Somayeh Asadi, PhD
Somayeh is a PhD graduate in Physics from K. N. Toosi University of Technology, and she was a postdoctoral research member of the Ophthalmic Research Center (ORC) & Tissue engineering Research Center (TERC) of Shahid Beheshti University of medical science. Her main research activities in the lab were the application of nanoparticles in cancer treatment which includes the in vitro, ex vivo and in vivo studies. She was focusing on both physical simulations about the laser-tissue-nanoparticles interaction, and on related experimental setup.
Martina De Landro, PhD
Martina was a PhD Student in Mechanical Engineering. She has received her MS degree in Biomedical Engineering from Università Campus Bio-Medico di Roma. She performed MS thesis at the IHU of Strasbourg, where she investigated the use of fiber optic sensors for catheters tracking. Her work was focused on the investigation of sensors and innovative images-based techniques for the monitoring of thermal outcome in tissues undergoing laser ablation.
Mohammadamin Soltani, PhD
Mohammadamin is a PhD graduated in Computer science – Artificial intelligence from Shiraz University, and he was a researcher in Traffic and transportation research center of Shiraz University. His main research interests include Optimization, Prediction models, Machine vision, Image processing, Intelligence transportation system (ITS), and Deep Neural Network (DNN). He has also twenty years of experience in web application development, have worked with several frameworks and programming languages include Python, Matlab, C++, Vue.js, Django, Nativescript, PHP, Angular.js, Keras, and Tensorflow.
Viacheslav Danilov, PhD
Senior ML Engineer and Senior Research Scientist specializing in data science, data analysis, and machine learning development. PhD in Computer Science obtained from Tomsk Polytechnic University in 2020. Over 7 years of experience as an ML Engineer & Researcher in both academic and industry domains. Experienced with every stage of the development cycle for dynamic AI projects. Well-versed in numerous programming languages and frameworks including Python, R, TensorFlow, Keras, and PyTorch. Worked extensively on ML tasks using a wide range of AWS services like EC2, IAM, S3, ECR, and SageMaker. Strong background in data analysis, mathematical modeling, image processing, and visualization.
Annalisa was a Ph.D. student in Mechanical Engineering. She was working on the HYPERSIGHT project in our lab. Annalisa has received her Master of Science degree in Mechanical Engineering - Production System (Fall 2020). Her Master Thesis was focused on numerical simulation and LabVIEW development of temperature-driven software for controlling laser ablation therapies in biological tissue.
Ahad has received his MS degree in Chemical Engineering from the University of Tehran. His MSc thesis majored in designing control systems in the presence of incomplete data by using Artificial Intelligence methods. His research interests fit to computational fluid dynamics, Optimization, and Design and Modeling of Transport Phenomena. He was involved in the LASER OPTIMAL project in the developing a reliable simulation to analyze the laser ablation process behavior, that was aimed to determine the physical and thermal behavior of biological tissues.
Nava Schulmann, PhD
Nava holds a PhD in Physics from Charles Sadron Institute, CNRS - Strasbourg, France. As a postdoctoral research fellow in the context of the LASER OPTIMAL project she developed a stochastic filtering framework, that aims at providing an optimal temperature map estimation, by combining bio-physical models with real-time measurements. Nava’s past research lies in the area of Complex Materials. As a postdoctoral fellow at the Weizmann Institute of Science (2013-2015), she participated in a science-educational project, targeting the fundamentals of Statistical Physics. As a research engineer at ICube, within the Mimesis team of Inria (2018-2019), she worked on questions related to stochastic filtering, parameter estimation and system observability.