Benjamin D. Killeen
Ph.D. Student, Johns Hopkins University
Department of Computer Science
3400 N Charles St
Baltimore, MD 21218, USA
Benjamin D. Killeen - 0000-0003-2511-7929 - benjamindkilleen
@bdkilleen - benjamindkilleen - @benjamindkilleen
A Ph.D. Student at Johns Hopkins University, I am interested in intelligent surgical systems that improve patient outcomes. My recent work involves realistic simulation of interventional X-ray imaging for the purpose of developing AI-integrated surgical systems. I am a member of the Advanced Robotics and Computationally Augmented Environments (ARCADE) research group and the Computational Interaction and Robotics Laboratory (CIRL).
08/2019 - present
Ph.D., Computer Science, Johns Hopkins University, Baltimore, MD, USA.
09/2015 - 06/2019
B.A., Computer Science with Honors, Minor in Physics, University of Chicago, Chicago, IL, USA.
- Thesis: Starting from Scratch: Deep Learning for Novel Scientific Image Analysis
- With Gordon Kindlmann.
08/2020 - present
Research assistant, Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA.
08/2019 - 06/2020
Research Assistant, Laboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD, USA.
- With Gregory D. Hager, Mathias Unberath, and Russel Taylor.
- Recipient: LCSR Fellowship for Outstanding Incoming Ph.D. Students.
03/2018 - 08/2019
Research assistant, Department of Computer Science, University of Chicago, Chicago, IL, USA.
- With Gordon Kindlmann.
06/2020 - 07/2020
Computer Vision / AI Intern, Applied Research, Intuitive Surgical Inc., Sunnyvale, CA, USA.
- With Omid Mohareri.
06/2018 - 08/2018
Software Development Intern, Cognitive Computing, Epic Systems, Verona, WI, USA.
06/2017 - 08/2017
Research Intern, IBM Research - Almaden, San Jose, CA, USA.
- With Geoffrey Burr.
Runner-up, Physics of Medical Imaging Best Student Paper Award
- For paper [C-5] at SPIE Medical Imaging 2022.
- For paper [C-4] at IEEE BIBE 2021.
Best Presentation Award
- In Reliable Software Systems at Johns Hopkins University.
Best Graduate Project Award
- In Computer Integrated Surgical Systems and Technology II at Johns Hopkins University.
COVID-19 Dataset Award, Kaggle
- For the dataset in [M-1].
Intuitive Surgical Best Project Award.
- For Enriching Unsupervised Feature Learning via Intermediate Subtasks in Deep Learning at Johns Hopkins University.
My publication list is also available on Google Scholar. Unless otherwise noted, (*) denotes equal contribution.
Peer-reviewed Journal Articles
A. Hundt, B. Killeen, H. Kwon, C. Paxton, GD Hager. “Good Robot!”: Efficient
Reinforcement Learning for Multi-Step Visual Tasks with Sim to Real Transfer. IEEE Robotics and
Automation Letters, vol. 5, no. 4, pp. 6724–6731, Oct. 2020. doi:
S. Ambrogio, P. Narayanan, H. Tsai, R. M. Shelby, I. Boybat, C. di Nolfo, S. Sidler,
M. Giordano, M. Bodini, N. Farinha, B. Killeen, C. Cheng, Y. Jaoudi,
G. W. Burr. Equivalent-accuracy accelerated neural-network training using analogue
memory. Nature, vol. 558, no. 7708, p. 60, Jun. 2018. doi:
Peer-reviewed Conference Papers
C-5 B. D. Killeen, Shreya Chakraborty, Greg Osgood, Mathias Unberath. Toward perception-based
anticipation of cortical breach during K-wire fixation of the pelvis. Medical Imaging 2022: Physics
of Medical Imaging. SPIE. doi: 10.1117/12.2612989.
- - Runner-up, SPIE Medical Imaging Physics of Medical Imaging Best Student Paper Award
J. D. Opfermann*, B. D. Killeen*, C. Bailey, M. Khan, A. Uneri, K. Suzuki, M. Armand, F. Hui,
A. Krieger**, M. Unberath**. Feasibility of a Cannula-mounted Piezo Robot for Image-guided Vertebral
Augmentation: Toward a Low Cost, Semi-autonomous Approach. 2021 IEEE 21st International Conference
on Bioinformatics and Bioengineering (BIBE), Kragujevac, Serbia, 2021 pp. 1-8.
- *Joint first authors; ** joint last authors.
- - Honored with Best Paper Award in Bioengineering.
X. Liu*, B. D. Killeen*, A. Sinha, M. Ishii, G. Hager, R. Taylor, M. Unberath. Neighborhood
Normalization for Robust Geometric Feature Learning. Proceedings of the IEEE/CVF Conference on
Computer Vision and Pattern Recognition, 2021.
