TRAVIS MANDEL
Associate Professor
Data Science Program Coordinator
Department of Computer Science
University of Hawai'i at Hilo
Email: tmandel [at] hawaii [dot] edu
I am happy to be an associate professor at the University of Hawai'i at Hilo. I have worked to create an interdisplinary data science major and certificate, and am currently leading them as the data science program coordinator. Before joining UH Hilo, I earned my PhD from the Paul G. Allen School of Computer Science and Engineering at the University of Washington advised by Zoran Popović and Emma Brunskill (Stanford). Before that, I earned my Bachelor's degree in Computer Science from Carnegie Mellon University.
Research Interests
I am currently interested in Human-In-the-Loop Artificial Intelligence (AI): How do we create AI systems that work effectively with human teammates to achieve better results than either could individually? This area of research lies at the intersection of two fields: AI and Human-Computer Interaction (HCI). I am particularly interested in exploring how AI can most effectively work together with human scientists, identifying and addressing common problems that arise in a number of different scientific domains. This has led me to do new work in the field of Computer Vision (CV) to meet the needs of Hawai'i Island scientists who wish to extract important scientific data from images and video. In 2020 I was awarded a National Science Foundation CAREER Award to advance this research agenda, and in 2022 I joined the NSF EPSCoR CHANGE HI team to help develop new Human-in-the-Loop AI techniques for climate science. My PhD work focused on improved reinforcement learning techniques to make educational video games more effective, a challenging real-world setting in which we encountered all sorts of fascinating and fundamental AI challenges. In the past I have also done significant work in channel coding (CRC error correction) for wireless sensor networks (WSNs), a totally unrelated area of computer science.Students
I am pleased to work with a awesome group of research students, both during summer research experiences as well as throughout the school year: Masters students (on thesis committee): Rebekka Williams (Communicology, University of Hawaii at Manoa, primary advisor Dr. Jessica Gasiorek)Olivia Jarvis (Tropical Conservation Biology and Environmental Science [TCBES], primary advisor Dr. Ryan Perroy)
Erica Ta (Tropical Conservation Biology and Environmental Science [TCBES], primary advisor Dr. Ryan Perroy, Graduated 2022) Undergraduate students:
Carina de Pillis-Shintaku (2024-)
Dan Malone (2023-)
Marcy Bautista (2022-)
Rodel Tagalicud (2022-)
Sebastian Carter (2019-)
Richard Oliver (2024)
Ethan Sick (2022-2023)
Ryp Ring (2022-2023)
Kalani Perry (2023)
Gus Coffey (2023)
Sharmin Zaman (2023)
Ryan Foley (2023)
Leo Espinosa Diaz (2023)
Tyler Spears (2023)
Rick Kobayashi (2023)
Clay Eitel (2022-2023)
Ryan Liu (2022)
Alannah Shinde (2022)
Roi Tanimoto (2022)
Olivia Jarvis (2022)
Jennifer Nakano (2022)
Meynard Ballesteros (2021-2022)
Keane Nakatsu (2021-2022)
Mark Jimenez (2020-2022)
Chris Hanley (2021)
Jaden Kapali (2021)
Ka'imi Beatty (2021)
Chris Roof (2021)
Alexa Runyan (2020-2021)
Urban Halpern (2021)
John Kuroda (2021)
Scott Sison (2020-2021)
James Boyd (2020)
Russ Masuda (2020)
Pat Pérez (2019-2020)
Kosta Devedzhiev (2020)
Ed Cashman (2020)
Emily Risley (2020)
Taishi Nammoto (2019-2020)
Ian Herman (2020)
Tim Kudryn (2019)
Kayla Schlechtinger (2019)
Max Panoff (2019)
Rebekka Williams (2018-2019)
Randy Tanaka (2018-2019)
Alec Goodson (2018)
Tyler Boromeo (2018)
Chansen Haili (2018)
Hiram Temple (2018)
Jahnu Best (2017-2018)
Isabella Mow (2023-)
Teaching
This Spring 2024 semester, I am teaching:
CS/DATA 272 Machine Learning for Data Scientists
CS 350 Systems Programming
In the past, I have taught:
