About Me
Hi, I'm Vinicius Bobato! I'm a Ph.D student in Computer Engineering at Texas A&M University, and I've always been passionate about exploring how technology can make a real difference in the world. My interests range from diving into cybersecurity and network analysis to building embedded systems and, more recently, learning about AI and machine learning. I've had the chance to work on some exciting projects, from automating tasks with embedded systems to tackling challenges in network security. When I'm not researching or building something new, I enjoy teaching, mentoring, and staying curious about the latest advancements in tech. I'm always looking for ways to grow and take on meaningful challenges!
Publications
- Analyzing a Multi-Stage Cyber Threat and Its Impact on the Power System - IET Cyber-Physical Systems: Theory & Applications [Link]
- Cyber Security of a Smart Power Distribution System - Cyber Subsystem Use Case - 2025 Grid Edge Technologies Conference & Exposition [Link]
- Cyber Security Use Case on a Smart Power Distribution System - Physical Subsystem - 2025 Grid Edge Technologies Conference & Exposition [Link]
Qualifications
- Currently pursuing my Ph.D in Computer Engineering at Texas A&M University
- M.S. Engineering Technology Graduate for Texas A&M University [Thesis]
- B.S. Electronics Engineering Graduate for Texas A&M University
- Relevant Graduate Coursework:
- Artificial Intelligence, Data Analysis and Tools for Industry, Intelligent Systems Design, Industrial IoT.
- Relevant Undergraduate Coursework:
- Embedded Systems Software Developement, Advanced Network and Systems Security, Embedded Systems Development in C.
Certifications
- Machine Learning with Python - IBM
- Introduction to Deep Learning & Neural Networks with Keras - IBM
- Deep Learning with PyTorch - IBM
- Deep Learning with Keras and Tensorflow - IBM
- GenAI Foundational Models for NLP & Language Understanding - IBM -- (In Progress)
Experience
Department of Electrical and Computer Engineering at Texas A&M University - PRISE Project
Graduate Research, Dec. 2023 - Present
- Modeled the network side of a Smart Distribution System and AMI RF mesh network using Linux containers.
- Created Python scripts to allow communication between containers using TCP and UDP sockets.
- Performed different cyber-attacks to analyze their impact on a Smart Distribution Grid using ARP spoofing and packet generation open-source tools.
- Worked on the analysis of cyber-physical data in malicious settings using Python data-analysis tools.
Department of Engineering Technology and Industrial Distribution at Texas A&M University
Graduate Teacher Assistant for Local-and-Metropolitan-Area Networks, Jan 2024 - Present
- Led hands-on lab sessions to guide students in gaining proficiency with terminal commands on various operating systems, facilitating practical experience in networking configuration and troubleshooting.
- Designed and implemented varied networks using Cisco equipment for laboratory sessions.
- Assisted students to understand and implement different communication protocols and standards on routers and switches (OSPF, BGP, RIP, DHCP, VLANs, Trunking, STP).
Texas A&M Engineering Experiment Station (TEES) - CyPRES Project
Undergraduate/Graduate Research Assistant, May 2022 - Dec. 2023
- Used Linux in virtualized environments and scripting languages to implement connectivity between DNP3 and ICCP protocols.
- Developed various programs in C/C++ and Python to integrate different technologies for research.
- Performed data-analysis techniques using Numpy and Pandas to find anomalies in malicious data from cyber-attacks.
- Applied and studied offensive and defensive techniques to safeguard digital assets, such as SQL injections and DMZ networks.
Projects
Current Projects
ASIC (AI for Satellite Image Classification)
Fine-tuned a semantic segmentation model using satellite images from DeepGlobe 2018 dataset to classify land types such as city areas, forests, agricultural fields, and water bodies. This classification can be used to automate land measurement calculations for urban planning, agriculture planning, and environmental monitoring. Built a WebApp to deploy the model and allow users to input and image and get the segmentation and area classification of the entire image. The dataset contains images with scale 1pixel = 50 cm, automated the area calculation in squared meters. The model achieved over 70% pixel accuracy. A blog post was also built to explain the project and the results. Access the blog here.
CAPTCHA Image Classification
Developing a deep learning model using VGG16 architecture and TensorFlow to classify CAPTCHA images with 93% accuracy. Implementing data augmentation techniques and evaluating performance using precision, recall, and F1 scores.
Past Projects
Engineering Capstone
Led the development of a laboratory bench simulating a SCADA system for energy utility companies. Created a custom RTU with Raspberry Pi, integrating analog/digital sensors and actuators with a GUI interface using DNP3 protocol.
*This project cannot be open-sourced due to university and research policies.
Machine Learning Based Firewall
Implemented a Python-based Intrusion Detection System using the IoT-23 dataset. Trained a Random Forest Classifier to analyze network traffic and identify malicious packets. Implemented a Flask API to serve the model.
ShellBridge
Developed a secure reverse shell application with SSL/TLS encryption for remote server interaction and file transfers between virtual machines.
Personal Password Manager
Created a secure password manager with password generation capabilities and MySQL database integration for safe credential storage.
Skills
Programming
Technologies
AI/ML
Networking
Security
Tools
Contact Me
Feel free to reach out via email at vmbobato@tamu.edu or at vini.bobato@hotmail.com.