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Coffee break and Poster Session I
Nishith Khandwala · Steve Gallant · Gregory Way · Aniruddh Raghu · Li Shen · Aydan Gasimova · Alican Bozkurt · William Boag · Daniel Lopez-Martinez · Ulrich Bodenhofer · Samaneh Nasiri GhoshehBolagh · Michelle Guo · Christoph Kurz · Kirubin Pillay · Kimis Perros · George H Chen · Alexandre Yahi · Madhumita Sushil · Sanjay Purushotham · Elena Tutubalina · Tejpal Virdi · Marc-Andre Schulz · Samuel Weisenthal · Bharat Srikishan · Petar Veličković · Kartik Ahuja · Andrew Miller · Erin Craig · Disi Ji · Filip Dabek · Chloé Pou-Prom · Hejia Zhang · Janani Kalyanam · Wei-Hung Weng · Harish Bhat · Hugh Chen · Simon Kohl · Mingwu Gao · Tingting Zhu · Ming-Zher Poh · Iñigo Urteaga · Antoine Honoré · Alessandro De Palma · Maruan Al-Shedivat · Pranav Rajpurkar · Matthew McDermott · Vincent Chen · Yanan Sui · Yun-Geun Lee · Li-Fang Cheng · Chen Fang · Sibt ul Hussain · Cesare Furlanello · Zeev Waks · Hiba Chougrad · Hedvig Kjellstrom · Finale Doshi-Velez · Wolfgang Fruehwirt · Yanqing Zhang · Lily Hu · Junfang Chen · Sunho Park · Gatis Mikelsons · Jumana Dakka · Stephanie Hyland · yann chevaleyre · Hyunwoo Lee · Xavier Giro-i-Nieto · David Kale · Michael Hughes · Gabriel Erion · Rishab Mehra · William Zame · Stojan Trajanovski · Prithwish Chakraborty · Kelly Peterson · Muktabh Mayank Srivastava · Amy Jin · Heliodoro Tejeda Lemus · Priyadip Ray · Tamas Madl · Joseph Futoma · Enhao Gong · Syed Rameel Ahmad · Eric Lei · Ferdinand Legros

Fri Dec 08 10:20 AM -- 10:50 AM (PST) @
in Machine Learning for Health (ML4H) - What Parts of Healthcare are Ripe for Disruption by Machine Learning Right Now? »

Author Information

Nishith Khandwala (Stanford University)
Steve Gallant (MultiModel Research)
Gregory Way (University of Pennsylvania)
Aniruddh Raghu (Massachusetts Institute of Technology)
Li Shen (Icahn School of Medicine at Mount Sinai, ML/DL in Med Img and Bioinfo)
Aydan Gasimova (Imperial College London)
Alican Bozkurt (Northeastern University)
William Boag (MIT)
Daniel Lopez-Martinez (Massachusetts Institute of Technology)

Daniel Lopez Martinez is a researcher at the Harvard-MIT Division of Health Sciences and Technology and the MIT Media Lab, currently pursuing a PhD in Medical Engineering and Medical Physics under the supervision of Prof Rosalind Picard. Prior to joining Harvard and MIT, Daniel completed bachelor and master degrees in Biomedical Engineering at Imperial College London, where he was awarded the Medal for Excellence of the Faculty of Engineering. During his undergraduate degrees, he was an Amgen Scholar at the University of Cambridge and participated in research internships at the University of Oxford, Massachusetts Institute of Technology, Cancer Research UK Cambridge Institute and Harvard University. He also participated in the Bioscience Enterprise program at the University of Cambridge. Outside the lab, Daniel enjoys entrepreneurship and investing. He has co-founded several start-ups in the digital health and computer vision spaces, and is a part-time student at the MIT Sloan School of Management and Harvard Business School.

Ulrich Bodenhofer (QUOMATIC.AI)
Samaneh Nasiri GhoshehBolagh (Emory University)
Michelle Guo (Stanford University)
Christoph Kurz (Helmholtz Zentrum München)
Kirubin Pillay (University of Oxford)
Kimis Perros (Georgia Tech)
George H Chen (Carnegie Mellon University)

George Chen is an assistant professor of information systems at Carnegie Mellon University. He works on nonparametric prediction methods, applied to healthcare and sustainable development. He received his PhD from MIT in Electrical Engineering and Computer Science.

Alexandre Yahi (Columbia University)
Madhumita Sushil (Antwerp University Hospital; University of Antwerp)
Sanjay Purushotham (University of Maryland Baltimore County)
Elena Tutubalina (Kazan Federal University \\ Samsung-PDMI Joint AI Center, PDMI RAS \\ Neuromation)
Tejpal Virdi (Henry M. Gunn High School)
Marc-Andre Schulz (RWTH Aachen University)
Samuel Weisenthal (University of Rochester School of Medicine and Dentistry)
Bharat Srikishan (Columbia University)
Petar Veličković (University of Cambridge)
Kartik Ahuja (University of California, Los Angeles)
Andrew Miller (Columbia)
Erin Craig (Florence A. Rothman Institute)
Disi Ji (UC, Irvine)
Filip Dabek (National Intrepid Center of Excellence (NICoE), Walter Reed National Military Medical Center Bethesda, MD)

Data Scientist at NICoE, Walter Reed Bethesda. PhD Student at UMBC. Interested in machine learning and visualization.

