Victor Ibanez

Data Scientist with a master's degree in neuroscience (summa cum laude) and a strong background in computational biology and machine learning. 4+ years experience as a research assistant at various institutes and 1+ years experience as data scientist in the pharmaceutical industry, leading to several first author publications and an open source package. Extensive experience in machine learning applied to many complex datasets from different domains using Python and R. Seeking for a challenging role in the pharmaceutical industry to expand data science and machine learning capabilities.

Internship Data Science at F. Hoffmann-La Roche AG, DPLabs (Jun 2022 - Jun 2023, Basel, CH): Developed top-performing Graph Convolutional Network (GCN) models for cancer research, enhancing explainability and proposing a novel architecture. Utilized PyTorch, achieved best results, and contributed to the codebase.

Research Assistant at University of Zurich, Brain Research Institute (Jul 2021 - Apr 2022, Zurich, CH): Conducted experiments with mice, created a high-performance automated behavior analysis tool using Tensorflow and OpenCV, and authored a first-author publication.

Research Assistant at University of Zurich, Institute of Forensic Medicine (Oct 2019 - present, Zurich, CH): Designed a CT image classifier, speech authenticity models, and published two first-author papers. Led data collection, preprocessing, and initiated a research project.

Research Assistant at Max Planck Institute for Intelligent Systems (Oct 2019 - Jan 2021, Stuttgart, DE): Conducted gecko aerodynamics and lizard tail stabilization experiments, resulting in a second-author publication.

Pubzip: Summarizing Scientific Literature (Jun 2023 - present): Web scraping scientific literature, NLP-based summarization with Meta's Llama2, and SQL database setup.

Classification of Orca Whale Sound (Mar 2021 - Jun 2021): Secured funding for live Orca whale abundance prediction using hydrophone signals and deep learning.

Spray Can Sound Detection (Sep 2019 - Jan 2020): Implemented a high-accuracy automated spray can sound detection system using spectrograms and deep learning on a Raspberry Pi.

M.Sc. in Neurosciences (summa cum laude) at University of Zurich. Heavy focus on computational biology.