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Jim Boerkoel
Csilla & Walt Foley professor and department chair of computer science @ harvey mudd


Meet Prof Jim!

Welcome!

Prof. Jim Boerkoel

Contact

  • boerkoel[@]cs[.]hmc[.]edu
  • McGregor Computer Science Center, 309
  • Office: 909-607-4522 (x74522)

Bio

Jim Boerkoel is Csilla & Walt Foley Professor and Department Chair of Computer Science at Harvey Mudd College where he also leads the Human Experience & Agent Teamwork Lab. The goal of the HEATLab is to develop techniques that augment humans' own cognitive and physical abilities to create integrated human-robot teams that are more capable than their individual counterparts. Prior to joining HMC, Jim worked as a Postdoctoral Associate with Julie Shah of the Interactive Robotics Group at MIT. Jim completed his doctoral thesis on developing distributed approaches for constraint-based, multi-agent scheduling under the supervision of Ed Durfee at the University of Michigan. Jim received his B.S. (Summa Cum Laude) in both Mathematics and Computer Science from Hope College (2006), and his M.S. (2008) and Ph.D. (2012) in Computer Science and Engineering. In 2017, Boerkoel was recognized with an NSF CAREER award for his project "Robust and Reliable Multiagent Scheduling under Uncertainty." More broadly, his research interests include automated planning and scheduling, multi-robot coordination, human-robot interaction, and AI education.

Education & Previous Experience

  • Postdoctoral Associate, Interactive Robotics Group, Computer Science and Artificial Intelligence Lab - Massachusetts Institute of Technology - Cambridge, MA, 2012 - 2013
  • Ph.D., Computer Science and Engineering - University of Michigan - Ann Arbor, MI, July 2012
  • M.S., Computer Science and Engineering - University of Michigan - Ann Arbor, MI, August 2008
  • B.S., Mathematics, Computer Science - Hope College - Holland, MI, December 2005 (Summa Cum Laude)

Teaching Interests

  • Intro CS
  • Artificial Intelligence
  • Interaction Design
  • Human-Robot Interaction

Research Interests

  • AI Education
  • Multiagent Coordination
  • Assistive Technology
  • Human Robot Interaction
  • Constraint-Based Scheduling
  • Robotics in Advanced Manufacturing

Research

HEATlab

Prof. Jim Boerkoel leads Human Experience & Agent Teamwork Lab (HEATlab) @ HMC. The mission of the HEATlab is to develop robust techniques for human-robot teamwork that exploit the relative strengths of humans and agents. We focus on using ideas from AI to automate the scheduling and coordination human-robot and robot-robot teams. We are particularly motivated by the challenge of coordinating human-robot teams in uncertain environments that require explicit cooperation to be successful. Our research recognizes and exploits the relative strengths of humans and agents to accomplish what neither can achieve alone. You can read more about the HEATlab in this recent PCMag interview with Jim!. For information about Jim's research, current HEATlab projects, publications, news and highlights,please visit heatlab.org, or follow us on social media:

Publications

2023

James Boerkoel and Mehmet Ergezer. 2023. An Undergraduate Consortium for Addressing the Leaky Pipeline to Computing Research. In Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1 (SIGCSE 2023), Association for Computing Machinery, Toronto ON, Canada, 687–693. DOI: https://doi.org/10.1145/3545945.3569841

Rosy Chen, Yiran Ma, Siqi Wu, and James C. Boerkoel Jr. 2023. Sensitivity Analysis for Dynamic Control of PSTNs with Skewed Distributions. In Proceedings of the International Conference on Automated Planning and Scheduling, 95–99. DOI: https://doi.org/10.1609/icaps.v33i1.27183

Emily Weiss, Zeneve Jacotin, Ryan Blake Jackson, Amy Yuan, and James C Boerkoel. 2023. Analyzing the Fluency of Human-Robot Interactions. In Proceedings of the AAAI 2023 Spring Symposium Series on HRI in Academia and Industry: Bridging the Gap. Available: https://rbjackson.github.io/paper_pdfs/weiss2023analyzing.pdf

2022

James C Boerkoel, Mehmet Ergezer, Christine Alvarado, and Valerie Taylor. 2022. Expanding Computing Research Pathways (Panel). In The Conference on Research in Equity and Sustained Participation in Engineering, Computing, and Technology (RESPECT) .

