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Samad Barri Khojasteh I am a researcher at the University of Alcalá (UAH) in Spain, where I work under the supervision of Daniel Pizarro and Adrien Bartoli. In 2025, I visited the EnCoV Research Group at the University of Clermont Auvergne, France, where I worked on deformable registration with Adrien Bartoli. Previously, I was a research intern at the University of Oviedo, Spain, under the Erasmus+ program, supervised by José Ramón Villar and Víctor M. Gonzalez. |
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ResearchMy research interests lie in applying machine learning and deep learning techniques to real-world healthcare challenges. I am currently working on Non-Rigid Structure from Motion (NRSfM), 3D reconstruction, and deformable modeling for medical imaging, with a particular focus on Neural Radiance Fields (NeRF) and non-rigid registration. My research aims to develop high-fidelity and robust methods for reconstruction and registration in minimally invasive surgery (MIS). Previously, I worked on Human Activity Recognition (HAR), with an emphasis on fall detection for elder people and monitoring. |
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Selected Publications |
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MIS-NeRF: neural radiance fields in minimally-invasive surgery
Samad Barri Khojasteh, David Fuentes-Jimenez, Daniel Pizarro , Yamid Espinel, Adrien Bartoli IPCAI, 2025 project page / paper MIS-NeRF improves AR-based lesion localization by facilitating accurate 3D model registration to multiple MIS images. |
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Neuron Characterization in Complex Cultures Using a Combined YOLO and U-Net Segmentation
Approach
Paula Puerta, Berke Öztürk, Samad Barri Khojasteh, Víctor M. González, José R. Villar, Esther Serrano-Pertierra, Antonello Novelli, M.Teresa Fernández-Sánchez, Ángel Río-Álvarez, SOCO, 2023 project page / paper Neuron detection in complex cultures by YOLO and U-Net Segmentation. |
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Autonomous on-wrist acceleration-based fall detection systems: unsolved challenges Approach
José R. Villar, Camelia Chira, Enrique de la Cal, Víctor M. González, Javier Sedano, Samad Barri Khojasteh, Neurocomputing, 2022 project page / paper Evaluation autonomous on-wrist wearable devices using different trained machine learning models, where a single dataset is used for training and multiple independent datasets are used for validation. |
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Mixing user-centered and generalized models for Fall Detection
Approach
Mirko Fáñez, José R. Villar, Enrique de la Cal, Víctor M. González, Javier Sedano, Samad Barri Khojasteh, Neurocomputing, 2022 project page / paper This paper proposes a hybrid fall detection method combining personalized and generalized models. The approach improves robustness and accuracy across different users compared to single-model method |
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Evaluation of a Wrist-Based Wearable Fall Detection Method
Approach
Samad Barri Khojasteh, José R. Villar, Enrique de la Cal, Víctor M. González, Javier Sedano, Harun Reşit Yazggan, HAIS, 2018 project page / paper This paper evaluates a fall detection system based on improved feature extraction and data balancing techniques to enhance classification performance.. |
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Improving Fall Detection Using an On-Wrist Wearable Accelerometer
Approach
Samad Barri Khojasteh, José R. Villar, Camelia Chira, Víctor M. González, Enrique De la Cal, SENSORS, 2018 project page / paper Propose the low-cost computation fall detection system on wearable accelerometer. |
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A Stochastic Programming Model for Decision-Making Concerning Medical Supply Location and Allocation in Disaster Management
Approach
Samad Barri Khojasteh, Irfan Macit , Cambridge, 2017 project page / paper Stochastic programming model as a solution for optimizing the problem of locating and allocating medical supplies. |
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This website is adapted from Jon Barron's template. |