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About Me
Hi there, I am a software engineer at NCR Corporation,
working as a part of the R&D security team under the banking division.
My current interests lie broadly in machine learning, full-stack/backend development, and algorithms.
I completed my B.Tech in Information Technology at
the National Institute of Technology Karnataka, India.
Here, I was a part of the HALE Lab as a Research Intern and
also completed my bachelor thesis under Dr. Sowmya Kamath.
Up for a chat?
Mail me here:
jaidev.chittoria02@gmail.com
Experience
Software Engineer | NCR Corporation, India
July '22-Present
Designed and developed APIs to strengthen the security of ATMs by providing dynamic data analysis of various operations performed using the ATMs manager application (NSP). Developing micro-services and working on improving the functionality of the ATMs manager application. Built an application collaboratively from scratch to provide automated testing to the ATMs manager application.
Research Intern | Healthcare Anlaytics & Language Engineering Lab
May '21-July '21
Developed machine learning models using novel machine learning approaches for the detection of cardiac arrhythmia using electrocardiogram records. The proposed approach beat many SOTA models on the basis of feature space and performance metrics.
Publications
Detection of Cardiac Arrhythmia Using Machine Learning Approaches
2022 IEEE Region 10 Symposium (TENSYMP)
Paper Link
Authors: Jaidev Chittoria, Dr. Sowmya Kamath, Veena Mayya
Skills
Python-3
Algorithms
Machine Learning
C++
SpringBoot
Operating Systems
Linux
Computer Networking
MYSQL-DBMS
Projects
Anomaly Detection in Road Traffic using Visual Surveillance
Machine Learning, Deep Learning, Masking, Detectron, Python3, Video Processing
Developed an algorithm collaboratively to detect anomalous events related to vehicles in road traffic. Utilized the 'AI city challenge' dataset for training and testing purposes. The approach includes machine learning techniques with scene masking to reduce the incorrectly identified anomalies.
Parkinson.ai
Python3, ReactJS, Flask, Sklearn, Machine Learning
A web application that can predict whether the user has parkinson's disease or not using user's audio. Built using machine learning modules, reactjs and flask.
Secure File Transfer System
Python3, Cloud, AES Algorithm, HTML, CSS
A cloud desktop web application using which you can transfer text files securely, include functionalities like adding, removing files on the public server, generating public-private keys. Diffie-hellman and AES algorithm were used for encryption and key exchange purpose.
Home Essentials- An E-commerce Website
HTML, CSS, Nodejs, Mongodb, Express
Built a working website with various functionality like authentication for login, mail validation after registration, search products, adding and removing products etc.
Implementation of Art Gallery Problem
Python, Algorithms, Data Structures, Computation Geometry
Developed an algorithm that can minimize the number of guards who can keep a check on the whole art gallery.
Image Steganalysis
Python, Opencv, Pandas, Numpy, sklearn, keras, CNN, EDA
Using deep learning concepts, built a convolutional neural network model that can detect hidden data in an image. The accuracy achieved was 90.6%.
vEB tree versus AVL Tree via Kruskal’s Algorithm
C++, Kruskal Algorithm, Van Embde Boas Trees, AVL Trees
Comparison of performance of Kruskal’s Minimum Spanning Tree algorithm with its implementation through van Emde Boas Tree and AVL tree with Union Find.
Capacitated Vehicle Routing Problem using Time windows
Python, Pandas, Numpy, Kmeans clustering algorithm
Built a program that can minimise the cost of servicing orders using vehicles with time constraint and without exceeding the vehicle’s capacity using k-means clustering algorithm.
