Helen Zhou
hlzhou [at] andrew.cmu.edu
I am a Ph.D. student in the Machine Learning Department at CMU, advised by Zachary Lipton. My work is generously supported by the Paul and Daisy Soros Fellowship for New Americans (2019-21) and the NSF Graduate Research Fellowship Program (2019-23).
I am interested in topics at the intersection of machine learning and healthcare, such as time series, multi-task learning, knowledge graphs, and causality, with the goal of developing personalized, accurate, and reliable models to assist with clinical decision-making.
Prior to CMU, I completed my masters of engineering (M.Eng.) degree at MIT, advised by David Sontag in the Clinical Machine Learning research group. In my undergraduate years, I researched at the MIT Media Lab with Soroush Vosoughi and Deb Roy in the Laboratory for Social Machines, and collaborated with Scott Greenwald and Pattie Maes in the Fluid Interfaces Group.
Projects
To assist clinicians in the empiric antibiotic treatment setting, we create predictive models for antibiotic resistence. Using these predictions, we employ a clinical decision-making algorithm and compare against rates of inappropriate antibiotic therapy and broad spectrum (2nd line) prescriptions in clinical practice.
Last summer, I worked within Amazon Product Search, on the Digital Relevance Ranking team. My intern project was to universalize Kindle relevance ranking models.
In my senior year, I started a new project at Professor Deb Roy's Laboratory for Social Machines (LSM). Using Target food data, I analyzed co-occurrences of food purchases.
While advanced VR headset technologies using IR sensors are quite precise, we wanted to see if we could accurately estimate gaze based simply off of an image of the eyeball. Last summer, I gave a talk at the European Conference on Eye Movements (ECEM).
Working on the Google Cardboard SDK team within Google Daydream, I created an over-the-air firmware update process to allow the Daydream controller to update its firmware from information sent by a Daydream-enabled phone.
I really enjoyed 6.141, Robotics Science and Systems. Working with my team, at the end of the semester we raced our robot through the tunnels of MIT.
As a software engineering intern, I worked on gamification of tasks important to individuals with autism, such as maintaining eye contact and understanding emotions. Technologies included OpenCV and Java.
App to save special moments for a rainy day. After winning an honorable mention at Greylock Hackfest 2015, my roommates and I published our app in the app store. (4.5 star rating, 1000-5000 installs)
Working in the Laboratory for Social Machines, my postdoctoral mentor Dr. Soroush Vosoughi and I used temporal and linguistic models to link user profiles across different social media platforms. Published in SocInfo'15.
To assist Wi-Fi tests, I created an analytics website to help test engineers quickly evaluate the state of their machines.
For our mobile development class 21W.789, we created an Android app that allows users to create and go on scavenger hunts.
As part of an iOS game development competition, I worked with a friend to create a 2-player make-3 game (think Bejeweled or Candy Crush). Make combos to send your opponent an unexpected twist!
Over my freshman year summer, I explored many classifiers and features to predict the sentiment of tweets. Ultimately, we found that context (time of day, location) proved quite valuable. Published in EMNLP.
My roommate and I created a trash-to-treasure website, where users could post their unwanted items and others could claim them.
Classes
school
Coursework
(G = graduate, H = header/ advanced, U = undergraduate)
In my undergraduate and M.Eng. career at MIT, I've taken a lot of classes. Below are some of my favorite.
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Advanced Natural Language Processing (6.864)
Fall 2016
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Advances in Computer Vision (6.819)
Fall 2015
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Machine Learning (6.867)
Fall 2016
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Signals, Systems, and Inference (6.011)
Spring 2017
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Biomedical Computing (6.872)
Fall 2017
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Robotics Science and Systems I (6.141)
Spring 2016
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Design and Analysis of Algorithms (6.046)
Fall 2015
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Database Systems (6.830)
Fall 2017
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Network and Computer Security (6.857)
Spring 2016
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Computer System Engineering (6.033)
Spring 2016
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Networks (14.15)
Spring 2016
group
Teaching
(TA = teaching assistant, LA = lab assistant, O = other)
Throughout the years, I've also enjoyed serving as a course assistant for many classes.
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Intro to Machine Learning (6.036) TA
Fall 2017, Spring 2017
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Intro to Deep Learning (6.S191) TA
IAP (January) 2017
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Intro to EECS II (6.02) Head Grader
Fall 2016
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Design and Analysis of Algorithms (6.046) HKN Tutor
Spring 2016
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Computation Structures (6.004) LA
Fall 2015
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Intro to Algorithms (6.006) HKN Tutor
Spring 2015 - Fall 2015
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Mathematics for Computer Science (6.042) HKN Tutor
Fall 2014 - Spring 2015
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Intro to EECS I (6.01) LA
Fall 2014
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Multivariable Calculus (18.02) TA
Fall 2014
Service / Hobbies
MIT Eta Kappa Nu (HKN) is our EECS honor society/ service organization. As Internal Relations Chair last year, I started our blog and wrote about our service efforts throughout the department. As Tutoring Chair this year, I lead a service with hundreds of tutors and tutees.
In junior year, I served as webmaster in the inaugural MIT IEEE Undergraduate Research and Technology Conference. In senior year, I worked with my co-chair to coordinate all aspects of the conference. This year, I serve as an alumni advisor for the new undergraduates in the conference committee.
I love long-distance running. It's a refreshing way to start the day, and great time to catch up on podcasts!
Rock climbing is always a blast. Every problem presents a fun puzzle to tackle, and it's a great balance between mind and body.
I think the world is beautiful, and that well over a thousand words are needed to describe it's elegance. As I move forward in life, I hope to continue to capture snapshots of treasured moments that will last a lifetime.