Work with thought leaders and academic experts from Polish Academy of Sciences

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 a Scientist at the Lawson 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 and Research Associate 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 Biocybernetics and Biomedical Engineering. He received his MSc in Electronics/Optoelectronics from the Military University of Technology, Warsaw, Poland, in 2008.

Empowering innovation through 10+ years of dedicated expertise in Computational Research Science, I specialize in leveraging statistical techniques, mathematical modeling, and high-performance computing (HPC) to solve complex challenges across diverse domains. My expertise spans critical areas such as Theoretical/Computational Quantum Condensed Matter Physics, Computational Chemistry, Computational Material Science, Quantum Computing, and Data Analysis. With a proven track record in deploying advanced methodologies, including quantum teleportation (qubit transfer in spin networks), Quantum Monte Carlo Simulations, First-principles (ab-initio) calculations, and cutting-edge algorithms, I bring a robust foundation in both classical and quantum realms. I thrive on translating complex data into actionable insights, utilizing a spectrum of Machine Learning techniques—from supervised to unsupervised and reinforcement learning, encompassing Regression, Classification, Neural Networks, TensorFlow, and Recommender Systems.