Malia Morgan, Julianna Schalkwyk, Huaxiaoyue Wang, Hannah Davalos, Ryan Martinez, Vibha Rohilla, and James Boerkoel. 2022. Simple Temporal Networks for Improvisational Teamwork. In Proceedings of the International Conference on Automated Planning and Scheduling, 261–269. DOI: https://doi.org/10.1609/icaps.v33i1.27183

2021

James Boerkoel, James Mason, Daniel Wang, Steve Chien, and Adrien Maillard. 2021. An Efficient Approach for Scheduling Imaging Tasks Across a Fleet of Satellites. In Proceedings of 2021 International Workshop on Planning & Scheduling for Space (IWPSS 21). Available: https://ai.jpl.nasa.gov/public/documents/papers/Boerkoel-IWPSS2021-paper-23.pdf

2020

Maya Abo Dominguez, La William, and Jim Boerkoel. 2020. Modeling Human Temporal Uncertainty in Human-Agent Teams. In In Proc. of Artificial Intelligence in Human Robot Interaction AAAI Fall Symposium Series (AI-HRI 2020). DOI: https://doi.org/10.48550/arXiv.2010.04849

Shyan Akmal, Savana Ammons, Hemeng Li, Michael Gao, Lindsay Popowski, and James C. Boerkoel. 2020. Quantifying controllability in temporal networks with uncertainty. Artificial Intelligence 289, (2020), 103384. DOI: https://doi.org/10.1016/j.artint.2020.103384

Steve Ankuo Chien, James Boerkoel, James Mason, D. Wang, Ashley Gerard Davies, Joel Mueting, Vivek Vittaldev, Vishwa Shah, and Ignacio Zuleta. 2020. Space Ground Sensorwebs for Volcano Monitoring. In The International Symposium on Artificial Intelligence, Robotics and Automation in Space. Available: https://www.hou.usra.edu/meetings/isairas2020fullpapers/pdf/5004.pdf

Steve Chien, James Boerkoel, James Mason, Daniel Wang, Ashley Davies, Joel Mueting, Vivek Vittaldev, Vishwa Shah, and Ignacio Zuleta. 2020. Leveraging Space and Ground Assets in A Sensorweb for Scientific Monitoring: Early Results and Opportunities for the Future. In IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020, Waikoloa, HI, USA, September 26 - October 2, 2020, IEEE, 3833–3836. DOI: https://doi.org/10.1109/IGARSS39084.2020.9324049

Michael Gao, Lindsay Popowski, and Jim Boerkoel. 2020. Dynamic Control of Probabilistic Simple Temporal Networks. In Proceedings of the AAAI Conference on Artificial Intelligence, 9851–9858. DOI: https://doi.org/10.1609/aaai.v34i06.6538

2019

Jordan R. Abrahams, David A. Chu, Grace Diehl, Marina Knittel, Judy Lin, William Lloyd, James C. Boerkoel, and Jeremy Frank. 2019. DREAM: An Algorithm for Mitigating the Overhead of Robust Rescheduling. In Proc. of the 29th International Conference on Automated Planning and Scheduling (ICAPS-19), 3–12. DOI: https://doi.org/10.1609/icaps.v29i1.3454

Shyan Akmal, Savana Ammons, Hemeng Li, and James C. Boerkoel. 2019. Quantifying Degrees of Controllability in Temporal Networks with Uncertainty. In Proc. of the 29th International Conference on Automated Planning and Scheduling (ICAPS-19), 22–30. DOI: https://doi.org/10.1609/icaps.v29i1.3456

