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Software Engineer @Abnormal-Security | OSS Maintainer @cncf @litmuschaos | LFX Mentor @litmuschaos | Microservices, Kubernetes, Golang, Python.
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abnormal-security
Data Scientist
June 20, 2026 – Present
Sukoon
May 3, 2024 – June 13, 2025
We want to build open-source solutions and standards for using AI to solve mental health challenges. The goal is to apply DPI knowledge and practices that can help professionals deeply explore and understand the latest advancements in AI and how they can be applied to use-cases in mental health specific to India.
View Projectkube-course
April 17, 2021 – October 22, 2023
Main resources for Udemy course "Configuring Kubernetes for Reliability with LitmusChaos"
View ProjectImage-Forgery-Detection
September 5, 2020 – April 15, 2021
A deep convolutional neural network for the detection as well as localization of the area of manipulation in forged images, bearing forgeries of simple as well as complex nature. Further along, the trained model is interfaced with a web application for users to interact with the model in a simple and effective manner, and finally, we also develop a chatbot for further easing the process of interaction with the model and effectively tackling the problem of fake news forwards in popular internet messaging platforms such as WhatsApp.
View ProjectFace-Recognition-Facenet-
August 2, 2020 – March 24, 2023
An implementation of the Siamese Neural Network for facial recognition using one shot detection, that eliminates the requirement for the Neural Network to be trained each time a new image is added to the database. Trained using a Triplet Loss Function, it may even be used to perform the facial recognition with one training instance image.
View ProjectDriver-Drowsiness-Detection
July 12, 2020 – July 6, 2023
A real-time drowsiness detection system for drivers, which alerts the driver if they fall asleep due to fatigue while still driving. The computer vision algorithm used for the implementation uses a trifold approach to detect drowsiness, including the measurement of forward head tilt angle, measurement of eye aspect ratio (to detect closure of eyes) and measurement of mouth aspect ratio (to detect yawning).
View ProjectParkinsons-Detection
June 15, 2020 – February 16, 2023
An AI-based mobile application that is able to diagnose Parkinson's Disease using two independent tests that require only a pencil and a paper. Based on the 2017 research paper Distinguishing Different Stages of Parkinson's Disease Using Composite Index of Speed and Pen-Pressure of Sketching a Spiral by Zham et. al. The trained models were deployed using a Flask backend server, along with a Flutter based frontend mobile application frontend to interact with the REST API.
View ProjectCrop-AI
June 14, 2020 – December 8, 2022
A diagnostic AI-enabled mobile app which is able to classify upto 38 different plant diseases ranging for 14 crops and vegetables. The application makes use of the VGG-Net CNN architecture for the purpose of multi-class classification of the images of infected plant leaves. The trained model was then deployed using a Flask backend server, along with a Flutter-based frontend mobile application to interact with the REST API.
View Projectchaos-runner
November 5, 2019 – Present
The bridge between chaos operator and chaos experiment! Lifecycle manager for chaos experiments
View ProjectCultural Fit Analysis
The candidate's project portfolio shows a strong inclination towards AI/ML and data science applications, which aligns well with a Data Scientist role. However, the projects are predominantly personal and lack diversity in team-based or industry-specific contexts, which might indicate a need for development in collaborative environments. The presence of Kubernetes-related projects (chaos-operator, chaos-runner, kube-course, m-agent) suggests an interest in MLOps or system reliability, which could be a valuable cross-functional skill.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions indicate an ability to work on complex problems independently.