CS 150 Intro to Computer Science I (Fall 2017, Spring 2018, Fall 2018, Spring 2019, Fall 2019, Fall 2020, Fall 2021)
CS 151 Intro to Computer Science II (Spring 2019, Spring 2020, Spring 2022)
CS/DATA 172 Python for Data Analysis (Fall 2018, Fall 2019, Fall 2020, Fall 2021, Fall 2022i, Fall 2023)
CS/DATA 272 Machine Learning for Data Scientists (Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023)
CS 350 Systems Programming (Spring 2020, Spring 2021, Fall 2022)
CS 440 Artificial Intelligence (Fall 2017, Fall 2019, Fall 2021, Fall 2023)
CS/DATA 483 Computer Vision (Spring 2023)
CS 494 Data-Driven Video Game Design (Spring 2018)
CS/DATA 272 Machine Learning for Data Scientists
CS 350 Systems Programming
In the past, I have taught:
CS 150 Intro to Computer Science I (Fall 2017, Spring 2018, Fall 2018, Spring 2019, Fall 2019, Fall 2020, Fall 2021)
CS 151 Intro to Computer Science II (Spring 2019, Spring 2020, Spring 2022)
CS/DATA 172 Python for Data Analysis (Fall 2018, Fall 2019, Fall 2020, Fall 2021, Fall 2022i, Fall 2023)
CS/DATA 272 Machine Learning for Data Scientists (Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023)
CS 350 Systems Programming (Spring 2020, Spring 2021, Fall 2022)
CS 440 Artificial Intelligence (Fall 2017, Fall 2019, Fall 2021, Fall 2023)
CS/DATA 483 Computer Vision (Spring 2023)
CS 494 Data-Driven Video Game Design (Spring 2018)
Publications
A asterisk * indicates a co-author who was a UH Hilo undergraduate supervised by meSelected Publications
Detection Confidence Driven Multi-Object Tracking to Recover Reliable Tracks from Unreliable Detections Travis Mandel, Mark Jimenez*, Emily Risley*, Taishi Nammoto*, Rebekka Williams*, Max Panoff*, Meynard Ballesteros*, Bobbie Suarez Pattern Recognition, Vol. 135, 2023Editor's Choice Award
(An earlier version of this paper appeared on arXiv) AI-Assisted Scientific Data Collection with Iterative Human Feedback Travis Mandel, James Boyd*, Sebastian J. Carter*, Randall H. Tanaka*, Taishi Nammoto* AAAI Conference on Artificial Intelligence (AAAI) 2021. Using the Crowd to Prevent Harmful AI Behavior
Travis Mandel, Jahnu Best*, Randall H. Tanaka*, Hiram Temple*, Chansen Haili*, Sebastian J. Carter*, Kayla Schlechtinger*, Roy Szeto
Proceedings of the ACM on Human-Computer Interaction 4, CSCW2, Article 97 (October 2020). Simultaneously appeared in ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW) 2020.
(An earlier version of this paper appeared on arXiv)
Where to Add Actions in Human-in-the-Loop Reinforcement Learning Travis Mandel, Yun-En Liu, Emma Brunskill, Zoran Popović. AAAI Conference on Artificial Intelligence (AAAI) 2017. Efficient Bayesian Clustering for Reinforcement Learning Travis Mandel, Yun-En Liu, Emma Brunskill, Zoran Popović. International Joint Conference on Artificial Intelligence (IJCAI) 2016. Offline Evaluation of Online Reinforcement Learning Algorithms Travis Mandel, Yun-En Liu, Emma Brunskill, Zoran Popović. AAAI Conference on Artificial Intelligence (AAAI) 2016. The Queue Method: Handling Delay, Heuristics, Prior Data, and Evaluation in Bandits Travis Mandel, Yun-En Liu, Emma Brunskill, Zoran Popović. AAAI Conference on Artificial Intelligence (AAAI) 2015. Offline Policy Evaluation Across Representations with Applications to Educational Games Travis Mandel, Yun-En Liu, Sergey Levine, Emma Brunskill, Zoran Popović. Autonomous Agents and Multiagent Systems (AAMAS) 2014. Practical Error Correction for Resource-Constrained Wireless Networks: Unlocking the Full Power of the CRC [Download PDF]
Travis Mandel, Jens Mache. ACM Conference on Embedded Networked Sensor Systems (SenSys) 2013.
Other Publications
Comparing Interpretation of High-Resolution Aerial Imagery by Humans and Artificial Intelligence to Detect an Invasive Tree SpeciesRoberto Rodriguez III, Ryan L. Perroy, James Leary, Daniel Jenkins, Max Panoff, Travis Mandel, Patricia Perez.
