ETH ZURICH - Key Persons
Alexander Möllers, Alexander Immer, Elvin Isufi, Vincent Fortuin Uncertainty in Graph Contrastive Learning with Bayesian Neural Networks AABI 2023
David Danko, Daniela Bezdan, Evan E. Afshin, Sofia Ahsanuddin, Chandrima Bhattacharya, Daniel J. Butler, Kern Rei Chng, Daisy Donnellan, Jochen Hecht, Katelyn Jackson, Katerina Kuchin, Mikhail Karasikov, Abigail Lyons, Lauren Mak, Dmitry Meleshko, Harun Mustafa, Beth Mutai, Russell Y. Neches, Amanda Ng, Olga Nikolayeva, Tatyana Nikolayeva, Eileen Png, Krista A. Ryon, Jorge L. Sanchez, Heba Shaaban, Maria A. Sierra, Dominique Thomas, Ben Young, Omar O. Abudayyeh, Josue Alicea, Malay Bhattacharyya, Ran Blekhman, Eduardo Castro-Nallar, Ana M. Cañas, Aspassia D. Chatziefthimiou, Robert W. Crawford, Francesca De Filippis, Youping Deng, Christelle Desnues, Emmanuel Dias-Neto, Marius Dybwad, Eran Elhaik, Danilo Ercolini, Alina Frolova, Dennis Gankin, Jonathan S. Gootenberg, Alexandra B. Graf, David C. Green, Iman Hajirasouliha, Jaden J.A. Hastings, Mark Hernandez, Gregorio Iraola, Soojin Jang, Andre Kahles, Frank J. Kelly, Kaymisha Knights, Nikos C. Kyrpides, Paweł P. Łabaj, Patrick K.H. Lee, Marcus H.Y. Leung, Per O. Ljungdahl, Gabriella Mason-Buck, Ken McGrath, Cem Meydan, Emmanuel F. Mongodin, Milton Ozorio Moraes, Niranjan Nagarajan, Marina Nieto-Caballero, Houtan Noushmehr, Manuela Oliveira, Stephan Ossowski, Olayinka O. Osuolale, Orhan Özcan, David Paez-Espino, Nicolás Rascovan, Hugues Richard, Gunnar Rätsch, Lynn M. Schriml, Torsten Semmler, Osman U. Sezerman, Leming Shi, Tieliu Shi, Rania Siam, Le Huu Song, Haruo Suzuki, Denise Syndercombe Court, Scott W. Tighe, Xinzhao Tong, Klas I. Udekwu, Juan A. Ugalde, Brandon Valentine, Dimitar I. Vassilev, Elena M. Vayndorf, Thirumalaisamy P. Velavan, Jun Wu, María M. Zambrano, Jifeng Zhu, Sibo Zhu, Christopher E. Mason, The International MetaSUB Consortium A global metagenomic map of urban microbiomes and antimicrobial resistance Cell
Job Titles:
- Department of Computer Science
- Department of Computer Science / Biomedical Informatics Group
I am particularly interested in learning to align cellular populations across both perturbational effects as well as multimodal profiles. I've applied these efforts towards understanding and optimizing cancer treatments, particiuarlly within the context of the Tumor Profiler consortium. Prior to starting my PhD, I finished a Masters degree in Computer Science, also at ETH Zürich, where Ie worked on matching cancerous somatic mutations to information extracted from clinical text notes, and contributed analysis to the cancer consortia ICGC and TCGA.
In November 2018 I started my PhD in Max Plank - ETH Center for Learning Systems, supervised by Gunnar Rätsch and Isabel Valera.
The combination of scientific facts and communication is my thing! I studied Biochemistry and obtained my Doctoral Degree from ETH in the Department of Materials Science, working on tailored bionanomaterials via self-assembly techniques, mimicking structures from mother nature. Before joining the Biomedical Informatics Group, I worked in communication and public relations for the healthcare industry and fundraising and philanthropic projects for higher education.
I have obtained my Bachelor's Degree in Computer Science, followed by a Master's Degree in Data Science at ETH Zürich. I have always been fascinated by the capabilities of modern computer hardware, and thus ventured into the world of HPC during my bachelor's degree. This led me to learn about my fascination for machine learning and the powerful applications we can develop by using the computing capabilities available to us. I started to focus my path towards data science in the biomedical and health care domain. My aim is to contribute to improved health care and I thus joined the Biomedical Informatics Group at ETH as a Ph.D. Student in 2022.
