Multiple Myeloma Collaborative Research Hackathon


Following our first biomedicine research event in June 2017, We are excited to announce the second event in our open collaborative research series. This event is focused on papillary renal-cell carcinoma type 1

In partnership with, we will invite 150 scientists and engineers to join us in San Francisco for an intense weekend of exploration in computational biomedicine. Interdisciplinary teams will work to further understand, develop potential interventions and advance the standard of care for p1RCC. This open research collaboration will use genomic datasets for p1RCC provided through the NIH Cancer Genome Atlas. 

Papillary renal-cell carcinoma, accounts for between 15 to 20% of all kidney cancers. It occurs in the cells lining the small tubules in the kidney that filter waste from the blood and make urine. Little is known about the genetic basis of sporadic papillary renal-cell carcinoma, and no effective forms of therapy for advanced disease exist.

 You will be able to follow the research projects at



  • Contribute to a real, ongoing patient case.
  • Advance research for rare kidney cancer.
  • Create intersectionality between computer scientists and biologists.
  • Develop new skills in computational biology and cancer genomics.
  • Continue building an open community for collaborative biomedicine research.



  • Create a pRCC clonal evolution model using sequencing info from individual pRCC cases.  Here's an similar model for chRCC.
  • Analyze the gene expression signature and come up with a treatment regimen. see here.



TCGA has authorized us to use their full Dataset.  They have two requirements.  First, we must list all event participants as collaborators in the project description we send to them.  So please let us know about your intent to participate as soon as possible.  Second, the participants must agree not to take the controlled access data home and further distribute it.

In addition, James Hsieh from the RCC Trial Consortium has pledged seven targeted exomes for the event.

Finally, SVAI is in discussion with several Sequencing companies to provide new personalized genomes of existing p1RCC patients.



  • Advanced learning in computational biology and cancer genomics.
  • Great mentoring sessions.
  • Make new friends.
  • Connect with us and our event partners.
  • Our first research event was amazing, and this one will be even better.



[PDF Link Coming]



We created a few slack channels for easy communication during the event Join: #SolveRKC or #RKC-remote. 

Join Our Slack Channel


Coming Soon - TBD.




Ben Busby, PhD

Computational Biology Branch, NCBI, NLM, NIH


Ben leads the NIH's efforts to partner with Genomics hackathons. His research interests include generation of clustering algorithms for analysis of large gene families and whole genomes and Phylomic Analysis of Gene Transfer Events. Ben holds a PhD in Biochemistry and Molecular Biology from University of Maryland, Baltimore.




Bill Paseman


Bill Paseman has been in Silicon Valley since 1980. He was the Founder and Chairman of Calico Commerce from 1994-2000 and currently focuses on Angel Investing through Paseman & Associates, and advancing rare kidney cancer research and patient advocacy  through

Twitter   LinkedIn   Personal Site

Onno Faber

Entrepreneur, NF2 Patient

Founder, NF2 Project

Onno is the Founder of NF2 Project. He previously founded several other startup companies (such as Tapstack), and now focuses full time on NF2 Project, a patient organization research and treatment options for Neurofibromatosis type 2. He will talk about his experience from the first SVAI research event. Onno has engaged in a life long pursuit of creating things and solving problems. He studied architecture, receiving his degree in 2006 ( honors).

 Twitter   LinkedIn

Pete Kane

Director, SVAI, Founder,

Peter has done a lot of work building healthcare and technology communities in Minnesota and the SF Bay Area. His academic background is Chinese Language and Literature.




Sean Davis


Bioinformatics and cancer researcher, pediatric oncologist, Bioconductor developer,

Twitter     LinkedIn

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Bharath Ramsundar

Stanford, UC Berkeley, DeepChem Author

Bharath Ramsundar received a BA and BS from UC Berkeley in EECS and Mathematics and was valedictorian of his graduating class in mathematics. He is currently a PhD student in computer science at Stanford University with the Pande group. His research focuses on the application of deep-learning to drug-discovery. In particular, Bharath is the creator and lead-developer of DeepChem, an open source package that aims to democratize the use of deep-learning in drug-discovery and quantum chemistry. He is supported by a Hertz Fellowship, the most selective graduate fellowship in the sciences.

Twitter   LinkedIn

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Clay Mellina

ML at Google Cloud


"My current interests are primarily in deep learning for computer vision, image search, and visual similarity search. I am also particularly interested - both from a research perspective as well as a productization perspective - in intelligent systems that allow users to express search intentions or information-needs in nuanced ways that are otherwise difficult to express by language or classical search tools." Clay complted his graduate studies at Stanford University with a dual focus in Human-Computer Interaction and Artificial Intelligence. Prior to joining Google, he worked on Computer Vision and Machine Learning Team at Yahoo on many topics, including scaling deep learning and computer vision technologies for Yahoo products, product integrations, large-scale approximate nearest neighbor search, deep learning for visual similarity search, and visualization tools.

LinkedIn   Twitter


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Keren Gu

Director at SVAI, ML Engineer at Sift Science

Keren is a Director at SVAI and Machine Learning Engineer at Sift Science, working with distributed machine learning algorithms and delivering real-time solutions to internet-fraud. She was part of the Interactive Robotics Group at MIT CSAIL where she worked to improve machine's ability to extract hierarchical structures from demonstrations of human team collaboration tasks. She graduated from MIT with degrees in Mathematics and EECS. She has also worked at Bloomberg, on distributed systems.