Seth Isaacson, Gretchen Rice, and James C. Boerkoel. 2019. MAD-TN: A Tool for Measuring Fluency in Human-Robot Collaboration. In In Proceedings of Artificial Intelligence in Human-Robot Interaction AAAI Fall Symposium Series (AI-HRI 2019). DOI: https://doi.org/10.48550/arXiv.1909.06675

Joon Young Lee, Vivaswat Ojha, and James C. Boerkoel. 2019. Measuring and Optimizing Durability against Scheduling Disturbances. In Proc. of the 29th International Conference on Automated Planning and Scheduling (ICAPS-19), 264–268. DOI: https://doi.org/10.1609/icaps.v29i1.3486

2018

Amy Huang, Liam Lloyd, Mohamed Omar, and James Boerkoel. 2018. New Perspectives on Flexibility in Simple Temporal Planning. In Proc. of the 28th International Conference on Automated Planning and Scheduling (ICAPS-18), 123–131. DOI: https://doi.org/10.1609/icaps.v28i1.13907

Vaibhav V. Unhelkar, Stefan Dörr, Alexander Bubeck, Przemyslaw A. Lasota, Jorge Perez, Ho Chit Siu, James C. Boerkoel, Quirin Tyroller, Johannes Bix, Stefan Bartscher, and Julie A. Shah. 2018. Mobile Robots for Moving-Floor Assembly Lines: Design, Evaluation, and Deployment. IEEE Robotics & Automation Magazine 25, 2 (2018), 72–81. DOI: https://doi.org/10.1109/MRA.2018.2815639

2017

Brenda Castro, Montana Roberts, Karla Mena, and Jim Boerkoel. 2017. Who Takes the Lead? Automated Scheduling for Human-Robot Teams. In In Proc. of Technical Report of the Artificial Intelligence in Human-Robot Interaction AAAI Fall Symposium Series (AI-HRI 2017). Available: https://cdn.aaai.org/ocs/15964/15964-69861-1-PB.pdf

Doug Fisher, Charles Isbell, Michael L. Littman, Michael Wollowski, Todd W. Neller, and Jim Boerkoel. 2017. Ask Me Anything about MOOCs. AI Magazine 38, 2 (2017), 7–12. DOI: https://doi.org/10.1609/aimag.v38i2.2729

Kyle Lund, Sam Dietrich, Scott Chow, and James Boerkoel. 2017. Robust Execution of Probabilistic Temporal Plans. In Proc. of the 31st National Conference on Artificial Intelligence (AAAI-17), 3597–3604. DOI: https://doi.org/10.1609/aaai.v31i1.11019

Michael Wollowski, Todd Neller, and James Boerkoel. 2017. Artificial Intelligence Education: Editorial Introduction. AI Magazine 38, 2 (2017), 5–6. DOI: https://doi.org/10.1609/aimag.v38i2.2728

2016

Jane Wu, Erin Paeng, Kari Linder, Piercarlo Valdesolo, and James C Boerkoel. 2016. Trust and Cooperation in Human-Robot Decision Making. In In Technical Report of The 2016 AAAI Fall Symposium Series (FS-16-01): Artificial Intelligence for Human-Robot Interaction (AI-HRI 2016). Available: https://aaai.org/papers/14118-14118-trust-and-cooperation-in-human-robot-decision-making/

2015

Jeb Brooks, Emilia Reed, Alexander Gruver, and James C Boerkoel. 2015. Robustness in Probabilistic Temporal Planning. In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI-15), 3239–3246. Available: https://dl.acm.org/doi/10.5555/2888116.2888167

Priya L Donti, Honey Rosenbloom, Alex Gruver, and James C Boerkoel. 2015. Predicting the Quality of User Experiences to Improve Productivity and Wellness. In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 4154–4155. DOI: https://doi.org/https://doi.org/10.1609/aaai.v29i1.9740

2014

Priya L Donti and James C Boerkoel. 2014. Exploring Active and Passive Team-Based Coordination. In Proceedings of the 2014 AAAI Fall Symposium Series, 62–64. Available: https://cdn.aaai.org/ocs/9112/9112-40056-1-PB.pdf

