CV

Ph.D. in Applied and Computational Mathematics (ongoing)

University of Edinburgh, UK

• Title: Bayesian computation for low-photon imaging
• Supervisors: Prof. Konstantinos Zygalakis & Prof. Marcelo Pereyra

MSc in Telematics (with distinction)

Graz University of Technology, Austria

• majors in Computational Intelligence and Software Technology
• Master's thesis: Bi-level Optimization for Support Vector Machines, supervised by Prof. Thomas Pock
• Project: State Estimation with Recurrent Neural Networks, supervised by Prof. Robert Legenstein

BSc in Telematics

Graz University of Technology, Austria

• Interdisciplinary study: Information technology, electrical engineering, computer science

Erasmus Program

Université Lille 1 Science et Technologies, France

• Project: Map Reduce Programming for Machine Learning Algorithms on Graphs, supervised by Marc Tommasi and Gemma C. Garriga at INRIA

Postgraduate Reseacher

University of Edinburgh

• Developed algorithms for efficient Bayesian computation incorporating machine learning models using PyTorch and Matlab
• Achieved state-of-the-art results for reconstructing photon-starved imaging data with integrated uncertainty quantification
• Contributed to convergence proofs for convex and data-driven machine learning priors
• Executed large-scale experiments using server infrastructure, benchmarked results, and published source code for reproducibility

Research Assistant

Institute of Computer Graphics and Vision, Graz University of Technology, Austria

• Conducted research in the Computer Vision, Learning and Optimization Group, led by Prof Thomas Pock
• Contributed to the development of variational networks to solve a wide range of image reconstruction problems, including joint denoising and demosaicing, super-resolution, joint reconstruction and classification and medical image reconstruction
• Developed algorithms using convex and non-convex optimization strategies, bi-level optimization and algorithm unrolling
• Co-developed learning frameworks using Theano, TensorFlow, PyTorch and C++/CUDA

University Tutor

University of Edinburgh, UK

• Subjects: Machine Learning in Python, Calculus, Linear Algebra, Stochastic and Ordinary Differential Equations

Teaching Assistant

Graz University of Technology, Austria

• Subjects: Convex Optimisation, Analysis, Computer and communication networks

Product Owner and Agile Coach

Black Tusk GmbH, Graz, Austria

• Directed the development of medical software products, ensuring alignment with DIN EN ISO 13485 regulatory standards
• Managed product and portfolio strategies for interoperability solutions in healthcare, leveraging the HL7 FHIR standard
• Conducted customer interviews and performed comprehensive requirements engineering
• Facilitated Agile practices within the organization, mentoring teams in Scrum and Agile practices

Product Owner

Denovo GmbH, Graz, Austria

• Directed several digitization projects within a fixed-price Agile framework, using Scrum practices
• Managed product backlogs, prioritized features to maximize business value, and fostered strong client relationships
• Led the development and deployment of an AI-driven tool for waste management

Project Manager for Digital Business Solutions

Scoop and Spoon GmbH, Graz, Austria

• Led the development of software products, with responsibility for budget, time, project quality and controlling
• Led a pilot project integrating voice assistant technology for marketing
• Acted as key liaison between teams and all stakeholders

• SIAM Travel Award and Laura Wisewell Scholarship
• to attend SIAM Imaging Science, Atlanta, USA

• Laura Wisewell Travel Scholarship
• to attend the MIA conference in Berlin and the spring school in Bonn (Data-driven Inverse Problems in Biomedical Imaging)

• Best Paper Award
• German Conference on Pattern Recognition 2017, Basel, Switzerland
• Paper title: Variational Networks: Connecting Variational Methods and Deep Learning

• Best Paper Award
• Computer Vision Winter Workshop 2015, Seggau, Austria
• Paper title: Continuous Hyper-parameter Learning for Support Vector Machines

• Scholarship of Excellence
• Graz University of Technology

BenchOpt Hackathon

organised by Thomas Moreau (INRIA) at Owkin, Google AI Hub and SCAI at Sorbonne University

Spring school

Data-driven Inverse Problems in Biomedical Imaging, Bonn, Germany

Summer school

Quantifying Uncertainty: Prediction and Inverse Problems, Radboud University, Nijmegen, The Netherlands

Summer School

Mathematical and Numerical Methods in Image Processing, Berlin Mathematical School, Germany

Machine Learning Summer school

Max Planck Institute for Intelligent Systems Tübingen, Germany