Ashley Chien Email & Phone Number

Mountain View, Ca, Us

Berkeley, Ca, Us

I have worked on a variety of research projects during my time in Berkeley.In my junior year, I worked on medical machine learning research in Mofrad Lab, a bioengineering lab in Berkeley. The task was using computer vision to segment leaks of blood in CT scans of the body. I worked on the whole data pipeline including the labeling of the data, pre-processing the data, creating the model, and tuning the model. A U-Net achieved decent performance in terms of the metric IOU, but only when predicting on positive scans (those with a leak). We have also worked on adding a classification portion of the network to be able to make good predictions on negative scans.In my senior year, I worked briefly on a systems RL project working on database optimization using deep reinforcement learning.In my senior year, I also worked on a causal inference project. I helped write examples for a new causal inference package in Python which allows people to easily run causal inference algorithms on simulators.The summer after my senior year, I worked on a neural interpretability project. We investigated how probes could explain differences between the representations of various language models such as ELMo, BERT, RoBERTa, and GPT-2.

Berkeley, Ca, Us

I have been a TA at Berkeley for every semester since my summer after my freshman year. TAing includes teaching a section of undergraduates by mini-lecturing and walking through a worksheet for an hour period. Some classes also have a lab component, where students work on a programming assignment while TAs help explain and debug.I have taught 6 different classes in the 7 semesters that I taught. They are a mix of computer science, statistics, and data science courses.I have taught CS61A , which teaches Python, SQL, and Scheme, and important programming concepts, twice (Summer 2017 and Fall 2017). I also managed the tutors of the course over the summer.In Spring 2018, I taught the CS61B, the Berkeley data structures course.In Fall 2018, I taught Stat 140, a probability for data science course. In Spring 2019, I taught Data 100, "Principles of Data Science", which teaches important data science concepts such as EDA, visualization, pandas, and SQL, as well as some classical machine learning.In Fall 2020, I taught Stat 88, an introduction to probability for business and econ majors. I was a head TA and worked for 20 hours a week. My main responsibilities were updating the website, writing pedagogy guides for the other TAs, editing the homework, writing quiz questions, and handling logistics.In Spring 2020, I taught Data 102, a statistical learning class which touched on a variety of topics such as multiple hypothesis testing, Bayesian Hierarchical models, causal inference, reinforcement learning, and differential privacy. I primarily handled the logistics of the course, updated the website, and wrote exam questions.

San Francisco, Ca, Us

I worked on the computer vision project of scene classification on Airbnb photos (classifying whether an image is a bedroom, kitchen, ball, pit, …, etc.) and using these image confidences to improve other models that my team created. I investigated whether adding these image features would improve an XGBoost model and a simple neural network that were previously only using text data. I also tweaked the model architecture of the simple neural network to improve the F1 score by 3.5%.

I worked at a medical machine learning stealth startup. I have worked on using generative adversarial networks for anomaly detection, re-implementing a hemorrhage model involving ResNet-18 and a random forest, and writing regular expressions for parsing doctors' reports.

San Francisco, Ca, Us

Performs image processing and data analysis on bone scans on clinically important studiesexamining effects of various disorders on bones

Rutherford, New Jersey, Us

Taught students math and reading, experience with Excel entering grades.

Bachelor’S Degree, Computer Science And Statistics

Education record