Twitter   LinkedIn



Avanti Shrikumar

Stanford, MIT

Avanti is a Ph.D student in the Department of Computer Science at Stanford, advised by Professor Anshul Kundaje. She has develop broadly-applicable methods to make deep learning models interpretable, and has applied these methods to study regulatory genomics. Avanti has a Bachelor's in Computer Science with Molecular Biology from MIT and spent a year working as a developer for the Healthcare team of Palantir Technologies before starting her PhD. Read more at Avanti's Stanford page.

Twitter   LinkedIn

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Ankita Das

Ankita specializes in studying Epigenetic mechanisms that regulate stem and progenitor cell differentiation during development. She has extensive experience in studying various vertebrate organisms including zebrafish and mice to study in vivo developmental processes, using imaging & genetic strategies. She is enthusiastic about entrepreneurship, and has designed a mentoring program serving Hopkins fellows considering careers in entrepreneurship / start-ups and venture capital strategists. She also serves on the board of Innovation Factory at JHU Carey School of Business to facilitate team building and peer mentoring between business school and science students interested in Entrepreneurship.




We'll introduce our mentors at the beginning of the event. When you have questions, reach out to them! They will around the event and you can reach them on slack as well.



The official event hashtag is: #SolvePRCC.

We will use Twitter for live announcements and updates from the event. Follow us at @SVAIresearch.



Join our FaceBook Group and share some photos of the event (In-person and remote). Our plan is to periodically live streaming short interviews and broadcasting what people are working on through Facebook. SVAI Facebook.



The opening and closing talks will be live streamed on SVAI's Youtube account.

  • Opening Talks: 
  • Closing Talks and Final Presentations:



We'd like to see submissions follow the same format as an (abbreviated) academic poster. Submissions are not restricted to this format and we encourage you to be as creative as you want. Push to Github.

  1. Introduction
  2. Purpose
  3. Approach
  4. Methods / Algorithms / Models
  5. Results and Discussion 



Each team or individual will have 5 Minutes to present what they worked on. Presentations will be fast! But don't worry, we will link submissions here afterwards so you can get a closer look at what everyone worked on.



Each presentation will be judged on the following criteria weighted in this order:

  1. How well does the solution lead to positive outcomes for Rare Kidney Cancer patient treatment?
  2. How novel is the approach to finding a solution?
  3. Quality and depth of the problem analysis.
  4. Team dynamics, diversity, and intersectionality including cross discipline and specialization collaboration.






Weekend Hackathon

(Not an overnight event)



Friday Night March 2nd

18.00: Doors Open

18.30: Welcome!


20.45: Objectives & Team Formation

23.00: Doors Close

Saturday March 3rd

9.00: Doors Open, Breakfast

10.00: Work


12.00: Lunch


15.00: Work

17.30: Dinner

23.00: Doors Close

Sunday March 4th

9.00: Doors Open, Breakfast

10.00: Work

12.00: Lunch

13.00: Work

15.30: Final Submissions

16.00: Presentations & Judging

18.00: Happy Hour, Celebrate!



This is a  technically intensive event, both from a computer science and bio / genomics perspective. Our target audience is Computer Scientists, AI/ML Researchers, Computational Biologists, Genomic Researchers. Students in any of these areas are especially encouraged to apply!









Reach out to learn more about all sponsorship opportunities at



Why are you doing this?

We think it's a good idea to bring together the smartest people in AI / ML, Biology and Genomics to hack on difficult medical problems.

Is this an overnight Hackathon?

Nope. We believe in healthy sleep.

Do I need to provide my own computational power?

No. Google has you covered. We will be issuing Google Cloud credits at the event.

Who is the target Audience?

Computer scientists, AI researchers, Computational Biologists and eager learners around the world.

Can I participate remotely?

Absolutely! Join here.

Will there be opportunities to continue collaborating on this project after the hackathon?





Standard Event Disclosures

We have a pretty thorough FAQ, please check it out here: FAQ


Our conference is dedicated to providing a harassment-free conference experience for everyone, regardless of gender, gender identity and expression, age, sexual orientation, disability, physical appearance, body size, race, ethnicity, religion (or lack thereof), or technology choices. We do not tolerate harassment of conference participants in any form. Sexual language and imagery is not appropriate for any conference venue, including talks, workshops, parties, Twitter and other online media. Conference participants violating these rules may be sanctioned or expelled from the conference without a refund at the discretion of the conference organizers. For full version, please see:


We take photos at our events. Some of these photos will be used on our website. We seek to respect your privacy and ask that if you do not want your photo to appear on SVAI to please email us.


By signing up for this event, you will automatically be added to future SVAI announcements.


We do not make announcements for non-SVAI events or conferences at our gatherings. Distribution of flyers, printed media or other non SVAI related materials is not allowed at our events. 


This gathering is limited to 150 people. You MUST be pre-registered to attend. Registration must include your First and Last name, and some of our venues require ID for entry. You do not need to print a paper ticket. We will be checking people in the building lobby. Questions or comments? Tweet to us @SVAIresearch.