CDS-Courant Undergraduate Research Program
PROGRAM DATES: JANUARY 24 – MAY 18, 2022
LOCATION: RESEARCH PROJECTS WILL TAKE PLACE REMOTELY
FELLOWSHIP AWARD: $3,500
APPLICATION DEADLINE: OCTOBER 31, 2021
Welcome to NYU’s Center for Data Science
The Center for Data Science (CDS) is the focal point for New York University’s university-wide efforts in Data Science. The Center was established in 2013 to advance NYU’s goal of creating a world-leading Data Science training and research facility, and arming researchers and professionals with the tools to harness the power of Big Data. Today, CDS counts 20 jointly appointed interdisciplinary faculty housed on three floors of our magnificent 60 5th Avenue building, one of New York City’s historic properties. It is home to a top-ranked MS in Data Science program, one of the first PhD programs in Data Science, and a new undergraduate program in Data Science, as well as a lively Fellow and Postdoctoral program. It has over 60 associate and affiliate faculty from 25 departments in 9 schools and units. With cross-disciplinary research and innovative educational programs, CDS is shaping the new field of Data Science.
CDS Associate Professor Kyunghyun Cho Named One of the “30 Leaders Under 40 Changing Healthcare in 2023” by Business Insider!
Kyunghyun Cho is revolutionizing drug discovery in the biotech world. His early research laid the groundwork for cutting-edge AI systems like ChatGPT. His journey led him to NYU, where he’s been instrumental in creating a data science hub for healthcare.
CDS Postdoc Researcher Micah Goldblum Recently Named Finalist for the 2023 Blavatnik Regional Awards for Young Scientists!
The award celebrates the brightest early-career researchers minds in the tri-state area. Dr. Goldblum’s pioneering research at NYU, alongside renowned experts Yann LeCun and Andrew Gordon Wilson, delves deep into the intricacies of machine learning.
Free Online Resource: Yann LeCun’s Deep Learning Course
Yann LeCun’s Deep Learning Course covers the latest techniques in both deep learning and representation learning, focusing on supervised/self-supervised learning, embedding methods, metric learning, convolutional and recurrent nets, with applications to computer vision, natural language understanding, and speech recognition.
Free Online Resource: Mathematical Tools for Data Science
Mathematical Tools for Data Science, developed by CDS Associate Professor Carlos Fernandez-Granda, provides an introduction to tools from several areas of mathematics such as linear algebra, Fourier analysis, probability theory, and convex optimization, which are useful in data science.
- Data Science Lunch Seminar Series: Florentin Guth, NYU
September 27, 2023, 12:30 pm
- Data Science Lunch Seminar Series: Cory McCartan, NYU
October 11, 2023, 12:30 pm
- NLP and Text-as-Data Speaker Series: Jacob Steinhardt (UC Berkeley)
October 19, 2023, 4:00 pm
- Data Science Lunch Seminar Series: Aahlad Puli, NYU
October 25, 2023, 12:30 pm
- NLP and Text-as-Data Speaker Series: Yoon Kim (MIT)
October 26, 2023, 4:00 pm
- Data Science Lunch Seminar Series: Sebastian Wagner-Carena, NYU
November 15, 2023, 12:30 pm
- NLP and Text-as-Data Speaker Series: Eunsol Choi (UT Austin)
November 16, 2023, 4:00 pm
- Data Science Lunch Seminar Series: Saadia Gabriel, NYU
November 29, 2023, 12:30 pm
- NLP and Text-as-Data Speaker Series: Daniel Khashabi (Johns Hopkins University)
November 30, 2023, 4:00 pm
- Data Science Lunch Seminar Series: Mor Naaman, Cornell Tech
December 6, 2023, 12:30 pm