Machine Learning Conference

Presenting the latest advances from Virginia’s academics, government agencies, and startups

Thursday
April 13

1pm – 5pm

Violet Crown Cinema
200 W Main St

 

Virginia and Charlottesville have seen a blossoming of exciting machine learning work emerging from academia, startups and government endeavours. This one-day event will highlight novel and applied machine learning research that brings together this growing community.

TICKETS


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PROGRAM

KEYNOTES

The conference’s emphasis is on advancing the understanding of practical issues of applying data science and machine learning techniques to real world problems. Presentations will describe the implementations of solutions and systems for practical tasks in data science and applied machine learning.

 

  • Doug Bryan, VP of Foundational Data Products, Merkle: 1:05PM
    Looking for a Boost?  XGBoost Performance for Customer Look-alike Models
  • Taryn Price and Courtney Shindeldecker, Data Scientists, CCRi: 3PM
    Learn about Your Location (Using ALL Your Data)

FLASH TALKS

A series of rapid fire talks will highlight the strides being made in data science and specifically with machine learning.

  • 1:40PM – Andrew Montalenti, CTO, Parse.ly
    Predicting Internet Attention
  • 2:00PM – Colin Cassady, M.S. Student, UVA Data Science Institute
    Leveraging Machine Vision to Predict Entrée Composition
  • 2:20PM – Dr. Andrew Fast, Chief Scientist, Elder Research
    Using Data Science to Ask Why: A brief introduction to Causal Modeling
  • 3:30PM – Dr. Hongning Wang, Assistant Professor, UVA
    Modeling Social Norms Evolution for Personalized Sentiment Classification
  • 3:50PM – Eileen Krepkovich, Biomedical Engineer, Barron Associates
    Helping People Walk: Modeling Energy Expenditure with Prosthetic-Integrated Sensors
  • 4:10PM – Chandan Singh, Ph.D. Candidate, UC Berkley
    Uncovering Brain Connections Underlying Autism via Graphic Models

Suggested Topics

  • Sensor Networks and IOT
  • Artificial neural networks, including deep learning
  • Design and analysis of algorithms
  • Unsupervised, semi-supervised, and active learning
  • Online learning
  • Learning with large-scale datasets
  • Climate Science
  • Political Science
  • Manufacturing and operations research
  • Satellite imagery and mapping
  • Healthcare

Format

15 Minute Topic Presentation, followed by 4 minute Q&A

Submit your presentation

Applications Due March 15th

Steering Committee

Michael Prichard– Founder, Metis Machine

Reginald Leonard – Assistant Director for Career Services, UVA Data Science Institute

Daniel Bailey– Founding Partner & CTO, Astraea

Patrick Harrison– Lead Data Scientist, S&P Global Market Intelligence

Paul Beyer – Director, Tom Tom Founders Festival

Sean Gorman – Product Manager, DigitalGlobe

Renee Teate– Data Scientist, HelioCampus

Tom Tom Founders Festival

 

After the conference, stay in town for Tom Tom events on Thursday evening– pub crawls, tech mixers, keynotes, concerts– continuing Friday and throughout the weekend.

See the Schedule

FOUNDING SPONSORS