C. Gao, X. Liu, W. Gu, B. D. Killeen, M. Armand, R. Taylor, M. Unberath. Generalizing
Spatial Transformers to Projective Geometry with Applications to 2D/3D
Registrationc. MICCAI, 2020, arxiv:2003.10987.
X. Liu, Y. Zhang, B. Killeen, M. Ishii, G. Hager, R. Taylor, M. Unberath. Extremely Dense Point
Correspondences using a Learned Feature Descriptor. Proceedings of the IEEE/CVF Conference on
Computer Vision and Pattern Recognition, pp. 4847-4856, 2020.
J. Y. Wu*, B. D. Killeen*, P. Nikutta, M. Thies, A. Zapaishchykova, S. Chakraborty,
M. Unberath. Changes in Reproductive Rate of SARS-CoV-2 Due to Non-pharmaceutical Interventions in
1,417 U.S. Counties. medRxiv preprint, Jun. 2020, doi:
B. D. Killeen*, J. Y. Wu*, K. Shah, A. Zapaishchykova, P. Nikutta, A. Tamhane, S. Chakraborty,
J. Wei, T. Gao, M. Thies, M. Unberath. A County-level Dataset for Informing the United States’
Response to COVID-19. arXiv preprint, 2020, arXiv:2004.00756.
P-1 G. W. Burr and B. D. Killeen. 2020. Efficient Processing of Convolutional Neural Network
Layers Using Analog-memory-based Hardware. 20200117986, filed March 25, 2019, and issued April
16, 2020, uspto.report/patent/app/20200117986.
Dziarkach, Andrei. “Details with Andrei Dziarkach.” Voice of America. November 21, 2020
Accessed November 26, 2020. golosameriki.com/a/detali/5671254.html.
Rosen, Jill. “Dog Training Methods Help JHU Teach Robots to Learn New Tricks.” The Johns Hopkins University Hub. The Johns Hopkins University, October 26, 2020. hub.jhu.edu/2020/10/26/positive-reinforcement-for-robots
I have supervised a number of talented masters and undergraduate students on research projects and theses:
10/2021 - present
- Sean Darcy, Johns Hopkins University, Baltimore, MD, USA.
10/2021 - present
- Zidi Tao, Johns Hopkins University, Baltimore, MD, USA.
05/2021 - 10/2021
- Nethra Venkatayogi, The University of Texas at Austin, Austin, TX, USA.
01/2021 - 08/2021
- Max Judish, Brown University, Providence, RI, USA.
08/2020 - 09/2021
12/2019 - 03/2020
08/2019 - present
Computer Integrated Surgery, Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA.
03/2019 - 06/2019
Machine Learning and Large Scale Data Analysis, Department of Computer Science, University of Chicago, Chicago, IL, USA.
- With Yali Amit.
- Wrote supplementary course material and held weekly lab sessions.
Selected review: “Ben was incredibly patient during office hours and always responsive to student questions. In addition, he often presented demos during office hours or showed easier ways to handle the homework assignments; both were very helpful.”
- More reviews available at benjamindkilleen.com/teaching/2019-spring-lsda
01/2019 - 08/2019
Department of Computer Science, University of Chicago, Chicago, IL, USA
- - Scientific Visualization
- - Introduction to Computer Science I
- - Introduction to Computer Science II
06/2020 - present
Topics in Computer Science, Machine Learning, Baltimore, MD, USA.
- We have explored numerous topics, including differential calculus, neural networks, computer vision, natural language processing, and functional programming.
12/2021 - present
Sports Officer, MICCAI Society Student Board
09/2020 - present
Graduate Student Committee Representative, Laboratory for Computational Sensing and Robotics
- Head of Student Resources
06/2021 - present
Family Member, Thread, Baltimore, MD, USA.
- I volunteer with students at Douglass High School in Baltimore City, helping with algebra or physics homework, organizing social outings, and assiting with graduation requirements.
Volunteer Instructor, CompileHer, Chicago, IL, USA.
- - Medical Image Analysis
- - IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
- - Nature Scientific Data
- Vision as Bayesian Inference
- Reliable Software Systems
- Theory of Computation
- Parallel Programming
- Nonlinear Optimization II
- Computer Integrated Surgery II
- Computer Integrated Surgery I
- Deep Learning
- Unsupervised Learning*
- Computer Vision
- Machine Learning and Large Scale Data Analysis
- Operating Systems
- Honors Combinatorics
- Honors Algorithms
- Honors Discrete Mathematics
- Scientific Visualization
- Programming Languages
- Networks and Distributed Systems
- Quantum Mechanics I \& II
- Intermediate Mechanics
- International Society for Optics and Photonics (SPIE) Student Member
- Institute of Electrical and Electronics Engineers (IEEE) Graduate Student Member
Outside of the office, I enjoy bouldering, cycling, running, and painting. I also write creatively:
- Creative nonfiction: benjamindkilleen.com/blog
- Science fiction.
This document is available
Last updated: April 2022