Chloé Pou-Prom (LKS-CHART)
Hejia Zhang (Princeton University)
Janani Kalyanam (University of California, San Diego)
Wei-Hung Weng (Massachusetts Institute of Technology)
Harish Bhat (University of California, Merced)
Hugh Chen (University of Washington)
Simon Kohl (German Cancer Research Center (DKFZ))
Mingwu Gao (Michigan State)
Tingting Zhu (University of Oxford)
Ming-Zher Poh (Cardiio, Inc.)
Iñigo Urteaga (Columbia University)

I am an Associate Research Scientist in the Applied Math department at Columbia University and the Data Science Institute. I have specialized in statistical data processing, Bayesian Theory and approximate (Monte Carlo and Variational) inference methods. I am currently working on descriptive, predictive, and prescriptive modeling for electronic health records

Antoine Honoré (KTH, Royal Institute of Technology)
Alessandro De Palma (Massachusetts Institute of Technology)
Maruan Al-Shedivat (Carnegie Mellon University)
Pranav Rajpurkar (Stanford University)
Matthew McDermott (MIT)
Vincent Chen (Stanford University)
Yanan Sui (California Institute of Technology)
Yun-Geun Lee (Naver)
Li-Fang Cheng (Princeton University)
Chen Fang (Florida International University)
Sibt ul Hussain (Automotive Artificial Intelligence National University of Computer & Emerging Sciences)
Cesare Furlanello (FBK)
Zeev Waks (Intel Corporaiton)
Hiba Chougrad (UNIVERSITY CHOUAIB DOUKKALI)
Hedvig Kjellstrom (KTH Royal Institute of Technology)
Finale Doshi-Velez (Harvard)
Wolfgang Fruehwirt (Medical University of Vienna & University of Oxford)
Yanqing Zhang (Georgia State University)
Lily Hu (Salesforce Research)
Junfang Chen (Heidelberg University)
Sunho Park (Cleveland Clinic)
Gatis Mikelsons (University of Oxford)
Jumana Dakka (Rutgers University)

Interested in fMRI deep learning

Stephanie Hyland (ETH Zurich/Cornell)
yann chevaleyre (University of Paris Dauphine)
Hyunwoo Lee (Samsung Electronics Co., Ltd.)
Xavier Giro-i-Nieto (UPC Barcelona)

Xavier Giro-i-Nieto is an associate professor at the Universitat Politecnica de Catalunya (UPC). He graduated in Electrical Engineering studies at ETSETB (UPC) in 2000, after completing his master thesis on image compression at the Vrije Universiteit in Brussels (VUB) under the direction of Professor Peter Schelkens. In 2001 he worked in the digital television group of Sony Brussels, before returning to Barcelona and joining the Image Processing Group at the UPC. Since 2003, he has created and taught graduate and undergraduate courses for Electrical Engineering degress at the ESEIAAT and ETSETB schools from UPC. In 2013 he participated in the design of the Master in Computer Vision of Barcelona by UPC, UAB, UPF and UOC universities, where he lectures on deep learning, image retrieval and video processingl. He has taught several international courses in the framework of the European Erasmus program. He obtained his Phd on image retrieval in 2012, under the supervision by Professor Ferran Marqués from UPC and Professor Shih-Fu Chang from Columbia University. He was a visiting scholar during Summers 2008 to 2014 at the Digital Video and MultiMedia laboratory at Columbia University, in New York. His relation with industry includes collaborations with Mediapro, Catalan Broadcast Corporation (TV3), Pixable, Catchoom and Narrative.

David Kale (University of Southern California)
Michael Hughes (Tufts University)
Gabriel Erion (University of Washington)
Rishab Mehra (Stanford Vision Lab)
William Zame (UCLA)
Stojan Trajanovski (Philips Research)

I am a scientist in Philips Research, working on deep learning projects. I am also a visiting researcher at Delft University of Technology (TU Delft), The Netherlands, where I obtained my PhD degree with cum laude. My research focuses are network science, complex networks, game theory, algorithms and machine learning. I graduated with distinction from the Master program in Computer Science at the University of Cambridge, UK. Even before, I won a bronze medal at the International Math Olympiad.

Prithwish Chakraborty (IBM Watson Health)
Kelly Peterson (Massachusetts Institute of Technology)
Muktabh Mayank Srivastava (ParallelDots, Inc.)
Amy Jin (Stanford University)
Heliodoro Tejeda Lemus (Stanford University)
Priyadip Ray (Lawrence Livermore National Laboratory)
Tamas Madl (University of Manchester)
Joseph Futoma (Harvard University)
Enhao Gong (Stanford University, Subtle Medical)

PhD Candidate in EE at Stanford. Founder of Subtle Medical and Polarr. Focus on Deep Learning based image processing and medical imaging technologies.

Syed Rameel Ahmad (MTBC)
Eric Lei (Carnegie Mellon University)
Ferdinand Legros (Stanford University)

2017 - Present: Research Assistant in the Stanford Vision Lab. Submitted to CVPR 2018, Visual attention models, Professor Silvio Savarese. 2016 - Present: Research Assistant in Mobilize Center. Submitted to NIPS Symposium on Interpretable Machine Learning 2018, Bayesian Networks for Healthcare. Professor Scott L. Delp. 2016 - Present: Graduate Student at Stanford, Computer Science track of MS&E. 2013-2016: MEng in CS and Applied Mathematics, Ecole Polytechnique, France

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