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Coffee break and Poster Session II
Mohamed Kane · Albert Haque · Vagelis Papalexakis · John Guibas · Peter Li · Carlos Arias · Eric Nalisnick · Padhraic Smyth · Frank Rudzicz · Xia Zhu · Theodore Willke · Noemie Elhadad · Hans Raffauf · Harini Suresh · Paroma Varma · Yisong Yue · Ognjen (Oggi) Rudovic · Luca Foschini · Syed Rameel Ahmad · Hasham ul Haq · Valerio Maggio · Giuseppe Jurman · Sonali Parbhoo · Pouya Bashivan · Jyoti Islam · Mirco Musolesi · Chris Wu · Alexander Ratner · Jared Dunnmon · Cristóbal Esteban · Aram Galstyan · Greg Ver Steeg · Hrant Khachatrian · Marc Górriz · Mihaela van der Schaar · Anton Nemchenko · Manasi Patwardhan · Tanay Tandon

Author Information

Mohamed Kane (Massachusetts Institute of Technology)
Albert Haque (Stanford University)
Vagelis Papalexakis (University of California Riverside)
John Guibas (Henry M. Gunn High School)
Peter Li (Henry M. Gunn High School)
Carlos Arias (FAR Institute)
Eric Nalisnick (University of Cambridge)
Padhraic Smyth (University of California, Irvine)
Frank Rudzicz (University of Toronto)
Xia Zhu (Intel Corporation)
Theodore Willke (Intel Corporation)
Noemie Elhadad (Columbia University)
Hans Raffauf (Clue by BioWink GmbH)

Hans Raffauf is the co-founder and COO of Clue, the world’s fastest growing female health app. Clue has more than five million active users in over 190 countries, and is one of the most popular apps in the “Health & Fitness” category in the United States, Germany, the UK, Brazil, France, Mexico and many others. Clue’s mission is to help people all around the world benefit from insights into female health. A lifelong entrepreneur, Hans is convinced that technology will profoundly change the future of family planning.

Harini Suresh (MIT)

Harini is a student at MIT in CSAIL (Computer Science and Artificial Intelligence Laboratory), pursuing a Master of Engineering degree in Computer Science. She received her Bachelor's degree in Computer Science from MIT as well. She is interested in what machine learning can do to improve health and medicine, and particularly in the application of deep neural networks to clinical time series data. Her current research in the Clinical Decision Making group at MIT (under Pete Szolovits) aims to use deep autoencoders to uncover latent patient phenotypes, and use these in a recurrent LSTM neural network to predict mortality and intervention onset/duration. Her past research in the Computational Biophysics Group at MIT also utilized clinical data to make mortality predictions, and explored the question of how selecting and engineering various features affected prediction performance.

Paroma Varma (Stanford University)
Yisong Yue (Caltech)
Ognjen (Oggi) Rudovic (MIT)
Luca Foschini (Evidation Health)
Syed Rameel Ahmad (MTBC)
Hasham ul Haq (MTBC)
Valerio Maggio (FBK)
Giuseppe Jurman (FBK)

Giuseppe Jurman is a mathematician, with a PhD in Algebra, working at MPBA on various aspects of computational biology. His main research interests are statistical machine learning, mathematical modelling for high-throughput data and network analysis. He is also an expert in scientific programming with Python and other computing languages.

Sonali Parbhoo (University of Basel)
Pouya Bashivan (MIT)
Jyoti Islam (Georgia State University)
Mirco Musolesi (University College London)

Professor of Computer Science at University College London.

Chris Wu (Athelas)
Alexander Ratner (Stanford)
Jared Dunnmon (Stanford)
Cristóbal Esteban (EHT Zurich)
Aram Galstyan (USC Information Sciences Inst)
Greg Ver Steeg (University of Southern California)
Hrant Khachatrian (YerevaNN)
Marc Górriz (Universitat Politecnica de Catalunya (UPC))
Mihaela van der Schaar (UCLA and Oxford University)
Anton Nemchenko (UCLA)
Manasi Patwardhan (TCS Research)
Tanay Tandon (Athelas Inc.)

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