Work with thought leaders and academic experts in radiological and ultrasound technology

Dr. Daniel Milej is a multidisciplinary researcher with experience in medical biophysics, electronics, biocybernetics, biomedical optics and engineering. He is highly knowledgeable and experienced in a range of research techniques. He is currently a Research Associate at the Lawson Health Research Institute, leading the transition of multimodal optical imaging systems from a research setting to clinical use in an ICU and OR environment, working closely with teams of nurses, surgeons, doctors and respiratory therapists. Previously he was a postdoctoral fellow working on developing noninvasive modalities for brain activity monitoring in the Department of Medical Biophysics at Western University. Before that, Dr. Milej worked as a researcher at the Nalecz Institute of Biocybernetics and Biomedical Engineering. He obtained his Ph.D. in 2014 from the Polish Academy of Science, specializing in Electronics and Biomedical Engineering. He received his MSc from the Military University of Technology in 2008.

My core interests lie in understanding how children and adolescents perceive and interpret social signals and how emerging functional specificity of the developing brain supports this process. My approach primarily involves using the face processing system as a model domain. Faces are dynamic stimuli from which we extract many different kinds of information (e.g., gender, age, emotional state, mate potential, social status, trustworthiness, intentions, “person knowledge”). All of these processes must be executed accurately and rapidly for many faces over the course of a single day, making face processing among the most taxing perceptual challenges confronted by people in their day-to-day life. Given that faces are also the pre-eminent social signal, studying developmental changes in the behavioral and brain basis of face processing in typically developing individuals and in those affected by social-emotional disorders may index a core set of developmental changes within the broader social information processing system. I employ converging methodologies, including functional (fMRI) and structural magnetic resonance, and diffusion tensor imaging (DTI) along with detailed behavioral paradigms in both typically developing populations and those with developmental disorders to examine development from early childhood to adulthood.

Christian Waugh, Ph.D., Associate Professor of Psychology at Wake Forest University, NC, is an expert in the study of stress resilience, emotions, and effective coping habits. His research features resilience as the result of stress, trauma, and the ability to experience positive emotions in times of stress. Dr. Waugh has been twice honored for teaching excellence at Wake Forest, is a professional speaker, and has published several dozen scientific articles.

I'm a Computer Scientist at [CONICET](http://www.conicet.gov.ar/) and an Assistant Professor at [Universidad Torcuato Di Tella](https://www.utdt.edu/), Argentina. I'm a former postdoc from [IST Austria - Bernd Bickel's group](https://ist.ac.at/). I've got my Ph.D. at [GRAPHDECO](https://team.inria.fr/graphdeco/) group, [INRIA Sophia Antipolis](https://www.inria.fr/centre/sophia/), France. In 2012 I've graduated as a Systems Engineer from [UNICEN University](https://www.unicen.edu.ar/), Tandil, Argentina. My research interests focus on developing AI tools for 2D and 3D content manipulation.

Dhritiman Das is a highly accomplished computer scientist with a strong background in bioengineering. He holds a Ph.D. in Computer Science from the Technical University of Munich, where he focused on developing innovative machine learning algorithms for medical imaging applications. More specifically, he developed applied machine learning and computer vision tools for accelerated processing and analysis of large-scale brain imaging (MRSI) data. Prior to his doctoral studies, Dhritiman earned a Master of Science in Bioengineering from Arizona State University and a Bachelor of Engineering in Biomedical Engineering from Manipal Institute of Technology. Throughout his academic career, Dhritiman has demonstrated a strong passion for research and has published several papers in top computer science and biomedical engineering journals. He has also presented his work at numerous international conferences and workshops, gaining recognition from the scientific community. In addition to his academic achievements, Dhritiman has gained valuable industry experience through various internships and research positions. He has worked as a Postdoctoral Researcher at the Massachusetts Institute of Technology, where he collaborated with leading researchers to develop cutting-edge technologies for healthcare applications. His work here focused on self-supervised learning, generative models and neuroinformatics. He has also held positions at GE Healthcare and Siemens Limited, where he applied his expertise in information theory, computer vision and machine learning to solve real-world challenges in the field of medical imaging. Dhritiman is a skilled researcher and problem-solver with a strong background in both computer science and bioengineering. He is dedicated to using his knowledge and expertise to make a positive impact in the field of healthcare and beyond.

Experienced academic and researcher specializing in data science and computer vision, with a proven track record in academia and industry. Proficient in Computer Vision, Machine Learning, and Image Processing, with published many works recognized by over 1000 citations in peer-reviewed publications. Proven ability to collaborate effectively within multidisciplinary teams to tackle complex problems and deliver innovative solutions.  Advocate for teamwork, effective communication, and mentorship.

I hold a PhD Eng. degree in computer science. I am a graduate of the Polish-Japanese Academy of Information Technology in Warsaw, POLAND. Currently, I am associate professor at the Cathedral of Multimedia at the same university. I lead and conduct scientific projects and research related to natural language processing and machine learning based on statistical methods and neural networks. I eagerly take up IT challenges and engage in interesting interdisciplinary projects, in particular related to HCI, UX, medicine, and psychology. In addition, as my profession, I have worked as a lecturer at the Warsaw School of Photography, and as an IT trainer. My specialties as a teacher are primarily deep learning, machine learning, natural language processing, computational linguistics, multimedia, HCI, UX, mobile applications, HTML 5, Adobe applications, and server products from Apple and Microsoft. As far as my didactic work is concerned, I lead classroom studies at the faculty of computer science and at the new media art department of the Polish-Japanese Academy of Information Technology and, in the past, I have also directed classes and lectures at the Warsaw School of Photography & Graphic Design. I am also an expert at the Polish National Agency for Academic Exchange, a member of the Polish Information Processing Society, and a member of the Polish Telemedicine and eHealth Society with Bene Meritus honor. Finally, I am a certified Microsoft, Apple, Adobe, w3schools, and EITCA specialist as well as being the Author of many scientific monographs and specialized IT books related to machine learning, administration of servers, and multimedia. I also engage as an editor of various specialized IT web portals such as in4.pl, pclab.pl, and e-biotechnologia.pl where I am author of training materials, guides, and hardware reviews. Some of my articles have also been published in iCoder Magazine and Komputer Świat magazine.

Jonadab is a postdoctoral research fellow. He graduated with a degree in Medicine from the Fluminense Federal University, in Brazil. He studied at UCLA during medical school, where he also worked on brain tumor imaging research. Driven by a particular interest in neuroimaging, he has worked with different modalities in clinical studies, including structural and functional MRI, EEG source localization, and tractography. As a future neurologist, Jonadab is interested in the interplay between brain lesions and their clinical and cognitive manifestations. Currently, he uses ultra-high field MRI to study the mechanisms of cortical lesion formation and repair, as well as how these processes are related to brain remodeling and disease progression.

Yasmeen is a Lecturer with data science and AI department at Monash Faculty of Information Technology with over a decade of interdisciplinary research experience in AI for healthcare analytics. She received her Ph.D. from the University of Melbourne in 2018 (Australia). Her research focuses on the use of AI for automated medical image analysis for better management of various health conditions including, kidney/breast/skin cancer, glaucoma, psoriasis. She worked on various research projects including event detection in social media streams, AI for automatic systematic reviews, cancer segmentation and classification, disease severity assessment and lesion detection using different data modalities (text, numerical, 2D images, and 3D volumes). Her research work is recognised through serval research publications, 2 patents, several invited talks, and prestigious research grants. Her research interests include AI, data science, NLP, computer vision, and medical image analytics across domains of radiology, pathology, dermatology, and ophthalmology.