He earned his Ph.D. at the German National Laboratory for Information Technology under supervision of Klaus-Robert Müller and was a postdoc with Bob Williamson and Bernhard Schölkopf. He received the Max Planck Young and Independent Investigator award and was leading the group on Machine Learning in Genome Biology at the Friedrich Miescher Laboratory in Tübingen (2005-2011). In 2012, he joined Memorial Sloan Kettering Cancer Center as Associate Faculty. In May 2016, he and his lab moved to Zürich to join the Computer Science Department of ETH Zürich.
Bio: Before joining ETH, I earned a BSc in Computer Engineering from Sharif University, an MPhil in Cognitive Neuroscience at SISSA, Italy, and an MSc in Computer Science from ETH Zurich.
I am a Doctoral Fellow at the ETH AI Center, jointly supervised by Prof. Gunnar Rätsch of the BMI group and Prof. Bernhard Schölkopf, leader the Empirical Inference group at the Max-Planck Institute for Intelligent Systems (Tübingen, Germany). Prior to my PhD, I led a project on imitation learning for clinical decision-making with Prof. Mihaela van der Schaar at the University of Cambridge. My professional experience also includes medical device development for stroke treatment, sensor-assisted surgery and 3D-printed heart stents, as well as software engineering at CERN. In parallel, I studied Physics, Materials Science and Machine Learning at Cambridge.
Job Titles:
- Ingo Schilken, Mikhail Karasikov, Carsten Eickhoff, Gunnar Rätsch, Andre Kahles Dynamic Compression Schemes for Graph Coloring Bioinformatics
- Post Doc
I am interested in integrating multiple layers of omics data with novel methods to help predict novel treatment-targets and improve patient care.
I completed my B.Sc between the Classe Préparatoire Henri IV (biology, physics, mathematics, chemistry) and the Ecole Normale Supérieure in Lyon (biology). I moved to Switzerland for my M.Sc. in Life Sciences and Technology at the EPFL with a focus on computational biology. I had the opportunity to work both in academia and industry. I have held positions at Stanford University under the supervision of Anne Brunet (Aging); at EPFL under the supervision of Jacques Fellay (Human Genomics) and at Lambda Health System (Clinical assays analysis), a Swiss MedTech start-up. I recently completed my Master Thesis at Imperial College London in the team of Inga Prokopenko. There, I investigated glyceamic traits prediction from multi-omics data with machine learning in diabetic patients. I joined the Biomedical Informatics group in 2018 for my Ph.D.
Job Titles:
- Ingo Schilken, Harun Mustafa, Gunnar Rätsch, Carsten Eickhoff, Andre Kahles Efficient Graph - Color Compression With Neighborhood - Informed Bloom Filters BioRxiv
- Submitted Genome Research, RECOMB 2023
- Submitted Journal Cancer Research
- Submitted Nucleic Acids Research
- Submitted Research Square ( Preprint Platform )
I am broadly interested in Machine Learning and Signal Processing for Healthcare, in particular the application of Deep Learning and Bayesian non-parametric methods to EHR and genomic data.
Before joining the Rätsch Lab, I studied Computer Science at ETH Zürich (MSc) and Computing at Imperial College London (BEng). Previously I have worked on forecasting intracranial hypertension and cerebral hypoxia events using high-frequency ICU data.
I studied Administration at the University of Poznan, Poland and gained my first work experience as a management assistant in an insurance company. I am happy to provide administrative support to the Biomedical Informatics group to make the group most effective and the members happy.
Job Titles:
- Editor
- Head
- Data Scientist
- Head of the Biomedical Informatics Group
Data scientist Gunnar Rätsch develops and applies advanced data analysis and modeling techniques to data from deep molecular profiling, medical and health records, as well as images.
My research focuses on creating computational tools for synthetic biology, metagenomics and transcriptomics. I am also interested in integrating different types of omics data for health and diagnostic applications.
I am a joint doctoral student at Prof. Gunnar Rätsch's group at the D-INFK and Prof. Randall Platt's group at the D-BSSE.