Blog posts

2018

Humans Especially Encourage To Apply: Why You Should Not Be Afraid Of Robots

33 minute read

As a new PhD student, starting at a new university, in a new city, in a new country, I’ve found myself introducing my work to many new people lately. I have worked in and (plan to, remember, just started) study machine learning for social and emotional interactions in robots. I’ve experimented with many ways to introduce this topic: “emotional intelligence, but for robots,” “social robotics,” “machine learning for robotic emotions.” Try as I might, I always get some flavor of this response:

Concrete Examples.

15 minute read

“Women are socialized to…”

I’ve had many friends basically say they don’t believe “women are raised to…” and use this skepticism to put the burden of gender inequality on women. Here are some concrete examples I can think of that support the idea that, currently, women are brought up in society to…

2017

Graduate School Dreams

5 minute read

An honest, cheeky, unfiltered brain dump of why I’m ready to go back. Partially an exercise to aid writing my statement of purpose, maybe somebody else can solidify

Dev Chat Interview

9 minute read

A chat for my friends’ blog series, reposted from original found here

2016

Paradox of Awareness

6 minute read

Being a woman is really, really weird. As, I assume, being a man can be really, really weird. But I put forth the idea that being a woman leads to a constant rollercoaster of crazy second-guessing and walking a stupidly fine line between “being assertive” and “playing the victim.”

2015

Deep Learning, Evolution, and Why Intelligence is not (just) Recognition

14 minute read

There has been a lot of talk recently about Deep Learning. Namely, how its recent resurgence is kicking ass across the board on machine learning benchmarks left and right. At the 2010 (and 2012) ImageNet Large Scale Image Recognition Competition, a group from University of Toronto, led by Geoffrey Hinton, built a neural net which outperformed the competition by 10% reduction in classification error rate (misrecognizing an image, so saying a picture that is in fact of a magnifying glass is a photo of scissors). This essentially brought neural networks back into play for the field of computer vision, where it dominates what most of us consider to be the coolest latest technology. Facebook’s face recognition? Neural network. Google’s self-driving cars? Controlled by neural nets. The tempting logical jump to make here is: artificial intelligence? Let’s just use a neural net!

2014