Paul Ruvolo

Research Interests

For a description of my current research direction and interest, please see the OCCaM frontpage.

Teaching

• Technology, Accessibility, and Design, Spring 2018 (materials available upon request)
• Quantitative Engineering Analysis 2, Fall 2017 (materials available upon request)
• Quantitative Engineering Analysis 1, Spring 2017 (materials available upon request)
• Data Science, Spring 2016
• A Computational Introduction to Robotics, Fall 2014, Fall 2015, and Spring 2017.
• Software Design, Spring 2014, Spring 2015, Spring 2016, and Spring 2018
• Modeling and Simulation of the Physical World, Fall 2013
• Creative Computation, Fall 2012 and Spring 2013

Publications

[39] Leveraging Augmented Reality to Create Apps for People with Visual Disabilities: A Case Study in Indoor Navigation
	with Chris Yoon, Ryan Louie, Jeremy Ryan, MinhKang Vu, Hyegi Bang, and William Derksen	ACM ASSETS 2019
[38] Embracing our Future: CS Courses and Curriculum for Non-CS-majors
	with Darakhshan Mir and Zach Dodds	Workshop at SIGCSE 2019
[37] A Contextualized, Experiential Learning Approach to Quantitative Engineering Analysis
	with Siddhartan Govindasamy, Rebecca Christianson, John Geddes, Chris Lee, Samantha Michalka, Mark Somerville, and Alexandra Coso Strong	FIE 2018
[36] Behind the robot’s smiles and frowns: In social context, people do not mirror android’s expressions but react to their informational value
	with Galit Hofree, Audrey Reinert, Marian S. Bartlett, and Piotr Winkielman	Frontiers in Neuroscience 2018
[35] Autonomous sailing for blind sailors using GPS
	with Kaitlyn Kiel, Alex Morrow, and John Geddes	OCEANS 2017
[34] Sensing sail luffing by detection of sail shape
	with Rebecca Jordan, and Alex Morrow	OCEANS 2017
[33] How Do Faculty Partner While Teaching Interdisciplinary CS+X Courses: Models and Experiences
	with Darakhshan Mir, Sumita Mishra, Lori Pollock, and Sam Engen	Journal of Computing Sciences in Colleges
[32] Dude, Where's My Robot?: A Localization Challenge for Undergraduate Robotics
		EAAI 2017
[31] Infants Time Their Smiles to Make Their Moms Smile
	with Daniel Messinger and Javier Movellan	PLOS ONE 2015
[30] Autonomous Cross-Domain Knowledge Transfer in Lifelong Policy Gradient Reinforcement Learning
	with Haitham Bou Ammar, Eric Eaton, and Jose Marcio Luna	IJCAI 2015
[29] Unsupervised Cross-Domain Transfer in Policy Gradient Reinforcement Learning via Manifold Alignment
	with Haitham Bou Ammar, Eric Eaton, and Matthew E. Taylor	AAAI 2015
[28] The Android in the Room: Spontaneous Mimicry of a Physically Present Android
	with Galit Hofree, Marian S. Bartlett, and Piotr Winkielman	PLOS ONE 2014
[27] Online Multi-Task Learning for Policy Gradient Methods
	with Haitham Bou Ammar, Eric Eaton, and Matthew Taylor	ICML 2014
[26] Online Multi-Task Learning via Sparse Dictionary Optimization
	with Eric Eaton	AAAI 2014
[25] Exploiting Commonality and Interaction Effects in Crowdsourcing Tasks Using Latent Factor Models
	with Jacob Whitehill and Javier Movellan	NIPS Workshop on Crowdsourcing: Theory, Algorithms, and Applications 2013
[24] Affective Computing, Emotional Development, and Autism
	with Daniel Messinger, Leticia Lobo Duvivier, Zachary Warren, Mohammad Mahoor, and Jason Baker, Anne Warlaumont	in Calvo R. (Ed.), Handbook of Affective Computing. New York: Oxford University Press.
