What's New

New paper accepted to ISMIR 2018 (with Rachel Manzelli, Vijay Thakkar, and Ali Siahkamari): "Conditioning Deep Generative Raw Audio Models for Structured Automatic Music." The paper is available on arxiv here. See this page for some example results.

New paper (with Andrew Cutler) on Arxiv, and also accepted to Socinfo 2018: "Inferring Human Traits from Facebook Statuses", posted here.

New paper (with Rachel Manzelli, Vijay Thakkar, and Ali Siahkamari) appeared at the Workshop on Musical Metacreation in Salamanca, Spain, entitled "An End-to-End Model for Automatic Music Generation: Combining Deep Raw and Symbolic Audio Networks". Paper available here.

New paper accepted to IEEE Transactions on Pattern Analysis and Machine Intelligence (with Trevor Campbell and Jon How): "Dynamic Clustering Algorithms via Small-Variance Analysis of Markov Chain Mixture Models."

New paper appearing at ICLR 2018 (with Ben Usman and Kate Saenko): "Stable Distribution Alignment using the Dual of the Adversarial Distance."

I am the co-chair for the annual BU Data Science Day in January, 2018.

New paper (with Xide Xia): "W-Net: A Deep Model for Fully Unsupervised Image Segmentation" posted here.

Introduction

I am an associate professor in the Department of Electrical and Computer Engineering and the Department of Computer Science at Boston University. I am also a core member of the Division of Systems Engineering. From 2015-2018 I was the Peter J. Levine Career Development Assistant Professor in ECE and CS at Boston University, and from 2012-2015 I was an assistant professor in the Department of Computer Science and Engineering and the Department of Statistics at Ohio State University.

Before that, I spent three years as a postdoc at UC Berkeley EECS (Computer Science Division), and was also affiliated with ICSI, where I had the good fortune to work with Trevor Darrell, Stuart Russell, Michael Jordan, and Peter Bartlett. Broadly speaking, I am interested in all aspects of machine learning, with an emphasis on applications to computer vision. Most of my research focuses on making it easier to analyze large-scale data. A major focus is on large-scale optimization for core problems in machine learning such as metric learning, content-based search, clustering, and online learning. I am also interested in large-scale graphical models, Bayesian inference, Bayesian nonparametrics, and deep learning.

I finished my Ph.D. in computer science in November, 2008, supervised by Inderjit Dhillon in the University of Texas at Austin computer science department. I did my undergrad in computer science and mathematics at Cornell University. I have also worked with John Platt and Arun Surendran at Microsoft Research on large-scale optimization, and as an undergraduate, I worked with John Hopcroft on tracking topics in networked data over time. During the Fall 2007 semester, I was a research fellow at the Institute for Pure and Applied Mathematics at U.C.L.A.

Curriculum Vitae [pdf]

Recent Service

Area chair: ICML 2019

Area chair: AISTATS 2019

Area chair: NIPS 2018

Area chair: ICML 2018

Senior Program Committee: AAAI 2018

Area chair: NIPS 2017

Area chair: ICML 2017

Area chair: AISTATS 2017

Area chair: ICML 2016

Area chair: AISTATS 2016

Area chair: ICML 2015

Area chair: AISTATS 2015

Area chair: NIPS 2014

Area chair: ICML 2014

Local arrangements chair: CVPR 2014

Area chair: ICML 2013

Publications by Type

Publications Chronologically

Google scholar profile

Teaching

Spring, 2019. Introduction to Machine Learning

Fall, 2018. Deep Learning

Spring, 2018. Advanced Data Structures and Algorithms

Spring, 2017. Deep Learning

Spring, 2017. Advanced Data Structures and Algorithms

Fall, 2016. Advanced Data Structures and Algorithms

Spring, 2015. Bayesian Modeling and Inference

Fall, 2014. Survey of Artificial Intelligence II

Spring, 2014. Survey of Artificial Intelligence II

Spring, 2013. Machine Learning

Fall, 2012. Probabilistic Graphical Models

Spring, 2012. Bayesian Modeling and Inference

Current Students

Andrew Cutler, PhD student

Kubra Cilingir, PhD student

Ali Siahkamari, PhD student

Xide Xia, PhD student

Rachel Manzelli, Undergraduate

Vijay Thakkar, Undergraduate

Former Group Members

Siva Sankarapandian, MS. After BU: Proscia Inc.

Robert Finn, PhD. After OSU: Assistant Professor, St. Peters University.

Anirban Roychowdhury, PhD. After OSU: Research Scientist at Facebook.

Ke Jiang, PhD. After OSU: Data Scientist at Microsoft.

Xiangyang Xhou, MS. After OSU: Google.

Lizzy Burl, BS. After OSU: Google.

Jiaxin Zhang, MS. After OSU: Google.

Ye Liu, MS. After OSU: PhD student, University of Michigan.

Siddharth Singh, MS. After OSU: IBM, then Amazon.

Research Details

Click here to read more about some of my research.

Contact Info

Office: 441 PHO

Email: bkulis [at] bu [dot] edu