Hey there! I’m Vittorio Stile, a Chartered Engineer and a massive IT enthusiast. I’ve got a Ph.D. in Big Data and Artificial Intelligence, grade “Excellent” (top tier of 4-level scale), with a research thesis titled AI-generated Deepfakes: Detection and Bias Analysis” at Mercatorum University, an M.Sc. in Business Engineering "Cum Laude," and a B.Sc. in Industrial Engineering under my belt. I spend my days juggling roles as an Innovation Manager, Product Manager, and UX Designer, with a keen focus on making mobile devices and human-machine interfaces as user-friendly as possible. Besides all that techy stuff, I teach courses on Industry 4.0, diving deep into Human-Machine Interaction and Blockchain.

I work at the intersection of applied AI, education, human centered systems and management, with a strong focus on reproducible research and clear documentation.

What really revs my engine? Innovating and optimizing every sector I touch. I’m all about building lasting, win-win partnerships with the companies I work with—not just racking up a long list of clients. Let’s make something great together!

I am an amateur writer. I enjoy learning and writing about tech and innovation (but not limited to) and sharing my experiences as Engineer. Check out my latest articles!

Book a paid consultancy session with me. With over 20 years of experience in the industry, I offer a diverse range of engineering services within digital innovation. My expertise includes providing advice for startup launches, securing funding and grants for entrepreneurship, conducting Product Design audits for digital products, and specializing in User Experience Design for websites and mobile applications. Additionally, I offer services in business process reorganization, corporate security, patent development, and the design of molds for plastic materials.

My qualifications include:

• PhD in Big Data and Artificial Intelligence
• Registered Engineer (Industrial Sector, ID No. 23605)
• IEEE Senior Member (ID No. 97919001)
• Innovation Manager (Unioncamere list, ID No. 755)
• Master of Science in Management Engineering with Honors (LM-31)
• Bachelor of Science in Industrial Engineering (L-9)
• Certified iOS Developer at Apple Developer Academy
• Forensic IT Expert

I am a certified iOS developer from the Apple Developer Academy of Napoli. I enjoy reading and learning about the latest technologies and frameworks to better collaborate, as Product Manager & UX Designer, with development teams. I can support front-end development in Xcode, create FileMaker projects from scratch, and I know the basics of C programming.

I also use Python for DeepFake detection projects in Computer Vision, mainly working on Jupyter Notebooks in Visual Studio Code. For me, the language is not the key point — the goal is. I do not consider myself a programmer, but I always keep up with the latest trends, frameworks, and tools, and if I need to implement even complex tasks (API configuration, JSON handling, ML models, or R code for data science), I can manage them without problems.

So... I can code but don't offer me jobs as a coder. I don't want to work as a coder, I do it for passion and for academic/research purposes.

• Deepfake detection research: attribute aware pipelines, bias and error analysis, and replication ready notebooks (see deepfake-attribute-detection).
• Literature review tooling: an end to end protocol and datasets for a deepfake detection PhD review, including query sets and de duplication workflow (see 00-deepfake-detection-review).
• Teaching and demos: compact CNN baselines and classic datasets such as MNIST and AT&T/Olivetti, designed to be easy to run and explain (01-binary-classification, 02-digit-classification-mnist, 03-face-classification-olivetti and 04-deepfake-detection).
• Applied data workflows: notebooks and scripts for education and ML analysis (2025edu4ai).

Python, Jupyter, TensorFlow/Keras, OpenCV, scikit learn, Swift, C, and LaTeX for research writing.

I’m happy to connect with researchers and educators working on trustworthy AI, computer vision, and reproducible ML experiments.

• Portfolio: https://linktr.ee/vstile
• Medium: https://medium.com/@vstile
• LinkedIn: https://www.linkedin.com/in/vittoriostile/
• Bēhance: https://www.behance.net/vittoriostile
• X (former Twitter): https://x.com/vittoriostile
• Tealfeed: https://tealfeed.com/vstile/connect

• This repository contains code and model. No personal data are included.
• Reuse is permitted provided that you cite the author and this work.
• Recommended license: Creative Commons Attribution 4.0 International (CC BY 4.0). You are free to share and adapt the material for any purpose, even commercially, as long as appropriate credit is given, a link to the license is provided, and any changes are indicated.

Short attribution text you can include in derivative works:

paper attribution

This material reuses data and methods from this paper:
Stile, V., Caldelli, R., Guerrero-Contreras, G., Balderas-Díaz, S., and Medina-Bulo, I. (2025). Analysis of DeepFake Detection through Semi-Supervised Facial Attribute Labeling. Proceedings of the 11th Spanish-German Symposium on Applied Computer Science (SGSOACS 2025), 2831, XX, 138, Wien, Austria. https://link.springer.com/book/9783032148155
© 2025 Vittorio Stile - Licensed under CC BY 4.0.

or Ph.D. thesis attribution

This material reuses data and methods from this Ph.D. Dissertation:
Stile, V. (2026). “AI-generated Deepfakes: Detection and Bias Analysis”. Ph.D. dissertation, Universitas Mercatorum, Roma, Italy.
© 2026 Vittorio Stile - Licensed under CC BY 4.0.

or GitHub repository attribution

This material reuses data and methods from this work:
Stile, V. (2025). Deepfake Attribute Detection – A Project on Attribute-Aware Detection and Bias Analysis. GitHub repository. https://github.com/vstile/deepfake-attribute-detection
© 2025 Vittorio Stile - Licensed under CC BY 4.0.