Student Paper Competition Finalists

Please join us in congratulating the Finalists selected for the 2022 EMBS Student Paper Competition!

The Finalists will present their papers in special judging sessions on Tuesday 12 July, 2022, with the winners announced just prior to the Keynote on Wednesday 13 July, 2022.

Best of luck to all in the final phase of the competition!

Middle East-Africa:

Alaa Mohamed, Cairo University
“Bilateral Analysis Boosts the Performance of Mammography-based Deep Learning Models in Breast Cancer Risk Prediction”

Latin America:

Yesid Gutiérrez, Universidad Industrial de Santander
“Multimodal Contrastive Supervised Learning to Classify Clinical Significance MRI Regions on Prostate Cancer”


Reem Almasri, University of New South Wales
“Electromechanical Stability and Transmission Behavior of Transparent Conductive Films for Biomedical Optoelectronic Devices”


Tommaso Volpi, University of Padova
“Modeling Venous Plasma Samples in [18F]FDG PET Studies: A Nonlinear Mixed-Effects Approach”

North America:

Yue Cui, University of Tennessee, Knoxville
“Privacy-Preserving Speech-Based Depression Diagnosis Via Federated Learning”

Johann Vargas-Calixto, McGill University
“Multi-Chain Semi-Markov Analysis of Intrapartum Cardiotocography”

Thomas Conroy, Cornell University
“Physiological Features of Cardiac Ventricle and Valve Dynamics from Wearable Radio-Frequency Sensors”

Li Heng, Southern University of Science and Technology
“MVD-Net: Semantic Segmentation of Cataract Surgery Using Multi-View Learning”

Nuria Pena Perez, Queen Mary University of London
“Lateralization of Impedance Control in Dynamic versus Static Bimanual Tasks”

Maria Jantz, University of Pittsburgh
“A Computational Study of Lower Urinary Tract Nerve Recruitment with Epidural Stimulation of the Lumbosacral Spinal Cord”

Niklas Smedemark-Margulies, Northeastern University
“AutoTransfer: Subject Transfer Learning with Censored Representations on Biosignals Data”

Marie-Judith Saint Martin, Inserm – Institut Curie
“Decrypting the Information Captured by MRI-Radiomic Features in Predicting the Response to Neoadjuvant Chemotherapy in Breast Cancer”

Mineaki Oinuma, Yokohama National University
“Bio-Signal Feature Analysis to Detect Aspiration Caused by Dysphagia”

Marco Carbonaro, Politecnico di Torino
“Detecting Anatomical Characteristics of Single Motor Units by Combining High Density Electromyography and Ultrafast Ultrasound: A Simulation Study”

Noa Nuzov, Northwestern University
“True location of deep brain stimulation electrodes differs from what is seen on postoperative magnetic resonance images: An anthropomorphic phantom study”