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Yat-Hong Lam has extensive work experience in various industries and roles. Currently, they are working as an AI Engineer at Silo AI, where they are involved in consultant projects to enable AI applications in different industries. Specifically, they have worked on projects such as implementing deep learning-based visual quality control in the pharmaceutical industry with low latency and developing an open-source software called CompressAI-Vision for Video Coding for Machine in collaboration with Interdigital.

Prior to that, Yat-Hong Lam worked as a Researcher and PhD student at Tampere University, starting in 2021. They also had a research internship at Nokia from 2019 to 2021, where they gained valuable experience.

In 2018, Yat-Hong Lam had an internship at Inria, where they focused on deep learning in Saliency Prediction. During their internship, they conducted studies on inter-observer variation of saliency maps and designed a protocol for eye-tracking experiments in saliency map prediction.

Before transitioning into the field of AI and research, Yat-Hong Lam worked as an Engineer (Testing Methodology Development) at SAE Magnetics (H.K.) Ltd. from 2014 to 2016. Prior to that, they worked as a Metrology Engineer at ASM Pacific Technology Ltd. from 2012 to 2014.

Their journey in the tech field began as a Teaching Assistant at HKUST while pursuing their MPhil degree from 2010 to 2012.

Yat-Hong Lam's education history is as follows:

Yat-Hong Lam is currently pursuing a Doctor of Philosophy (PhD) degree in Computer Vision at Tampere University, starting from the year 2021.

In 2017, Yat-Hong Lam attended the Norwegian University of Science and Technology (NTNU) for a Master's degree in Colour Imaging, with a focus on Colour Imaging and Object recognition. This program lasted for one year.

In the same year, Yat-Hong Lam also studied at Universidad de Granada for a certificate program in Color in Science and Industry, specifically focusing on Color Science. This program was also completed within one year.

From 2016 to 2017, Yat-Hong Lam attended Université Jean Monnet Saint-Etienne, pursuing another certificate program in Color in Science and Industry, with a specialization in Color Science. This program lasted for two years.

In 2012, Yat-Hong Lam acquired a Master of Philosophy (MPhil) degree in Physics from The Hong Kong University of Science and Technology, concentrating on the field of Physics. This program lasted for two years.

From 2007 to 2010, Yat-Hong Lam earned a Bachelor of Science (BSc) degree from The Hong Kong University of Science and Technology, with a major in Physics and an option in Physics and Mathematics. This program was completed within three years.

Prior to university education, Yat-Hong Lam attended CSWCSS from 2000 to 2007. The specific degree or field of study during this period is not provided.

Additionally, Yat-Hong Lam holds several certifications. These certifications include "Robotics: Aerial Robotics" from Coursera Course Certificates in April 2016 (obtained twice), "Dynamical Modeling Methods for Systems Biology" from Coursera Course Certificates in March 2016, "edX Honor Code Certificate for Introduction to Java Programming - Part 1" from edX in July 2015, "Social and Economic Networks: Models and Analysis" from Coursera in June 2013, "edX Honor Code Certificate for Quantum Mechanics and Quantum Computation" from edX in April 2013, and "AWS Certified Cloud Practitioner" from Amazon Web Services (AWS) in December 2022.