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Faculty

 
Amotz Bar-Noy
Brooklyn College
Website

Peter Brass
City College of New York
Website

Chen Chao
Queens College
Website

Soon Ae Chun
College of Staten Island
Website

Saptarshi Debroy
Graduate CenterHunter College
Website

Scott Dexter
Brooklyn College
Website

Susan Epstein
Hunter College
Website

Elena Filatova
Graduate CenterNew York City College of Technology
Website

Michael Grossberg
City College of New York

Feng Gu
College of Staten Island
Website

Olympia Hadjiliadis
Hunter College
Website

Robert M Haralick
Graduate Center
Website

Matthew Johnson
Lehman College
Website

Delaram Kahrobaei
New York City College of Technology
Website

Akira Kawaguchi
City College of New York
Website

Devorah Kletenik
Brooklyn College

Rivka Levitan
Brooklyn College
Website

Michael Mandel
Brooklyn College
Website

Lev Manovich
Graduate Center
Website

Louis Petingi
College of Staten Island
Website

Theodore Raphan
Brooklyn College
Website

Ashwin Satyanarayana
Graduate CenterNew York City College of Technology
Website

Dina Sokol
Brooklyn College
Website

Katherine St. John
Lehman College
Website

Ioannis Stamos
Hunter College
Website

Bon K. Sy
Queens College
Website

Abdullah Uz Tansel
Baruch College
Website

Ying-Li Tian
City College of New York
Website

Felisa Vazquez-Abad
Hunter College
Website

Huy Vo
Graduate Center
Website

Jie Wei
City College of New York
Website

Paula Whitlock
Brooklyn College
Website

George Wolberg
City College of New York
Website

Changhe Yuan
Queens College
Website

Sarah Zelikovitz
College of Staten Island
Website

Jianting Zhang
City College of New York
Website

Shuqun Zhang
College of Staten Island
Website

Zhigang Zhu
City College of New York
Website

 
 

Data Science

The focus of Data Science is to advance the core scientific and technological
means of managing, analyzing, visualizing, and extracting useful
information from large, diverse, distributed and heterogeneous data
sets to: accelerate the progress of scientific discovery and
innovation; lead to new fields of inquiry that would not otherwise be
possible; encourage the development of new data analytic tools and
algorithms; facilitate scalable, accessible, and sustainable data
infrastructure; increase understanding of human and social processes
and interactions.



The rapid digitalization of the world in recent decades has made various kinds of data available whose depth and breadth is steadily increasing. The interdisciplinary field of data science aims to derive knowledge or previously hidden insights from usually vast amounts of this new data, both structured and unstructured, by applying and extending methods of statistics, machine learning, data modeling, data mining, data visualization and other fields. In doing so, it applies domain knowledge, often to solve specific problems in business such as fraud detection or marketing optimization but also in other fields like medicine or security. To obtain a dataset that they can work with, data scientists also develop and apply concepts for large-scale data collection, storage and preparation. Our courses in Data Science covers all fundamental concept and techniques of the field as well as latest developments, and prepare students to engage in research of their own. Current faculty research interests include machine learning, pattern recognition, knowledge discovery, modeling and simulation, large complex systems, distributed computing, data mining, data visualization, and more.


Courses

 

3D Photography
Advanced Data Structures
Algorithms For Big Data Analysis
Artificial Intelligence
Big Data Analytics
Big Spatial Data
Combinatorial Algorithms
Computer Vision And Image Processing
Data Mining
Data Visualization
Database Management Systems
Graph And Social Network Analysis
Graphical Models
Machine Learning
Machine Learning In Quantitative Finance
Modeling and Simulation
Natural Language Processing
Parallel Scientific Computing
Pattern Matching
Programming Massively Parallel Systems
Quickest Detection and Applications
Analysis of Social and Cultural Data
Text Mining and Classification
Vision, Brain and Assistive Technologies