The human body is a biomechanical structure that is made up of three systems: muscular system, skeletal system and neural system. These three systems (the so-called "Neuro-Musculo-Skeletal System'') are profoundly interconnected and a change in one system affects other two systems. Unfortunately, researchers often study human body systems and develop related computing technologies in relative isolation. To develop the ability to conduct  research on these three major systems together, my academic career has taken me on a journey. My PhD research at Prince of Songkla University, Thailand, was focused on the muscular system and developing algorithms to accurately classify upper-extremity movement patterns from electromyographic (EMG) patterns. These patterns can be used as information sources for the control of multifunctional assistive and rehabilitative devices referred to as "Myoelectric Control" systems or "muscle-computer" interfaces. During the final year of my PhD studies, at the University of Essex, in the UK, and during my first postdoctoral training, at Université Grenoble Alpes, France, I began to focus my research on improving the robustness and generalization ability of these systems. This work focused not only on developing the algorithms under laboratory well-controlled conditions, but also to address and validate the assumptions with regard to user behavior in real world contexts.

The muscular system together with the skeletal system form the musculoskeletal system which is responsible for movement of the human body. To expand my knowledge and experience with the musculo-skeletal system, my second postdoctoral research position at the University of Calgary, Canada, was aimed at advanced machine learning approaches, involving thousands of runners and walkers, to detect both major and subtle changes in "Gait Biomechanics" for the purpose of injury prevention and optimal rehabilitation. These two systems, however, are controlled through the nervous system. Therefore, a study of the brain and nervous system (so-called "Neuroscience") is necessary. As a researcher at ISI Foundation, Italy, my research was aimed at a set of techniques rooted in algebraic topology, collectively referred to as topological data analysis (TDA), to study human brain functional connectivity in neurodegenerative diseases.

I am currently a Postdoctoral Fellow at the Institute of Biomedical Engineering at the University of New Brunswick, Fredericton, NB, Canada (September 2017-Present) under the supervision of Dr. Erik Scheme. Since 2009, I have developed an H-index of 19 (i10-index of 36) and my 96 published refereed journals, book chapters, conference proceedings, abstracts, and invited talks have been cited 1884 timesThirty-one papers have been published in ISI indexed journals (22 as the first author)... more (about me)

Based on my research expertise, I have served as an invited reviewer for 43 different peer-reviewed journals in ISI Web of Science over the past 6 years. In total, I have reviewed more than 125 manuscripts, which were related to my area of research expertise. I am currently an associate editor at IRBM (Innovation and Research in BioMedical engineering), an ISI indexed journal. ... more (professional activities)

Recent Articles

(Journal of the Royal Society Interface; IF2016: 3.579)

(Journal of Sport and Health Science; IF2016: 2.531)

Highly Cited Articles

Most Highly Cited Paper in My Google Scholar Profile (322 times)

(Expert Systems with Applications; IF2016: 3.928)

The Most Highly Cited Article of Measurement Science Review 
(IF2016: 1.344) in ISI Web of Science (among 386 articles)

The 2nd Most Highly Cited Article of Elektronika ir Elektrotechnika
(IF2016: 0.859) in ISI Web of Science (among 1977 articles)