algorithms analysed to improve the efficiency of learning
  • Comparison of training before and after hyperparameters tuning

 

Testing of E- Commerce Website

Open Source (2022)
  • Consists of a separate Administrator Panel for the Admins of the company to view and update product information
  • The products are categorized based on the needs to the users and types of users with a Classical Interface
  • Implemented using HTML, CSS, JavaScript, PHP, MySQL which can run on XAMPP Server
  • Testing of the user interface and functionality of the E-commerce website
  • Testing conducted with the help of Black Box and White Box Testing methods
  • Probable Errors and bugs fixed after thorough analysis

Analysis of COVID-19 Data

Open Source (2022)
  • Data provided was the 2019 COVID-19 data including the list of Indian and International cases divided into the category of total cases, infected cases, recovered cases, and deceased cases
  • Story creation with the data for all the states to analyse the increase on a daily basis for the states
  • Implemented using Tableau

 

Fake News Prediction

Open Source (2021)
  • Prediction if the given news is fake or not based on the key words in the text and vectors created after removing all the stop words and statistical analysis

Network Intrusion Detection System

Document Confidential (2021)
  • Worked on Machine Learning Algorithms which can be used to be predict whether the Request coming is an attack
  • Comparative Study of several available Algorithms
  • Novel Approach for the Deep Learning model to improve learning efficiency

Publication In-Progress

Skin Cancer Detection using Transfer Learning and Ensemble Modelling

Research Publication (2021)
  • Improved Machine Learning Model to predict if the person is suffering from Skin Cancer
  • Improved Accuracy Results of the Algorithms based on the Current Project
  • Approved for publishing in SoCPaR 2022, LNNS 417 proceedings

   

Apple Store Management System

Open Source (2020)
  • The major component is the Database normalized to reduce redundancy in data to the minimum level possible
  • The interface is simple for both administrators to update product information and for the users to view product information
  • Implemented using HTML, CSS, JavaScript, PHP, MySQL which can run on XAMPP Server

 

Summer Internship Project: Twitter Sentiment Analysis (2020)

Open Source (2020)
  • Deep Learning Model predicts whether the tweet given by the used is Positive, Negative or Neutral based on the training using Bi-LSTM