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Workshop
ICML 2020 Workshop on Computational Biology
Workshop CompBio · Delasa Aghamirzaie · Alexander Anderson · Elham Azizi · Abdoulaye Baniré Diallo · Cassandra Burdziak · Jill Gallaher · Anshul Kundaje · Dana Pe'er · Sandhya Prabhakaran · Amine Remita · Mark Robertson-Tessi · Wesley Tansey · Julia Vogt · Yubin Xie

Fri Jul 17 06:00 AM -- 02:30 PM (PDT) @
in Workshops Fri »
Event URL: https://icml-compbio.github.io »

The workshop will showcase recent research in the field of Computational Biology. Computational biology is an interdisciplinary field that develops and applies analytical methods, mathematical and statistical modeling and simulation to analyze and interpret vast collections of biological data, such as genetic sequences, cellular features or protein structures, and imaging datasets to make new predictions towards clinical response, discover new biology or aid drug discovery. The availability of high-dimensional data, at multiple spatial and temporal resolutions has made machine learning and deep learning methods increasingly critical for computational analysis and interpretation of the data. Conversely, biological data has also exposed unique challenges and problems that call for the development of new machine learning methods.

This workshop aims to bring together researchers working at the unique intersection of Machine Learning and Biology that include areas (and not limited to) such as computational genomics, neuroscience, pathology, radiology, evolutionary biology, population genomics, phenomics, ecology, cancer biology, causality, and representation learning and disentanglement to present recent advances and open questions to the ML community.

The workshop is a sequel to the WCB workshops we organized in the last four years ICML 2019, Long Beach , Joint ICML and IJCAI 2018, Stockholm , ICML 2017, Sydney and ICML 2016, New York as well as Workshop on Bioinformatics and AI at IJCAI 2015 Buenos Aires, IJCAI 2016 New York, IJCAI 2017 Melbourne which had excellent line-ups of talks and was well-received by the community. Every year, we received 60+ submissions. After multiple rounds of rigorous reviewing around 50 submissions were selected from which the best set of papers were chosen for Contributed talks and Spotlights and the rest were invited as Posters. We have a steadfast and growing base of reviewers making up the Program Committee. For the past two editions, a special issue of Journal of Computational Biology has been released with extended versions of a select set of accepted papers.

We invited Thomas Fuchs, Debora Marks, Fabian Theis, Olga Troyanskaya. We have received funding confirmation from PAIGE and Amazon Web Services that we intend to use for student travel awards. In past years, we have also been able to provide awards for the best poster/paper and partially contribute to the student registration fee.

Keywords: Causality · Deep Learning · Representation Learning · Computational Biology · Machine Learning · computational genomics · computational neuroscience · computational pathology · computational radiology · evolutionary biology · population genomics · phenomics · ecology · cancer biology

Author Information

Workshop CompBio (MSKCC)
Delasa Aghamirzaie (Illumina)
Alexander Anderson (Moffitt Cancer Center)
Elham Azizi (Columbia University)
Abdoulaye Baniré Diallo (Université du Québec à Montréal)
Cassandra Burdziak (Memorial Sloan Kettering Cancer Center)
Jill Gallaher (Moffitt Cancer Center)
Anshul Kundaje (Stanford University)
Dana Pe'er (Sloan Kettering Institute)
Sandhya Prabhakaran (Moffitt Cancer Centre)
Amine Remita (Bioinfo-UQAM | Université du Québec à Montréal)
Mark Robertson-Tessi (Moffitt Cancer Cente)
Wesley Tansey (columbia university)
Julia Vogt (ETH Zuerich)
Yubin Xie (Memorial Sloan Kettering Cancer Centre)

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