Edmund H. Durfee, James C. Boerkoel, and Jason Sleight. 2014. Using hybrid scheduling for the semi-autonomous formation of expert teams. Future Generation Computer Systems 31, (2014), 200–212. DOI: https://doi.org/10.1016/j.future.2013.04.008

Vaibhav V Unhelkar, JM Perez, James C Boerkoel, Johannes Bix, Stefan Bartscher, Julie Shah, and others. 2014. Towards control and sensing for an autonomous mobile robotic assistant navigating assembly lines. In Proceedings of the 2014 IEEE International Conference on Robotics and Automation (ICRA), IEEE, 4161–4167. DOI: https://doi.org/10.1109/ICRA.2014.6907464

2013

James C Boerkoel and Edmund H Durfee. 2013. Distributed reasoning for multiagent simple temporal problems. Journal of Artificial Intelligence Research 47, (2013), 95–156. DOI: https://doi.org/10.1613/jair.3840

James C Boerkoel and Edmund H Durfee. 2013. Decoupling the Multiagent Disjunctive Temporal Problem. In Twenty-Seventh AAAI Conference on Artificial Intelligence, 123–129. Available: https://dl.acm.org/doi/abs/10.5555/2484920.2485113

James C Boerkoel, Léon Planken, Ronald Wilcox, and Julie A Shah. 2013. Distributed Algorithms for Incrementally Maintaining Multiagent Simple Temporal Networks. In Proceedings of the 23rd International Conference on Automated Planning and Scheduling (ICAPS), 11–19. Available: https://dl.acm.org/doi/10.5555/3038718.3038721

2012

James C Boerkoel and Edmund H Durfee. 2012. A Distributed Approach to Summarizing Spaces of Multiagent Schedules. In Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 1742–1748. Available: https://dl.acm.org/doi/10.5555/2566972.2566976

2011

James C. Boerkoel and Edmund H. Durfee. 2011. Distributed Algorithms for Solving the Multiagent Temporal Decoupling Problem. In The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 1 (AAMAS ’11), International Foundation for Autonomous Agents, Taipei, Taiwan, 141–148. Available: https://dl.acm.org/doi/abs/10.5555/2030470.2030491

Edmund H Durfee, James C Boerkoel, and Jason Sleight. 2011. Comparing techniques for the semi-autonomous formation of expert teams. In 2011 International Conference on Collaboration Technologies and Systems (CTS) Workshop on Multi-Agent Systems and Collaborative Technologies (I-MASC11), IEEE, 351–358. DOI: https://doi.org/10.1109/CTS.2011.5928710

2010

James C. Boerkoel and Edmund H. Durfee. 2010. A Comparison of Algorithms for Solving the Multiagent Simple Temporal Problem. In Proceedings of the Twentieth International Conference on International Conference on Automated Planning and Scheduling (ICAPS’10), AAAI Press, Toronto, Ontario, Canada, 26–33. Available: https://dl.acm.org/doi/10.5555/3037334.3037339

James C Boerkoel, Edmund H Durfee, and Keith Purrington. 2010. Generalized solution techniques for preference-based constrained optimization with cp-nets. In Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1-Volume 1, 291–298. Available: https://dl.acm.org/doi/abs/10.5555/1838206.1838247

2009

James C Boerkoel and Edmund H Durfee. 2009. Evaluating hybrid constraint tightening for scheduling agents. In Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems-Volume 1, 673–680. Available: https://dl.acm.org/doi/pdf/10.5555/1558013.1558106

2008

James C. Boerkoel and Edmund H. Durfee. 2008. Hybrid Constraint Tightening for Solving Hybrid Scheduling Problems. In Proceedings of the 23rd National Conference on Artificial Intelligence (AAAI’08), AAAI Press, Chicago, Illinois, 1446–1449. Available: https://dl.acm.org/doi/abs/10.5555/1620270.1620301

Contact Me

My preferred mode of communication is email. Please see contact information above to get in touch.

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