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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
About me
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Posts
Discrete and Continous-time Markov Chains
Published:
Discrete-time Markov Chain, Mover-Stayer Model, Continous-time Markov Chain, Poisson Process, Kolmogorov’s Differential Equations
An Example of Estimating ITT and LATE via Instrumental Variable
Published:
An example estimating the Intention-to-treat (ITT) effect and the Local Average Treatment Effect (LATE) of a public health policy.
Linear Regression and Regularization
Published:
Linear Regression, Non-linear Relationship, Bias-Variance Tradeoff, Regularization
Linear vs. Logistic Regression
Published:
Linear Regression, Logistic Regression, and their difference
courses
CSCI-UA 102 Data Structures
Term: Fall 2021
Instructor: Dr. Anasse Bari
Level: Undergraduate
CSCI-UA 201 Computer Systems Organization
Term: Fall 2022
Instructor: Dr. Hasan Aljabbouli
Level: Undergraduate
CSCI-UA 310 Basic Algorithms
Term: Summer 2022
Instructor: Dr. Areeba Ikram
Level: Undergraduate
CSCI-UA 473 Introduction to Machine Learning
Term: Fall 2022
Instructor: Dr. Lerrel Pinto
Level: Undergraduate
CSCI-UA 475 Predictive Analytics
Term: Summer 2023
Instructor: Dr. Anasse Bari
Level: Undergraduate
CSCI-UA 479 Data Management and Analysis
Term: Spring 2022
Instructor: Dr. Matthew Zeidenberg
Level: Undergraduate
DS-GA 3001 / MATH-GA 2840 Probability and Statistics 2
DS-GA 3001 Special Topics in Data Science:
MATH-GA 2840 Advanced Topics in Applied Math:
Probability and Statistics 2
DS-GA 3001 Modern Topics in Statistical Learning Theory
DS-GA 3001 Special Topics in Data Science:
Modern Topics in Statistical Learning Theory
DS-UA 112 Introduction to Data Science
Term: Spring 2021
Instructor: Dr. Pascal Wallisch
Level: Undergraduate
DS-UA 202 Responsible Data Science
Term: Spring 2023
Instructor: Dr. Elisha Cohen
Level: Undergraduate
DS-UA 301 Advanced Techniques in Machine Learning and Deep Learning
DS-UA 301 Advanced Topics in Data Science:
Advanced Techniques in Machine Learning and Deep Learning
DS-UA 9201 Causal Inference
Term: Fall 2022
Instructor: Dr. Judith Abécassis
Level: Undergraduate
MATH-GA 2840 Theory of Deep Learning
MATH-GA 2840 Advanced Topics in Applied Math:
Theory of Deep Learning
MATH-UA 120 Discrete Mathmetics
Term: Spring 2022
Instructor: Dr. Hasam Oveys
Level: Undergraduate
MATH-UA 123 Multivariable and Vector Calculus
Term: Fall 2022
Instructor: Dr. Daniel Stein
Level: Undergraduate
MATH-UA 140 Linear Algebra
Term: Fall 2021
Instructor: Dr. Simon Becker
Level: Undergraduate
MATH-UA 235 Probability and Statistics
Term: Spring 2022
Instructor: Dr. Antoine Cerfon
Level: Undergraduate
MATH-UA 325 Analysis
Term: Spring 2023
Instructor: Dr. Michal Shavit
Level: Undergraduate
STAT-UB 21 / STAT-GB 3321 Introduction to Stochastic Processes
Term: Spring 2023
Instructor: Dr. Halina Frydman
Level: Undergraduate / Graduate
STAT-UB 3 Regression and Forecasting Model
Term: Fall 2021
Instructor: Dr. Lucius Riccio
Level: Undergraduate
portfolio
Personalized Inteligence Mailbox Based on IoT
Report, Slides
A Personalized Inteligence Mailbox employing IoT techniques with Android app controlling through cloud communication.
Soccer Player Ratings
Slides, Video
A Regularized Adjusted Expected Goal Plus-Minus model(RAxGPM) in soccer to evaluate players’ performance.
Lip Reading Word Classification
Code, Slides
A CNN-LSTM based classifier model that takes a sequence of video frames as input and identifies the speaker’s words.
Fingertips Position Estimation of a Robot Hand
Code, Report, Video
A Convolutional Neural Network which takes the RGBD images of the robotic hand from three different views as input and returns the positions of each fingertip.
A Comparative Analysis of Collaborative Filtering Algorithms for Recommendation Systems
Report
Collaborative filtering (CF) is a widely used technique in Recommendation Systems (RS) that leverages the collective wisdom of users to make recommendations. In this work, we provide a comparative analysis of three prominent collaborative filtering algorithms: Matrix Factorization, Neighborhood Models, and emerging Neural Collaborative Filtering.
Calibrated NBA Win Probability Estimation
Report, Slides, Video
Trained Neural network and linear models to estimate in-game win probability of NBA using play-by-play data for both accuracy and calibration.
Technical Audit of Students’ Performance in Exams
Report, Slides, Video
A technical audit of an automated decision system (ADS) which implements machine learning models to predict student’s performance in exams to allocate extra study support accordingly.
Analyzing the Impact of Subway Major Incidents on Passenger Flows
Report
Modeling changes in subway passenger flows during major incidents using turnstile data to understand the impact on passenger dynamics within the network.
publications
Paper Title Number 1
Published in Journal 1, 2009
This paper is about the number 1. The number 2 is left for future work.
Recommended citation: Your Name, You. (2009). "Paper Title Number 1." Journal 1. 1(1). http://academicpages.github.io/files/paper1.pdf
Paper Title Number 2
Published in Journal 1, 2010
This paper is about the number 2. The number 3 is left for future work.
Recommended citation: Your Name, You. (2010). "Paper Title Number 2." Journal 1. 1(2). http://academicpages.github.io/files/paper2.pdf
Paper Title Number 3
Published in Journal 1, 2015
This paper is about the number 3. The number 4 is left for future work.
Recommended citation: Your Name, You. (2015). "Paper Title Number 3." Journal 1. 1(3). http://academicpages.github.io/files/paper3.pdf
talks
A RAPM Model for Soccer Player Ratings
Published:
teaching
CSCI-UA 0002 Introduction to Computer Programming (in Python)
Teaching Assistant, New York University, Department of Computer Science, Fall 2022
CSCI-UA 0002 Introduction to Computer Programming (in Python)
Teaching Assistant, New York University, Department of Computer Science, Spring 2023
DS-UA 201 Causal Inference
Teaching Assistant, New York University, Center for Data Science, Summer 2023
CSCI-UA 0002 Introduction to Computer Programming (in Python)
Teaching Assistant, New York University, Department of Computer Science, Fall 2023
DS-UA 301 Advanced Techniques in ML and Deep Learning
Teaching Assistant, New York University, Center for Data Science, Fall 2023