Dr Pam Johnston

Biography	Pam obtained her PhD from Robert Gordon University, graduating in December 2019. Her thesis, "Beyond the pixels: learning and utilising video compression features for localisation of digital tampering", is published on RGU's OpenAIR and is about how features of compression can be learned by neural networks and applied to detect regions of manipulation in tampered videos. Her research interests include the application of deep neural networks in video analysis, particularly learning specific features from controlled datasets. Pam's first degree was an MEng (Electronic and Computer) from the University of Aberdeen in 2001. She then spent over a decade working for a world class supplier of video compression codecs, implementing standards such as MPEG2, AVC and HEVC on a variety of platforms from FPGAs to bespoke microprocessors. Pam has also worked on video analysis using deep learning on mobile devices as a KTP associate (Innovate's Knowledge Transfer Partnership).
Research Interests	Computer vision; machine learning; video and image analysis; deep neural networks; dataset synthesis; manipulation and tampering in images and videos.

Biography

Pam obtained her PhD from Robert Gordon University, graduating in December 2019. Her thesis, "Beyond the pixels: learning and utilising video compression features for localisation of digital tampering", is published on RGU's OpenAIR and is about how features of compression can be learned by neural networks and applied to detect regions of manipulation in tampered videos. Her research interests include the application of deep neural networks in video analysis, particularly learning specific features from controlled datasets.

Pam's first degree was an MEng (Electronic and Computer) from the University of Aberdeen in 2001. She then spent over a decade working for a world class supplier of video compression codecs, implementing standards such as MPEG2, AVC and HEVC on a variety of platforms from FPGAs to bespoke microprocessors. Pam has also worked on video analysis using deep learning on mobile devices as a KTP associate (Innovate's Knowledge Transfer Partnership).

Research Interests

Computer vision; machine learning; video and image analysis; deep neural networks; dataset synthesis; manipulation and tampering in images and videos.