ABOUT I am a Computer Engineering master's student at Paderborn University and a research assistant working on physiological time-series learning. My background spans software engineering in networking and cloud-native systems, along with applied machine learning and signal processing research.
In progress: Building seizure-prediction pipelines using wearable ANS signals, improving reproducibility in physiological ML workflows, and preparing for research and software engineering roles.
Education
Master of Science in Computer Engineering
Oct 2024 - Present
Universitat Paderborn, Germany
Coursework: Statistical Signal Processing, Machine Learning 1, Machine Learning in Biometrics, Advanced Computer Architecture.
Bachelor of Engineering in Electronics and Communication
Aug 2017 - Jul 2021
Netaji Subhas Institute of Technology, University of Delhi, India
Coursework: Signals and Systems, Probability Theory and Communication, Digital Signal Processing.
Skills
Programming: Python, Scala, C/C++, TypeScript, Bash, SQL, TensorFlow
Cloud / DevOps / Platforms: AWS (EKS, EC2, IAM, VPC, ECR), Kubernetes, Docker, CI/CD Pipelines, Infrastructure as Code, AWS CDK
Software / Systems: Akka Framework, Kafka, Actor Model, OOP, SDLC, Networking Fundamentals, Operating Systems, DBMS, LLD, Version Control
Tools: Linux, Git, VS Code, IntelliJ IDEA, Bitbucket, TeamCity, MySQL, LaTeX
Soft Skills: Leadership, Time Management, Teamwork, Problem Solving, Critical Thinking
Languages: English (C1), Deutsch (A1)
Work
Research Assistant
Jan 2026 - Present
University of Paderborn, Germany. Developing data-driven and classical signal processing pipelines for physiological time-series tasks, including filtering, feature extraction, detection, and estimation.
Software Dev Intern (Embedded)
Sept 2025 - Dec 2025
Amazon Web Services (AWS), Berlin, Germany. Built cloud and embedded validation workflows for GPU-based canary testing in Kubernetes environments.
Software Engineer
Oct 2021 - Sept 2024
Ciena India Pvt. Ltd., Gurgaon, India. Built and maintained telecom network-management applications in distributed microservice architectures, while owning feature delivery, debugging, and customer-facing issue resolution.
Research Intern
June 2019 - July 2019
Ministry of Defence, Delhi, India. Worked on embedded sensing and compensation logic for aerospace-oriented MEMS sensor behavior.
Projects
Heart-Rate Stress Classifier - Built a Python and scikit-learn pipeline to classify 60-second heart-rate windows into stressed and relaxed states.
Applied LDA to RBF-SVM modeling workflow for physiological classification.
Drowsiness Detection using Deep Learning and Computer Vision - Developed a CNN-based drowsiness detection model for live in-car video prediction.
Trained and evaluated a deep learning model for real-time drowsiness inference.
ABOUT I am a Computer Engineering master's student at Paderborn University and a research assistant working on physiological time-series learning. My background spans software engineering in networking and cloud-native systems, along with applied machine learning and signal processing research.
In progress: Building seizure-prediction pipelines using wearable ANS signals, improving reproducibility in physiological ML workflows, and preparing for research and software engineering roles.