Sotiris Nousias

Welcome to my website! I am Sotiris, Postdoctoral Fellow at University of Toronto working with Prof. Kyros Kutulakos. My current research focuses on imaging and 3D reconstruction under low light conditions.

Prior to UofT, I obtained my PhD from UCL under the supervision of Prof. Christos Bergeles. During my PhD, I conducted research on structure from motion with light fields. Centuries ago, I worked on state estimation for legged robots under the supervision of Prof. Evangelos Papadopoulos.

Email / X / Google Scholar

Research

I'm interested in computer vision, computational photography and neural fields. My current research revolves around photon cameras, a cutting-edge technology capable of detecting the tiniest unit of light - the photon. I'm excited about coming up with new ways to process signals from photon cameras, so we can see the world in never-before-seen ways.

I will join Purdue University in the CS department as an assistant professor in Fall 2025!

Prospective students: I am actively looking for motivated and talented students! If you are interested in joining my group, please read this.

	Opportunistic Single‑Photon Time of Flight Sotiris Nousias^, Mian Wei^, Howard Xiao, Maxx Wu, Shahmeer Athar, Kevin J. Wang, Anagh Malik, David A. Barmherzig, David B. Lindell, Kiriakos N. Kutulakos * Joint first authors. CVPR 2025, Oral project page We propose a passive single‑photon method that opportunistically recovers time‑of‑flight from ambient pulsed light sources.
	Passive Ultra-Wideband Single-Photon Imaging Mian Wei^, Sotiris Nousias^, Rahul Gulve , David B. Lindell, Kiriakos N. Kutulakos * Joint first authors. ICCV 2023, Marr Prize (best paper award) project page We introduce a novel theory and method that passively captures a dynamic scene once and allows re-rendering of video across 9+ orders of magnitude in time.
	Transient Neural Radiance Fields for Lidar View Synthesis and 3D Reconstruction Anagh Malik, Parsa Mirdehghan, Sotiris Nousias, Kiriakos N. Kutulakos, David B. Lindell NeurIPS 2023, Spotlight project page / video / arXiv We introduce a method to do novel view lidar synthesis, allowing sparse view scene reconstruction.
	Design and quasistatic modelling of hybrid continuum multi-arm robots Zisos Mitros, S.M.Hadi Sadati, Sotiris Nousias, Lyndon Da Cruz, Christos Bergeles ICRA 2022 Novel design and modelling of continuum robots for robotic surgery.
	From Calibration to Large-Scale Structure from Motion with Light Fields Sotirios D. Nousias University College London, 2021 PhD Thesis Examiners: Prof. Andrew Davison, Dr Fransisco Vasconcelos
	A linear approach to absolute pose estimation for light fields Sotiris Nousias, Manolis Lourakis, Pearse Keane, Sebastien Ourselin, Christos Bergeles 3DV 2020 Absolute pose estimation for light fields using 4 correspondences.
	Large-scale, metric structure from motion for unordered light fields Sotiris Nousias, Manolis Lourakis, Christos Bergeles CVPR 2019 video Large scale structure from motion framework for metric 3D reconstruction using light fields.
	A Theory of Fermat Paths for Non-Line-of-Sight Shape Reconstruction Shumian Xin, Sotiris Nousias, Kyriakos N. Kutulakos, Aswin C. Sankaranarayanan, Srinivasa G. Narasimhan, Ioannis Gkioulekas CVPR 2019, Best Paper Award project page NLOS shape reconstruction.
	Part-to-whole Registration of Histology and MRI using Shape Elements Jonas Pichat, Juan Eugenio Iglesias, Sotiris Nousias , Tarek Yousry, Sebastien Ourselin, Marc Modat ICCV Workshops 2017 Registration of different modalities in medical images using level-lines.
	Corner-based Geometric Calibration of Multi-focus plenoptic cameras Sotiris Nousias, Francois Chadebecq, Jonas Pichat, Pearse Keane, Sebastien Ourselin, Christos Bergeles ICCV 2017 code / supplementary Calibration of plenoptic cameras using checkerboards.
	Quadruped Robot Roll and Pitch Estimation using an Unscented Kalman Filter Sotiris Nousias, Evangelos Papadopoulos Med. Conf. on Control and Automation 2016 Estimation of a quadruped's roll and pitch using an IMU and leg kinematics.

I stole this template from Jon Barron.