Work with thought leaders and academic experts in radiology nuclear medicine imaging

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.

T. Osswald is Hoeganaes Professor of Materials at the University of Wisconsin-Madison, where he has been a faculty member since 1989. Osswald received the PhD in Mechanical Engineering from the University of Illinois at Urbana-Champaign in 1987, the MS in Mechanical Engineering from the South Dakota School of Mines and Technology in 1982, and the BS in Mechanical Engineering from the South Dakota School of Mines and Technology in 1981. Before joining the UW-Madison faculty, Osswald was a Humboldt Fellow at the Rheinisch Westfalische Technische Hochschule Aachen. Osswald’s research interests are in the areas of processing-structure-property relationships for metals and composites, with a focus on powder metallurgy and metal injection molding. His research has been supported by the National Science Foundation, the Department of Energy, the US Army Research Office, and industry. Osswald is a Fellow of ASM International and the American Academy of Mechanics, and he has received the Extrusion Division Award, the Powder Metallurgy Division Award, and the Distinguished Teaching Award from TMS.

As a Postdoctoral Researcher at UC Irvine, I apply my PhD in Cognitive Neuroscience to investigate the neural mechanisms of learning and memory. I use advanced data management, analytics, techniques to process and analyze large-scale brain imaging data sets. I have over seven years of research experience, including as a Graduate Research Assistant at Florida International University, where I contributed to multiple publications and projects on cognitive and affective neuroscience. I am passionate about advancing the scientific understanding of the brain and its functions, and collaborating with other researchers and experts in the field. I am also committed to sharing my knowledge and skills with the next generation of neuroscience students and professionals.

I am passionate about solving big problems with scientific and computational tools. A highly experienced applied mathematician working in academia (faculty) and industry (consulting), with 15+ years of research and teaching expertise in inverse problems, signal processing, and data science. A highly-skilled software engineer and analyst/architect with 6+ years of experience as a technical lead in professional software development.

Jeffrey Townsend is a Professor of Organismic and Evolutionary Biology at Yale University. He received his Ph.D. from Harvard University in 2002 and his Sc.B. from Brown University in 1994. He has been a teacher at St. Ann's School and an Assistant Professor at the University of Connecticut. He is currently the Elihu Professor of Biostatistics at Yale University.

Head of Research and Customer Success at NotedSource.

Norman Farb, PhD, is an Associate Professor of Psychology at the University of Toronto Mississauga, where he directs the Regulatory and Affective Dynamics laboratory (www.radlab.zone). He studies the psychology of well-being, focusing on mental habits, such as how we think about ourselves and interpret our emotions. He is particularly interested in why people differ in their resilience to stress, depression, and anxiety. Prof. Farb's work currently explores online training to support wellbeing, as well as neuroimaging to understand how emotional reactions predict mental health over the lifespan.

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.

Postdoctoral Researcher at the Massachusetts Institute of Technology and freelance machine-learning consultant for startups. Strong background in Deep Learning, Computer Vision, Signal Processing and Neuroinformatics. My work has involved building pipelines for integrating machine learning technologies for medical imaging research and clinical applications. Key focus areas: self-supervised learning, multimodal learning, generative models, open source ML software development, image & signal processing, large-scale datasets (2D, 3D, time-series), reproducible research. Skilled in Python (TensorFlow/Keras/Pytorch), JAX, C++, Pandas, Docker, Matlab. Previously, I was a Marie Skłodowska-Curie PhD Fellow in Computer Science at the Technical University of Munich and GE Healthcare. My thesis focused on Data Driven Methods (using Machine Learning) for Accelerated Analysis of 3D Neuroimaging Data. Strong track record of multi-site collaborations across academia and industry along with high-impact publications.

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.

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.

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.