Please review below our invited speakers who will be presenting as part of the Industry Track at ICHI 2018. We think this remarkable set of speakers will inspire you in your respective work!
Mamta Parakh, Product Director - Algorithms, Quartet Health
Leads strategy and development of Quartet's machine learning platform and recommendation services. She heads a team of talented data scientists and machine learning engineers dedicated to bridging the gap between physical and mental health care. Her team utilizes expert clinical input, claims, and point of care data to develop models that detect underlying mental health needs and generate care recommendations for providers and patients. Previously, Mamta led business development and pre-launch market operations for Quartet in the Pacific Northwest. Early in her career, Mamta was a management consultant in the life sciences sector, developing expertise in forecasting, patient and provider segmentation, drug pipeline decision analytics. She holds an M.S. in Management Science and Engineering from Stanford University.
David Wennberg, MD, MPH, Chief Science Officer, Quartet
Leads the Data Science and Business Development functions at Quartet, a New York-based technology company transforming the way mental health is delivered, by making it more accessible and integrated into primary care. David previously served as the Chief Executive Officer of the Northern New England Accountable Care Collaborative (NNEACC), and as the Chief Executive Officer of the High Value Health Collaborative at The Dartmouth Institute. A co-founder of Health Dialog Analytic Solutions, the analytic division of Health Dialog, David served as Health Dialog’s Chief Science Officer. David received his MD from McGill University and MPH from the Harvard School of Public Health, and is a member of the Dartmouth Institute for Health Policy and Clinical Practice faculty.
Graph-based Analytics for Historical, Unstructured Medical Data
Graph Analytics has long been used in financial and social engineering for insight discoveries and specific solution recommendations. Example use cases include anti-money laundering, cybersecurity monitoring and insurance recommendation. Graph algorithms such as Page Rank, Collaborative Filtering and Community Detection have been proven effective in discovering correlations, causations and solutions in industry-specific problems. The medical industry has gathered tremendous data over the years, with different formats such as time series data, written texts, to high-definition images. While the analysis of these data could lead to useful insights, the lack of interoperability presents a challenge to traditional information processing. In this work, we demonstrate the Graphen Ardi Platform, which combines a scalable graph database, a high-performance graph analytic engine and a cognitive user interface, to uncover interesting relationships in medical data that led to effective solutions for the industry.
Ching-Yung Lin, PhD
Dr. Ching-Yung Lin is the CEO of Graphen, Inc., a startup company dedicated to developing next-generation Artificial Intelligence technologies, especially for novel solutions in the Financial Services industry and the Healthcare industry. Before June 2017, He was the IBM Chief Scientist of Graph Computing, and an IBM Distinguished Researcher. He led the Network Science and Machine Intelligence Department in IBM T. J. Watson Research Center. He is also an Affiliate Professor at the University of Washington 2003-2009, an Adjunct Professor at NYU in 2014, and has been an Adjunct Professor at Columbia University since 2005.
Dr. Lin was elevated to IEEE Fellow in Nov 2011, the first IEEE Fellow in the area of Network Science. He is an author of 180+ publications and 30+ awarded patents. Inspired by human’s brain structure of billions to trillions of nodes and edges, hIs research interest has been on fundamental issues of full brain functioning via creating novel graph platform. He led a team of ~40 researchers from Columbia University, CMU, Northeastern Univ., Northwestern Univ., UC Berkeley, Stanford Research Institute, Rutgers Univ., Univ. of Minnesota, and NMU in the then largest US social media analysis research project from 2012 to 2015. He also led a pioneering project on predicting human behavior for cognition. In 2010, IBM Exploratory Research Career Review selected Dr. Lin as one of the five researchers "most likely to have the greatest scientific impact for IBM and the world.” His “Big Data Analytics” course in Columbia University attracts more than 300 graduate students per year, and is the Top 1 search result of Baidu search on Big Data Analytics.
In 2015, he was invited as a panelist by the American Medical Association, together with the White House Chief Data Scientist, to discuss the impact of Big Data in Healthcare. He was the founding steering committee chair of the ACM SIG Health Informatics IHI 2010-2012. He was invited as a keynote or plenary speaker in 20+ conferences, including the International Conference on Cybersecurity hosted by FBI in 2016 and the Expo 2.0 in New York Javits Convention Center. His work won 7 best paper awards, shown in 100+ press releases, and was featured 4 times by the BusinessWeek magazine, including being the Top Story of the Week in May 2009.