Firas Ladhari

I help clients overcome challenges by leveraging IoT technologies and DevOps practices to deliver efficient, scalable solutions. I also design and build affordable applications and websites tailored to the needs of businesses and individuals.

I have strong experience in IoT systems, DevOps, and software development. As a research intern at Université Laval in 2023, I developed IoT projects using Go and JavaScript, deployed systems with Kubernetes, K3s, and KubeEdge, and implemented fault-tolerance strategies to improve system availability. At SECA in Tunisia, I worked as an R&D assistant, where I optimized a parking management system with AI, and as a software development intern at Coworky, where I trained a machine learning model for cryptocurrency price prediction, built an e-commerce site with ReactJS, and developed an Odoo module for hotel management.

During my IoT development internship at ASQII, I redesigned a chemotherapy preparation robot, built a backup power solution for ESP32, created real-time dashboards with Firebase and JavaScript, and developed a REST API for data export. I also gained experience in computer vision at The Sparks Foundation, where I implemented a traffic sign classifier and a color detector, and at SECA as an industrial IoT intern, where I implemented RS232 communication, optimized data extraction algorithms, and modeled public service queue systems. Earlier, as a backend development intern at Diginov, I built a Node.js app for Facebook ad automation and tested REST APIs.

In addition to these technical roles, I worked as an administrative assistant at Université Laval, where I created the rivericelab.ca website, served as a Mitacs Globalink mentor, and worked as a tutor in math and computer science. I also served as a teaching assistant at Université Laval, leading labs and grading in courses on cloud-native applications and DevOps. These experiences highlight my expertise in IoT, AI/ML, cloud-edge deployments, full-stack development, and academic mentoring

I am currently pursuing a PhD in Computer Science at Université Laval, where my research focuses on the impact of artificial intelligence on the availability of IoT systems deployed with microservices. I previously completed a Master’s degree in Telecommunications Engineering where I evaluated the availability of IoT systems deployed with Kubernetes and KubeEdge. I earned a Bachelor-equivalent degree in Embedded Telecommunications Engineering which gave me a solid foundation in embedded systems, telecommunications, and IoT technologies.

Alongside my academic studies, I obtained several certifications that strengthened my expertise, including Supervised Machine Learning from Stanford University and DeepLearning.AI, Introduction to IoT and Embedded Systems from the University of California, and Introduction and Programming with IoT Boards from POSTECH.

My academic journey has been recognized with notable achievements, such as receiving the Mitacs Globalink Research Award in 2023 and winning first place in La Nuit de l’Info competition in 2021. These experiences reflect both my research potential and my commitment to applying advanced technologies to real-world challenges.