Remote Sensing Vol. 13, 2021
A Comparison of the Diagnostic Accuracy of in-situ and Digital Image-Based Assessments of Coral Health and Disease
John H. R. Burns, Grady Weyenberg, Travis Mandel, Sofia B. Ferreira*, Drew Gotshalk*, Chad K. Kinoshita*, Micah J. Marshall*, Nicholas A. V. Del Moral*, Shane J. Murphy*, Kailey H. Pascoe, Alexandra Runyan*, Alexander J. Spengler*, Brittany D. Wells*, Danielle K. Wilde*, Roberto Pelayo
Frontiers in Marine Science Vol. 7, 2020
Balancing Human and Machine Performance When Analyzing Image Cover [Download PDF]
Travis Mandel, Drew Gotshalk*, Nicholas A. V. Del Moral*, Danielle K. Wilde*, Micah J. Marshall*, Alexander J. Spengler*, Shane J. Murphy*, Brittany D. Wells*, John H. R. Burns, Grady Weyenberg
Conference on Computational Science & Computational Intelligence (CSCI) 2019
Exploring Interfaces to Democratize AI Constraint Generation
Travis Mandel, Jahnu Best*, Randall H. Tanaka*, Hiram Temple*, Chansen Haili*, Roy Szeto.
Poster at AAAI-19 Workshop on Artificial Intelligence Safety (SafeAI) 2019.
Building Out Data Science at Small Colleges Travis Mandel, Jens Mache, Richard Weiss, Peter Drake. Poster at ACM Special Interest Group on Computer Science Education (SIGCSE) 2018. Examining PhD Student Interest in Teaching: An Analysis of 19 Years of Historical Data Travis Mandel, Jens Mache. Poster at ACM Special Interest Group on Computer Science Education (SIGCSE) 2017. Crowdsourcing Accurate and Creative Word Problems and Hints Yvonne Chen, Travis Mandel, Yun-En Liu, Zoran Popović. AAAI Conference on Human Computation and Crowdsourcing (HCOMP) 2016. Developing a Short Undergraduate Introduction to Online Machine Learning Travis Mandel, Jens Mache Journal of Computing Sciences in Colleges, Volume 32, Number 1. 2016. Nonstationary Evaluation for Reinforcement Learning Travis Mandel, Yun-En Liu, Emma Brunskill, Zoran Popović. Reinforcement Learning and Decision Making (RLDM) 2015. Trading Off Scientic Knowledge and User Learning with Multi-Armed Bandits Yun-En Liu, Travis Mandel, Emma Brunskill, Zoran Popović. Educational Data Mining (EDM) 2014. Towards Automatic Experimentation of Educational Knowledge Yun-En Liu, Travis Mandel, Emma Brunskill, Zoran Popović. Computer-Human Interaction (CHI) 2014. Honorable Mention Unbiased Offline Evaluation of Policy Representations for Educational Games Travis Mandel, Yun-En Liu, Sergey Levine, Emma Brunskill, Zoran Popović. Data Driven Education Workshop, Neural Information Processing Systems (NIPS) 2013. Predicting Player Moves in an Educational Game: A Hybrid Approach Yun-En Liu, Travis Mandel, Eric Butler, Erik Andersen, Eleanor O'Rourke, Emma Brunskill, Zoran Popović. Educational Data Mining (EDM) 2013. Best Paper Nomination. ContextType: Using Hand Posture Information to Improve Mobile Touch Screen Text Entry [Download PDF] Mayank Goel, Alex Jansen, Travis Mandel, Shwetak N. Patel, Jacob O. Wobbrock Computer-Human Interaction (CHI) 2013. Investigating CRC Polynomials that Correct Burst Errors Travis Mandel, Jens Mache International Conference on Wireless Networks (ICWN) 2009. Selected CRC Polynomials Can Correct Errors and Thus Reduce Retranmission Travis Mandel, Jens Mache Workshop on Information Theory for Sensor Networks (WITS), International Conference on Distributed Computing in Sensor Systems (DCOSS) 2009. Sensor Network Security: Elliptic Curve Cryptography on SunSPOTs Jens Mache, Samuel W. Bock, James Elwell, Dennis P. Gosnell, Travis Mandel, Jonathan S. Perry-Houts International Conference on Wireless Networks (ICWN) 2008.