Experience

I3S/CNRS

• France
• Research
• 1 - 100 Employee

• PhD Student in Image and Video Compression at I3S/CNRS

  • Nov 2020 - Present

  - Develop a multiple descriptions coding solution based on the HEVC standard. - Evaluate the developed solution using the ns-3 network simulator within a 802.11 channel model. - Develop a multiple descriptions coding solution based on the HEVC standard. - Evaluate the developed solution using the ns-3 network simulator within a 802.11 channel model.



FDI MATELEC S.A.

• France
• Electrical/Electronic Manufacturing
• 1 - 100 Employee

• Embedded Software Engineer

  • Sep 2020 - Oct 2020

  Implement transmission of the images jpeg via UDP.Evaluate the performance of the solution.Result: increase the number of images transmitted per second from 3 to 15.

• Embedded Software Engineer

  • Feb 2020 - Aug 2020

  - Investigate the current state of the art in VoLTE technology.- Examine the communication between LTE modems and microprocessors.- Explore the performance of JPEG encoding using both hardware and software solutions.- Understand the software architecture of products within the enterprise.- Manage resource utilization in embedded systems.



Dai hoc Da Nang

• Education Administration Programs
• 1 - 100 Employee

• Summer Researcher: Toxin-checker: Recognition of the origin of fruits / vegetables

  • Jun 2019 - Sep 2019

  - Investigate Texas Instruments' NIR spectrometer technology. - Learn about principles of machine learning and supervised learning. - Explore feature extraction techniques for signals from spectrometers. - Develop a dataset of fruits and vegetables specific to the regions. - Experiment with various machine learning algorithms. - Evaluate and analyze the results. Outcome: A preliminary machine learning prototype with 80% accuracy in detection. - Investigate Texas Instruments' NIR spectrometer technology. - Learn about principles of machine learning and supervised learning. - Explore feature extraction techniques for signals from spectrometers. - Develop a dataset of fruits and vegetables specific to the regions. - Experiment with various machine learning algorithms. - Evaluate and analyze the results. Outcome: A preliminary machine learning prototype with 80% accuracy in detection.



Laboratoire d’Electronique Antennes et Télécommunication (LEAT)

• Research Assistant : LORA GPS Tracking

  • Jun 2018 - Jul 2018

  Implement GPS communication using UART. Study LoRa wireless communication technology. Develop a prototype incorporating both technologies. Implement GPS communication using UART. Study LoRa wireless communication technology. Develop a prototype incorporating both technologies.