Armin Masoumian

I have over five years of experience working in data science on developing and implementing predictive models, performing data analysis, and visualizing data for real-world applications. My expertise lies in delivering high-quality data-driven solutions to complex business problems, which is exemplified by my track record of success. My skills include statistical analysis, machine learning, and data visualization using programming languages like Python and R. In my doctoral studies, I focused on developing a self-supervised deep learning model for monocular depth estimation, which can predict the speed and distance of objects using a monocular camera, ultimately helping prevent vehicle collisions. I have also contributed to several projects involving machine learning applications in medical, process, and technological industries. I am eager to share more details about my work on projects such as breast cancer detection and wastewater treatment with potential employers.

1. Working as a Ph.D. Candidate at the University of Rovira i Virgili in the faculty of Mathematics and Computer Vision. (October 2019, Present)
 Developed a Self-supervised Monocular Depth Estimation Model based on Graph Convolutional Network.
 Developed a Supervised Machine Learning Model for Breast Cancer Diagnosis Improvement based on Image Processing.
 Developed a Novel Hybrid Approach for Selecting Users in Federated Learning with Deep-Q-Reinforcement Learning based on Spectral Clustering.
 Supervised Three Master Students in Artificial Intelligence Engineering.
2. Worked as a RA (Research Associate) at Kingston University in the Faculty of Science, Engineering, and Computing. (May 2018, August 2018)
 Developed a Feedback System Between a BAXTER Robot and a Dynamic Active-pixel Vision Sensor (DAVIS) Camera.
 Designed and Implemented a New 3D Printed Gripper for a BAXTER Robot.
 Supervised Two Undergraduate Students in Mechatronics Engineering.
3. Worked as a RA (Research Assistant) at the Big Data Processing and Visualization Lab Department of Data Science and Visualization. (January 2015, January 2017)
 Collaborated with Cross-Functional Teams to Identify Business Requirements and Develop Solutions to Complex Data Problems.
 Designed and Implemented a Line Follower Robot utilizing an FPGA Microcontroller.
 Developed and embedded a Heating Chamber with MyRio and LabVIEW Software.

Research Mobility for Ph.D., University of California, Riverside, USA. (June 2022, December 2022)
Ph.D. Candidate in Computer Vision, University of Rovira i Virgili, Tarragona, Spain. (October 2019, Present)
Project: Self-supervised Monocular Depth Estimation based on Graph Convolutional Network.
M.Sc. in Mechatronics Systems, Kingston University, London, UK. (September 2017, January 2019)
Project: Using the Feedback of Dynamic Active-Pixel Vision Sensor (Davis) to Prevent Slip in Real Time.
B.Sc. in Mechatronic Engineering, University of Debrecen, Debrecen, Hungary. (September 2013, January 2017)
Project: Designing a Line Follower Robot with FPGA Microcontroller.