Yoshi (Josh) graduated from the University of Warsaw with a Master’s degree in Quantitative Finance and received the Semkow Prize for his innovative research on High-Frequency Trading (HFT). He also studied Machine Learning and Reinforcement Learning at NYU Tandon School of Engineering. In the past years he has provided technical consulting services to several quantitative hedge funds and trading firms, where he did R&D on, inter alia, the application of Deep Reinforcement Learning (DRL) to financial markets and on Multi-Agent Simulation (MAS) for market risk analysis and trading strategy design. He also has expertise in blockchain and served as a technical advisor at early blockchain startups. Prior to entering the financial industry, he developed a 3D graphics engine from scratch in the gaming industry, where he gained expertise in high-performance computing in C/C++ with x86 code optimization.
Surveying and real-world capture have gone through huge changes in the last five years. Laser scanning has got faster and more mobile and we have SPOT the robot dog. Photogrammetry has increased in accuracy to rival laser scans. Now we have Gaussian Splats to bring new capabilities to reality capture. With AI being used to deliver unassisted scan to BIM, where is this industry going next?