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Medicine in Silico


Stanford Students in Biodesign's 2017 Conference

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Medicine in Silico


Stanford Students in Biodesign's 2017 Conference

Conference Overview

Learn about the latest research and technology in cutting-edge quantitative biomedicine. 
Topics range from automated diagnosis of macular degeneration to engineering of genetic circuits.

Date & Time: April 29, 9:30 AM - 4 PM
location: SHriram 104 Auditorium

REGISTER HERE

Questions? Email agchempa@stanford.edu


Schedule

9:30 AM

10:00 AM

10:15 AM

 

10:45 AM

 

11:15 AM

 

11:45 AM

12:30 PM

 

1:00 PM

 

1:30 PM

1:50 PM

 

2:20 PM

 

3:05 PM

3:30 PM

Conference Registration and Morning Coffee Reception

Opening Remarks by Augustine Chemparathy, Event Organizing Lead

Remarks by Professor Christina Curtis, PhD, MsC

“Quantifying the evolutionary dynamics of tumor evolution through spatial computational modeling”

Remarks by Professor Andreas Pfenning PhD

“A data-driven approach to understanding the genetic basis of Alzheimer's disease.”

Remarks by Professor James Zou PhD

"AI to read and write the human genome"

Catered lunch

Remarks by Dr. Mark DePristo, PhD

“Introduction and applications to next-generation sequencing and disease diagnostics”

Technology Demonstration by Athelas

"Athelas - Deep Learning for Decentralized Diagnostics"

Break and refreshments

Remarks by Professor Jennifer Elisseeff, PhD

“Designing from translation: how technology implementation births discovery”

Remarks by Professor Jose Gomez-Marquez

Affordable medical devices for developing countries

Closing remarks by Dean Lloyd Minor

Wrap-up

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Speakers


Speakers


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Professor Christina Curtis, PhD - Stanford University

Christina Curtis, PhD, MSc is an Assistant Professor of Medicine and Genetics in the School of Medicine at Stanford University and Co-Director of the Molecular Tumor Board at the Stanford Cancer Institute. Dr. Curtis’s laboratory couples innovative experimental approaches, high-throughput molecular profiling, and computational modeling to quantify the evolutionary dynamics of tumor progression and therapeutic resistance and to develop robust predictive and prognostic biomarkers. Her research has redefined the molecular map of breast cancer, revealing novel subgroups with distinct clinical outcomes. She also recently described a novel Big Bang model of colorectal tumor growth, challenging the universality of the de facto sequential clonal evolution model.

Curtis Lab

 
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Dr. Mark Depristo, PHD - Google Brain

Extensive industry experience coupled with depth of academic knowledge has propelled Dr. Mark Depristo to the head of the Google Brain Project, an initiative on developing large-scale deep learning software systems. Additionally, he works within Google Verily Life Sciences as a technical lead due to his expertise in computational biology, methods development, software engineering, and statistical data analysis. There, he is working on software tools to analyze life sciences data (genomics, devices, clinical records) to make medicine more proactive and less reactive.

 
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Professor Jennifer Elisseeff, PhD - Johns Hopkins University

Through her background in biomedical engineering and ingenuity, Dr. Jennifer Elisseeff has revolutionized the tissue and wound healing field. She has found numerous start-ups including Cartilix, a startup that translated adhesive and biomaterial technologies for treating orthopedic disease and Algeria Soft Tissue and Tissue Repair, which are startups focused on soft tissue regeneration and wound healing. She is currently the Jules Stein professor at the Wilmer Eye Institute and director of the Translational Tissue Engineering Center at John Hopkins and has won numerous awards in the past including Awards from the Arthritis Foundation and the Yasuda from the Society of Physical Regulation in Medicine and Biology.

Elisseeff Lab

 
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Professor José Gómez-Márquez - Massachusetts institute of technology

As the director of MIT’s Little Devices Lab, Jose Gomez-Marquez dives into designing medical devices for extreme affordability. His research projects run the gamut from inexpensive diagnostics to the MEDIKit platform, which aims to empower healthcare practitioners in developing countries to invent their own med-tech. A native of Honduras, Gomez-Marquez has won two Lemelson Awards for International Technology, has served as an expert advisor in the President’s Council of Advisors on Science and Technology, and has been named Humanitarian of the Year by Technology Review.

Little Devices Lab

 

 

Professor Andreas Pfenning, PhD - Carnegie Mellon University

Dr. Andreas R. Pfenning completed his BS in Computer Science at Carnegie Mellon University in 2006. He then went on to obtain his PhD in Computational Biology and Bioinformatics at Duke University. Pfenning is currently a postdoctoral associate with Prof. Manolis Kellis in the Computer Science and Artificial Intelligence Laboratory at the Massachusetts Institute of Technology, researching neural diseases. His goal is to build a set of computational and genomic tools to study how sequence differences in those regions influence neurons, neural circuits, disease predisposition, and behavior. Understanding the genetic mechanisms of neural function may enable identification of disease biomarkers and treatments, as well as provide insights into the evolutionary process that led to the human brain.

Pfenning Lab

 

Professor James Zou PhD - Stanford University

Dr. James Zou is an Assistant Professor of Biomedical Data Science, Computer Science (courtesy) and Electrical Engineering (courtesy) at Stanford University. He works on a wide range of problems in machine learning (from proving mathematical properties to designing new probabilistic models), and he is especially interested in applications to human genomics. Zou received his Ph.D. from Harvard University in May 2014 and was fortunate to be a member of Microsoft Research New England. Prior to that, he completed Part III in Mathematics at the University of Cambridge and was a Simons fellow at U.C. Berkeley. Zou joined Stanford in Fall 2016 and is excited to be an inaugural Chan-Zuckerberg Investigator.

Zou's Research