Associate Professor
Department of Electrical and Computer Engineering
Department of Computer Science
Division of Systems Engineering
Boston University
Boston, MA
What's New
New paper accepted to CVPR 2019 (with Kun He, Fatih Cakir, Xide Xia, and Stan Sclaroff): "Deep Metric Learning to Rank." 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: NeurIPS 2019 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