Shayan Amir Shahkarami

Hey, I’m Shayan Amir Shahkarami.


M.Sc. Student in Data & Computer Science at Heidelberg University

AI Researcher & DevOps Engineer


Research Interests

  • Computer Vision
  • Object Detection & Industrial AI
  • Machine Learning for Medical Imaging
  • Large Language Models & Intelligent Agents
  • Cloud-Native AI Infrastructure
  • Privacy-Preserving AI Systems
  • Artificial Intelligence for Cybersecurity


My work focuses on Artificial Intelligence, Machine Learning, Cybersecurity, and scalable cloud-native systems. I am particularly interested in intelligent security automation, medical imaging applications of deep learning, and AI-driven vulnerability discovery.

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My Experiences



Internship Experience


Upon completing my Network+ certification, I embarked on a comprehensive exploration of networking. After all, I got an interview for infrastructure and help desk internship several months later in November 2022. My internship in “Turquoise Partners industry” spanned 3 months. After my enthusiastic approach to learning in work area, they offered me another 4 months internship as “Introduction to Cybersecurity” in February 2022. There I have experienced, configuring Switches and Routers, working with the FortiGate firewall, and working with the BitDefender dashboard.


TA (Teacher Assistance)


Since Spring 2023, I have been a teaching assistant for Dr. Motevali, delivering lectures on Evaluation of Cloud Infrastructure as a Service and IT Strategy Implementation for Industries and Startups.


Blockchain Security and Distributed Systems


I was honored to lead a lecture, supervised by Dr. Shirazipour, introducing undergraduate students to various blockchain algorithms and demonstrating varieties of Solidity code examples.







Past Research:

Enhancement of Black-Box Web Application Security Scanners in Detecting XSS Injection Vulnerabilities

Every day a new company or organization is going to rise and become more advanced in technology. Using the Internet for various purposes, such as e-commerce, e-banking, e-learning, and social networking. By having more customers and clients visiting their web applications, they are opening their gates to malicious users. Web applications today are increasingly vulnerable due to some common factors like outdated services, misconfigured settings, hidden directories, data leaks, etc. To find these web vulnerabilities before a malicious hacker, security experts use fuzzing tools and scanners to find web vulnerabilities and security flaws in web applications. We have gathered some of the best open-source tools in this field to find vulnerabilities and security flaws. With the help of these Black-Box testing security tools, security engineers and web developers can have the chance to discover their vulnerabilities and secure their web-application without putting much time and effort.