About

I am a professor of electrical engineering at The Cooper Union

I teach courses and advise students in the area of signal processing, wireless communications and networks, machine learning and data science.

This website is meant to highlight all the great things Cooper students are doing under my supervision in these areas.

My Google Scholar profile

My cv

Masters Theses

One of the most rewarding aspects of being a professor is advising Masters Theses. There is nothing better than working closely with smart people towards a shared goal. Here’s a list of all the theses I’ve advised:

Predicting Isotopologue Counts from Bulk Metabolomics Data, Ravindra Bisram

Applying a Bayesian Structural Time Series Model to Infer Causal Impact in the Crypto Market, Philip Blumin

Graph Machine Learning with Scattering Transforms, Armaan Kohli

Improving Semantic Water Segmentation by Fusing Sentinel-1 Intensity and Interferometric Synthetic Aperture Radar (InSAR) Coherence Data, Ernesto Colon

Method to Impute Missing Features in Metabolomics Data using Rank-Transformation and Matrix Factorization, Sophie Jaro

Deep Learning Pipeline for Detection of Mild Cognitive Impairment from Unstructured Long Form Clinical Audio , Theo Jaquenoud

An Exploration of Probabilistic Models for Consumer Choices, Zhihao Zhang

Improving Flood Maps by Increasing the Temporal Resolution of Satellites Using Hybrid Sensor Fusion - Video Interpolation Networks,Yuval Epstain Ofek

Mississippi Jail Projections: Understanding The Bailable Population, Nithilam Subbaian

Pancancer Analysis to Bridge the Gap between Metabolomics and Transcriptomics through Machine Learning, Junbum Kim

Automatic Artifact Annotator for EEG Waves Using Recurrent and Convolutional Neural Networks, Dongkyu Kim

Autoencoding Neural Networks as Musical Audio Synthesizers, Joseph T. Colonel

Gradient-based Adversarial Attacks to Deep Neural Networks in Limited Access Settings, Yash Sharma

Learning a Latent Space for EEGs with Computational Graphs, Radhakrishnan Thiyagarajan

A Fully Convolutional Neural Network Approach to End-to-End Speech Enhancement, Frank Longueira

A Neural Network Based Implementation of Non-Negative Matrix Factorization for Targeted Speech Denoising, Matthew Smarsch

A Deep Reinforcement Learning Approach to the Portfolio Management Problem , Sahil S. Patel

Learning an End-to-End Physical Layer with Computational Graphs, Caleb Zulawski

Inferring the causal impact of Super Bowl marketing campaigns using a Bayesian structural time series model , Neema Aggarwal

OFDM Modulation Recognition Using Convolutional Neural Networks, Justin Alexander

Alternative Architectures for Image Generation and Residual Dilated Convolutions for Image Colorization with Adversarial Networks, Christopher Curro

Unsupervised Topic Clustering of Text Corpora, Daniel Gitzel

Distributed Synchronization for Ad-Hoc Operation in LTE, David Li

A Generative Model for Digital Camera Chemical Colorimetry, Jason Tam

A Paritioned Auto-encoder for Audio De-Noising, Ethan Lusterman

Classifying Phases of the Business Cycle: A Machine Learning Approach, Julia Astrauckas

Adaptive Phased Locked Loop for Interference Mitigation, Kevin Nguyen

Spectrum Sensing with Non-local Means, David Rubenstein

Synchronization of Interference to Facilitate Joint Detection, Andrew Apollonsky

Interactive Foreground Extraction with Superpixels, Abrar Rahman

Capture-Exploited Fair Rate Adaptation for 802.11 WLANs, Seung Hun Kang

Fair TCP Channel Access for IEEE 802.11 WLANs, Christopher Sang

Joint Spatial-Temporal Equalization of 3G HF Communications, Samantha Blaisdell