About Me
Know Me More
Hello! I'm Vincenzo Vigilante
A curious human being, computer nerd since childhood, experienced Software Engineer.
Always passionate about learning, graduated with high honors at every step, earned a Ph.D. in March 2021 about computer vision algorithm for embedded systems.
Started out part-time during university, first in the field of web development, then working on artificial intelligence applications and embedded systems, finally becoming a team leader.
Right now working with Amazon Web Services to develop and mantain their Cloud platform.
Hobbies include a number of personal projects, participation to hackatons and programming competitions as well as electronics, photography, graphics, 3d printing, videogames and music.
- Name:Vincenzo Vigilante
- Email:info@vvigilante.com
- Age: 29
- From:Salerno, Italy
Skills
What I Do
Software Engineering
Dealing with complexity, design and architecture, best practices, cloud computing, project management.
Embedded Systems
Writing efficient yet mantainable clean code, interfacing with the real world, electronics.
Computer Vision
Processing images, vectorial programming, 3d coordinate systems, algorithms.
Artificial Intelligence
Deep learning, machine learning, inference, statistics, parallel programming, frameworks.
Web & Distributed programming
Web, asyncronous programming, threading, HTML, CSS, Javascript, frameworks, CMSs.
GNU/Linux
Scripting, hardware, networking, administration, compiling, debugging.
Summary
Resume
Education
2017 - 2021
Ph.D. Artificial Intelligence
University of Salerno, Italy
Thesis title: Intelligent embedded systems for facial soft biometrics in social robotics.
My experience included a period of 4 months spent as a visiting researcher at the University of Twente (Netherlands) where I worked with my co-tutor.
Help teaching: algorithms and data structures, logical networks, computer vision, cognitive robotics, machine learning
Achievements:
- 4 papers published to international journals, 6 presented to international conferences
- 21 papers reviewed, 6 cotutorship for master theses, 14 for bachelor theses
- Developed a software framework for training and evaluation of deep networks that is now used by the group.
- Setup and maintenance of a cluster of linux machines with GPUs, shared storage and delegated authentication, used by 30 people.
2015 - 2017
Master's Degree (cum laude)
Computer Engineering ‐ University of Salerno, Italy
Thesis title: A wearable device for accident detection in sports activities using machine learning. Published and presented as a conference paper.
The course included lots of project work, done in groups. My group and I always took pride in our projects and aimed to excellence beyond what was required; some results are showcased in the projects section of this website.
I've often been selected as team leader by my peers due to my dedication and experience.
Achievements:
- Thesis published as a conference paper
- Our laser harp project was requested and showcased at multiple venues, even on national TV.
- Grade Point Average: 29.83 / 30
2012 - 2015
Bachelor Degree (cum laude)
Computer Engineering ‐ University of Salerno, Italy
Thesis title: Porting and experimental evaluation of video analytics applications on low-cost platforms.
Achievements:
- Of the 180 students of my cohort I was one of the 8 that obtained their degree within 3 years.
- Grade Point Average: 28.95 / 30
2007 - 2012
High school degree (cum laude)
Scientific High School Leonardo Da Vinci, Salerno
Experience
2021
Software Development Engineer II
Amazon Web Services
Developing and mantaining the AWS RDS Platform.
2020
Team Lead
A.I. Tech srl
Mentoring and managing a team of 4 developers.
Design of algorithms, protocols and processes.
Participation to fairs and expositions; interaction with customers and business partners.
Achievements:
- Release of 4 new products, 2 new platforms, many major and minor bugfixes and features
- Up to 10x reduced hardware requirements by designing of a resource sharing protocol
- Improved reliability and reduced test time by designing an automatic regression testing suite
2015 - 2019
Developer
A.I. Tech srl
Design and development of state of the art computer vision algorithms, optimized to run directly on board of embedded smart cameras (not limited to Deep Learning).
Desing and development of latency critical software modules in C++ for High Frequency Trading.
Achievements:
- 5-10x speed-up of multiple computer-vision algorithm by profiling and optimization
- Proposed and implemented self-monitoring modules for automatic bug-spotting at runtime
- Proposed and implemented improvements of the development process and of the software architecture that allowed to scale the number of products and the number of supported platforms by 5-10x
2012 - 2015
Web Developer
Studio 109
Development of web-based ERP software and applications.
Development of templates and plugins for well-knwon CMSs.
Portfolio
Projects
Publications
Publications
A convolutional neural network for gender recognition optimizing the accuracy/speed tradeoff
IEEE Access 8, 130771-130781, 2020
2020
39 citationscit.
Benchmarking deep network architectures for ethnicity recognition using a new large face dataset
Machine Vision and Applications 31, 1-13, 2020
2020
33 citationscit.
A deep learning based approach for detecting panels in photovoltaic plants
Proceedings of the 3rd International Conference on Applications of …, 2020
2020
31 citationscit.
Effective training of convolutional neural networks for age estimation based on knowledge distillation
Neural Computing and Applications, 1-16, 2021
2021
28 citationscit.
VF3-Light: a lightweight subgraph isomorphism algorithm and its experimental evaluation
Pattern Recognition Letters 125, 591-596, 2019
2019
18 citationscit.
A system for gender recognition on mobile robots
Proceedings of the 2nd international conference on applications of …, 2019
2019
18 citationscit.
A parallel algorithm for subgraph isomorphism
Graph-Based Representations in Pattern Recognition: 12th IAPR-TC-15 …, 2019
2019
18 citationscit.
Gender recognition in the wild: a robustness evaluation over corrupted images
Journal of Ambient Intelligence and Humanized Computing 12, 10461-10472, 2021
2021
16 citationscit.
Emotion analysis from faces for social robotics
2019 IEEE international conference on systems, man and cybernetics (SMC …, 2019
2019
15 citationscit.
Benchmarking deep networks for facial emotion recognition in the wild
Multimedia tools and applications 82 (8), 11189-11220, 2023
2023
11 citationscit.
MIVIABot: a cognitive robot for smart museum
Computer Analysis of Images and Patterns: 18th International Conference …, 2019
2019
11 citationscit.
SoReNet: A novel deep network for audio surveillance applications
2019 IEEE international conference on systems, man and cybernetics (SMC …, 2019
2019
9 citationscit.
Detecting sounds of interest in roads with deep networks
Image Analysis and Processing–ICIAP 2019: 20th International Conference …, 2019
2019
8 citationscit.
Performance assessment of face analysis algorithms with occluded faces
International Conference on Pattern Recognition, 472-486, 2021
2021
7 citationscit.
Vehicles Detection for Smart Roads Applications on Board of Smart Cameras: A Comparative Analysis
IEEE Transactions on Intelligent Transportation Systems 23 (7), 8077-8089, 2021
2021
2 citationscit.
A Wearable Embedded System for Detecting Accidents while Running.
VISIGRAPP (4: VISAPP), 541-548, 2018
2018
2 citationscit.
Intelligent embedded systems for facial soft biometrics in social robotics
Universita degli studi di Salerno, 2021
2021
Updated: 2023-12-08.
View all on Google Scholar
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