Mohamed Martini

Mohamed Martini has a diverse work experience, beginning in 2022 as a Machine Learning Engineer at Pison. In 2021, they were a Machine Learning Research Assistant at the University of Massachusetts Lowell, where they worked on the STRONG project, examining the effect of cooperation networks among agents on search performance, and developing multi-agent RL learning algorithms for map coverage. Mohamed also worked on an Advanced Graduate Project, Drone-based wireless sensor network for multimodal underground situational awareness, where they researched the computer vision literature, proposed the YOLO ligh-weight variants, processed LiDAR and images data, and documented research efforts and findings. In 2020, they were an Engineering Consultant at U(n)Altered Laboratories, where they implemented a company-proprietary stream cipher algorithm in Python and C++, optimized the algorithm's speed, and designed and performed differential cryptanalysis tests to assess the security of the stream cipher. Mohamed also worked as an Application Engineering Intern at Rockwell Automation, where they gained experience in Python and Matlab, and took full responsibility of automated hardware testing project after their supervisor left the company.

Mohamed Martini completed a Bachelor's degree in Biology, General at the University of Massachusetts Lowell from 2013 to 2017. Mohamed then went on to obtain a Bachelor of Engineering - BE in Electrical and Electronics Engineering from the same institution from 2018 to 2020. Currently, they are pursuing a Master of Science - MS in Computer Engineering at the University of Massachusetts Lowell, which they are expected to complete in 2022. In addition to their degrees, Martini has obtained several certifications from Coursera, including "Building Batch Data Pipelines on Google Cloud" (2022), "Building Resilient Streaming Analytics Systems on Google Cloud" (2022), "Google Cloud Big Data and Machine Learning Fundamentals" (2022), "Modernizing Data Lakes and Data Warehouses with Google Cloud" (2022), "Advanced Learning Algorithms" (2022), "Data Engineering, Big Data, and Machine Learning on GCP Specialization" (2022), "Smart Analytics, Machine Learning, and AI on GCP" (2022), "Supervised Machine Learning: Regression and Classification" (2022), "Bachelor of Electrical Engineer" (2021), "Data Analysis with Python" (2020), and "Introduction to Data Science in Python" (2020).