My name is Alex. I am a PhD student at NYU studying computer science, focusing on machine learning for natural language and vision. I am advised by Professors Kyunghyun Cho and Sam Bowman. I graduated from Harvard University with a bachelor’s in applied mathematics and a master’s in computer science.
A sketch of my professional experience; see LinkedIn for more details.
- Head teaching fellow for CS 134: Networks, taught by Professor Yaron Singer. Spring 2017.
- Research intern with Professor Jure Leskovec and Will Hamilton through the Center for the Study of Language and Information, Stanford University. Published “Learning Linguistic Descriptors of User Roles in Online Communities” to NLP+CSS at EMNLP 2016. Summer 2016.
- Teaching fellow for CS 136: Economics and Computation, taught by Professor David Parkes. Spring 2016.
- Teaching fellow for CS 134: Networks, taught by Professors Yaron Singer and Ben Gollub. Fall 2015.
- Intern at Microsoft. Published an R package to programmatically access Microsoft Azure Machine Learning (more info). Summer 2015.
- Machine Learning: CS 229r (Information Theory in Computer Science), CS 287 (Statistical Natural Language Processing), CS 281 (Advanced Machine Learning), CS 283 (Computer Vision), CS 181 (Machine Learning)
- Computer Science: CS 263 (Systems Security), CS 186 (Economics and Computation), CS 124 (Data Structures and Algorithms), CS 61 (Systems Programming and Machine Organization), CS 51 (Intro to Computer Science II), CS 50 (Intro to Computer Science I)
- Statistics: STAT 210 (Probability I), STAT 110 (Introduction to Probability)
- Mathematics: AM 221 (Advanced Optimization), MATH 122 (Algebra I: Theory of Groups and Vector Spaces), MATH 23A (Linear Algebra and Real Analysis I), MATH 23B (Linear Algebra and Real Analysis II)
- Economics: ECON 1338 (Inequality and Poverty), ECON 1052 (Game Theory and Economic Applications), ECON 1011b (Macroeconomic Theory), ECON 1010a (Microeconomic Theory), FRSEMR 40K (Health Care on Less Than 8000 Dollars a Year)
- A Neural Framework for One-Shot Learning: thorough examination in the use of matching networks, a neural network and nonparametric model hybrid, for one-shot learning in various settings. See paper for more details. Completed for my senior thesis, earning high honors. I was advised by Professor Alexander Rush, whom I was fortunate to be mentored by for several semesters.
- Learning Linguistic Descriptors of User Roles in Online Communities: recurrent neural network model for unsupervised learning of descriptors of social interactions on online communities such as Reddit based of user comments. See paper for details.
- Traffic Swarm Optimization: investigation in the use of swarm optimization methods for optimizing traffic light cycles. For more info see this article or this writeup. Made for AM 221.
- Gaussian Processes for Crime Prediction: an exploration into the use of Gaussian processes to predict future crime rates in cities. See the writeup for details. Made for CS 281.
- Twitter Plays Chess: crowdsourced chess playing against an AI where users vote for the human team’s next move via Twitter, à la Twitch Plays Pokemon. Made for CS 186.