Alex Gittens

Email: gittea at rpi dot edu
Office: 316 Lally Building
General Office Hours: ThF 1-2pm
Tel: 518-276-6476
Address: Room 316 Lally, CS Department, 110 8th St, Troy, NY 12180

I am an assistant professor in the Computer Science department of Rensselaer Polytechnic Institute. My research focuses on using randomization to reduce the computational costs of extracting information from large datasets. My work lies at the intersection of randomized algorithms, numerical linear algebra, high-dimensional probability, and machine learning.

I earned my PhD in applied and computational mathematics at CalTech under the supervision of Prof. Joel Tropp, in 2013. From 2013 until 2015, I was a member of the machine learning research group at eBay. Following that I was a postdoctoral fellow in the AMPLab at UC Berkeley and a member of the International Computer Science Institute. I joined RPI in January of 2017.

Research

My current research interests include, in no order:

Group

My current graduate students are Sharmishtha Duttas (PhD; AI for threat intelligence), Dong Hu (PhD; matrix completion and low-rank approximation), and Kevin Kim (PhD; tensor decompositions). In the summer of 2020, I am also working with Chris Jerrett (BS; tensor decomposition heuristics).

Publications (out of date; see Google Scholar)

Technical Reports

Teaching

Fall 2020 Teaching CSCI4961/6961, "Machine Learning and Optimization". The focus is on understanding randomized algorithms motivated by and focusing on applications in machine learning and data analysis.
Spring 2020 Taught CSCI2200, "Foundations of Computer Science", a discrete mathematics/theory of computing course. See the website for more information.
Fall 2019 taught CSCI6220/4030, "Randomized Algorithms". See the website for the syllabus and assignments.
Spring 2019 taught CSCI6971/CSCI4971, "Large Scale Matrix Computation and Machine Learning". See the website for the syllabus and assignments.
Fall 2018 taught CSCI6220/4030, "Randomized Algorithms". See the website for the syllabus and assignments.
Spring 2018 taught CSCI6971/CSCI4971, "Large Scale Matrix Computation and Machine Learning". See the website for the syllabus and assignments.
Fall 2017 taught CSCI6220/4030, "Randomized Algorithms". See the website for the syllabus and assignments.
Spring 2017 taught CSCI6971/CSCI4971, "Large Scale Matrix Computation and Machine Learning". See the syllabus.