Engineering Secure Intelligence: A Professional Portfolio

Prateek Yadav
Dept. of Computer Science (AI/ML & InfoSec)
RPTU Kaiserslautern-Landau
Kaiserslautern, Germany
prateek.yadav@edu.rptu.de [PDF]
Abstract—This document presents the professional profile / technical capabilities of Prateek Yadav. It details expertise in Machine Learning, Digital Forensics, and Penetration Testing. The paper analyzes the author's academic background at RPTU Kaiserslautern-Landau and practical experience in computational biology and security operations. Key contributions include reproducible ML experiments and forensic evidence acquisition. The reader is encouraged to explore specific details via the interactive Project Citations provided throughout the text.
Index Terms—Machine Learning, Digital Forensics, Penetration Testing, Python, Cloud Computing (GCP/AWS), Network Security.

I.Introduction

In the domain of modern computer science, the convergence of Artificial Intelligence and Information Security presents unique challenges and opportunities. This portfolio explores the author's journey through these dual specializations. Prateek Yadav is currently pursuing an M.Sc. in Computer Science at RPTU Kaiserslautern-Landau (2022-2026), focusing on AI/ML and Information Security.

The central thesis of this work is that robust engineering requires a holistic understanding of both system defense and computational intelligence. Through the following sections, we will examine the Projects that substantiate this claim.

II.Education

M.Sc. Computer Science
RPTU Kaiserslautern-Landau, Germany (2022 - Present)
Specialization: AI/ML & Information Security.

M.Sc. Computer Science (Visiting Student)
Universität des Saarlandes, Germany (2024 - 2025)
Focus: Computer Science.

B.Tech. Computer Science & Engineering
UIET MDU Rohtak, India (2017 - 2021)
Grade: A+.

III.Professional Experience

A.Research Intern (ML)

University of Kerala (Mar 2022 - Apr 2022)
Built reproducible ML pipelines for biological datasets, optimizing feature engineering and experiment tracking.

B.Computer Forensic Analyst

Feather's Group Pvt. Ltd. (Jan 2022 - Apr 2022)
Conducted digital evidence acquisition and artifact analysis for investigative reports, utilizing open-source forensic toolchains.

C.Penetration Tester

Virtually Testing Foundation (Oct 2021 - Dec 2021)
Executed vulnerability assessments in controlled environments and authored remediation guides aligned with security frameworks.

IV.Technical Methodology

The author employs a diverse set of tools and methodologies. The primary technical stack includes:

A.Security & Forensics

Proficiency in vulnerability assessment and digital forensics using tools such as Nmap, Wireshark, Burp Suite, Metasploit, Autopsy, and Sleuth Kit. Methodologies include evidence acquisition, integrity verification, and artifact analysis.

B.Machine Learning & Dev

Development of ML experiments using Python, Scikit-learn, TensorFlow, and Pandas. Extensive experience with C/C++ and Bash scripting facilitates low-level optimizations. Cloud infrastructure expertise spans Google Cloud Platform (GCP), AWS, and Oracle Cloud (OCI).

V.Open Source Contributions

The following table summarizes key active development projects. For a comprehensive analysis, please refer to the Detailed Project Appendix.

Table I
Summary of Selected Roles/Projects
Identifier Domain Status
Project Nirav Sys/Linux Open Source
Project oNIgiRI Config/UX Open Source
Gyan Udyan InfoSec/Edu Live

The author maintains active open-source contributions. Project Nirav and Project oNIgiRI demonstrate expertise in Linux display systems, while Gyan Udyan serves as a live knowledge repository for cybersecurity research.

VI.Conclusion

Prateek Yadav's work demonstrates a rigorous application of computer science principles to solve complex problems in biology and security.

References

[1] P. Yadav, "Nirav: Niri Shell Overlay," GitHub, 2024. [Online]. Available: View Paper.

[2] P. Yadav, "oNIgiRI Configuration Suite," GitHub, 2024. [Online]. Available: View Paper.

[3] P. Yadav, "Gyan Udyan: Cybersecurity Notes," Netlify, 2025. [Online]. Available: View Paper.