Aashish Bansal

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
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
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)
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
- 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
- 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
Breast Cancer Detection Using Machine Learning Techniques
Testing of E- Commerce Website
- 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
- 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
Network Intrusion Detection System
- 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
Apple Store Management System
- 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