Introduction

From Amazon's recommender system to automated mail sorting, technologies using machine learning are increasingly prevalent in our day-to-day lives. Recent developments have enabled advances in fields as varied as personalized medicine, search engines, and robotics. At its core, machine learning is the science of managing information: finding patterns, building models, making decisions. In our current information age, machine learning is needed more than ever before.

Despite its growing importance, the percent of female researchers in machine learning remains low, the percent of minority women even lower. Most women interested in machine learning rarely get the chance to interact with other female researchers, making it easy to feel isolated and hard to find role models...

... but this workshop is not about grumbling! Male and female students alike often face questions of self-doubt and career-planning; our goal is to be a force of positive change, to invigorate -- or reinvigorate, as the case may be -- excitement in machine learning. In particular, we offer an opportunity for female students to:

  • one-to-one mentoring match up where participants can meet up with a mentor during a mutually convenient time
  • participate in career-focused panel discussions with senior women in industry and academia
  • present research in a friendly, positive environment while also providing critical feedback
  • hear technical presentations on the work of senior women in their field
  • network and exchange ideas with each other and senior female researchers

Students interested or curious about the field are welcome to attend. This year's workshop will be co-located with NIPS, a premier conference in machine learning and another opportunity to learn more about the field. Workshop registration is free.

Workshop Format

The one-day workshop will consist of talks by established researchers and graduate students, a poster session for graduate students to showcase their research, and a panel discussion to discuss careers in machine learning.

Workshop registration is free.

Organizers

The organizers for this year's workshop are Tamara Broderick, Tejaswini Narayanan, Pallika Kanani and Minmin Chen, with faculty advisor Raquel Urtasun.