[23] Active Task Selection for Lifelong Machine Learning [code]
	with Eric Eaton	AAAI 2013
[22] ELLA: An Efficient Lifelong Learning Algorithm [Matlab code, Python code]
	with Eric Eaton	ICML 2013
[21] Online Multi-Task Learning Based on K-SVD
	with Eric Eaton	ICML Workshop on Theoretically Guided Transfer Learning 2013
[20] Scalable Lifelong Learning with Active Task Selection
	with Eric Eaton	AAAI Spring Symposium on Lifelong Learning 2013
[19] A Computational Approach to the Study of Social Interaction
		UC San Diego Ph.D. Dissertation 2012
[18] Control by Gradient Collocation: Applications to Optimal Obstacle Avoidance and Minimum Torque Control
	with Tingfan Wu and Javier Movellan	IROS 2012
[17] Multi-layer architectures for facial action unit recognition
	with Tingfan Wu, Nicholas Butko, Jacob Whitehill, Marian Bartlett, and Javier Movellan	Systems, Man, and Cybernetics (journal) 2012
[16] Collecting a Developmental Dataset of Reaching Behavior: First Steps
	with Tingfan Wu, Juan Artigas, Whitney Mattson, Javier Movellan, and Daniel Messinger	IROS Workshop on Cognitive Neuroscience Robots 2011
[15] Are you interested baby? Young infants exhibit stable patterns of attention during interaction
	with Daniel Messinger, Naomi Ekas, and Alan Fogel	Infacy (journal) 2011
[14] Action Unit Recognition Transfer Across Datasets
	with Tingfan Wu, Nicholas Butko, Jacob Whitehill, Marian Bartlett, and Javier Movellan	Face and Gesture Workshops 2011
[13] The motion in emotion -- a CERT based approach to the FERA emotion challenge
	with Gwen Littlewort, Marian Bartlett, Jacob Whitehill, Tingfan Wu, Nicholas Butko, and Javier Movellan	Face and Gesture Workshops 2011
[12] Alternatives to Low-Level Synchrony Based Methods for Speech Detection
	with Javier Movellan	NIPS 2010
[11] Applying Machine Learning to Infant Interaction: The Development's in the Details
	with Daniel Messinger, Naomi Ekas, and Alan Fogel	Neural Networks (journal) 2010
[10] A learning approach to hierarchical feature selection and aggregation
	with Ian Fasel and Javier Movellan	Pattern Recognition Letters (journal) 2010
[9] Approaches and Databases for Online Calibration of Binaural Sound Localization for Robotic Heads
	with Holger Finger, Shih-Chii Lui, and Javier Movellan	IROS 2010
[8] Whose Vote Should More: Optimal Integration of Labels from Labelers of Unknown Expertise [code]
	with Jacob Whitehill, Tingfan Wu, Jacob Bergsma, and Javier Movellan	NIPS 2009
[7] Learning to Make Facial Expressions
	with Tingfan Wu, Nicholas Butko, Marian Bartlett, and Javier Movellan	ICDL 2009
[6] Optimization on a Budget: A Reinforcement Learning Approach
	with Ian Fasel and Javier Movellan	NIPS 2008
[5] Tuning Optimizers for Time-Constrained Problems using Reinforcement Learning
	with Ian Fasel and Javier Movellan	NIPS Workshop on Optimization for Machine Learning 2008
[4] Building a More Effective Teaching Robot via Apprenticeship Learning
	with Jacob Whitehill, Mario Virnes, and Javier Movellan	ICDL 2008
[3] Automatic Cry Detection in Early Childhood Education Settings
	with Javier Movellan	ICDL 2008
[2] Auditory Mood Detection for Social and Educational Robots
	with Ian Fasel and Javier Movellan	ICRA 2008
[1] The RUBI project: a progress report
	with Javier Movellan, Tanaka Fumihide, Ian Fasel, Cynthia Taylor, and Micah Eckhardt	HRI 2007