Android Science: General
Gadde, P., Kharrazi, H., Patel, H., & MacDorman, K. F. (2011). Toward monitoring and increasing exercise adherence in older adults by robotic intervention: A proof of concept study. Journal of Robotics, 2011(Article ID 438514), 1–11. doi: 10.1155/2011/438514
MacDorman, K. F., Gadde, P., Ho, C.-C., Mitchell, W. J., Patel, H., Schermerhorn, P. W., & Scheutz, M. (2010). Probing people’s attitudes and behaviors using humanlike agents. IUPUI Research Day. April 9, 2010. Indianapolis, Indiana.
Wairatpanij, S., Patel, H., Cravens, G., & MacDorman, K. F. (2009). Baby steps: A design proposal for more believable motion in an infant-sized android. In K. Dautenhahn (Ed.), Proceedings of the New Frontiers in Human-Robot Interaction (pp. 139–144). The 23rd Convention of the Society for the Study of Artificial Intelligence and Simulation of Behaviour. April 6–9, 2009. Edinburgh, United Kingdom.
MacDorman, K. F., Wairatpanij, S., Chen, Y., Du, Y., Anwar, S., Yu, C. (2009). Humanizing robots. IUPUI Research Day. April 24, 2009. Indianapolis, Indiana.
MacDorman, K. F., & Ishiguro, H. (2006). The uncanny advantage of using androids in social and cognitive science research. Interaction Studies, 7(3), 297–337. doi: 10.1075/is.7.3.03mac
MacDorman, K. F., & Ishiguro, H. (2006). Opening Pandora’s uncanny box: Reply to commentaries on “The uncanny advantage of using androids in social and cognitive science research.” Interaction Studies, 7(3), 361–368. doi: 10.1075/is.7.3.10mac
MacDorman, K. F., & Ishiguro, H. (2006). Toward social mechanisms of android science: A CogSci 2005 workshop. Interaction Studies, 7(2), 289–296. doi: 10.1075/is.7.2.12mac
MacDorman, K. F. (2006). Introduction to the special issue on android science. Connection Science, 18(4), 313–318. doi: 10.1080/09540090600906258
MacDorman, K. F., & Ishiguro, H. (2004). The study of interaction through the development of androids. Computer Vision and Image Processing Workshop, Information Processing Society of Japan, SIG Technical Reports 2004-CVIM-146 (pp. 69–75), 2004(113). November 11–12, 2004. Tokyo, Japan.
Android Science: Normative Interaction
Matsui, D., Minato, T., MacDorman, K. F., & Ishiguro, H. (2018). Generating natural motion in an android by mapping human motion. In H. Ishiguro & F. D. Libera (Eds.), Geminoid studies: Science and technologies for humanlike teleoperated androids (pp. 57–73). Singapore: Springer.
MacDorman, K. F., & Cowley, S. J. (2008). Long-term relationships as a benchmark for robot personhood. AAAI 2008 Spring Symposium on Emotion, Personality, and Social Behavior (SS-08-04, pp. 143–145). March 26–28, 2008. Stanford, California.
Velonaki, M., Rye, D., Scheding, S., MacDorman, K. F., Cowley, S. J., Ishiguro, H., & Nishio, N. (2008). Engagement, trust and intimacy: Are these the essential elements for a ‘successful’ interaction between a human and a robot? AAAI 2008 Spring Symposium on Emotion, Personality, and Social Behavior (SS-08-04, pp. 141–148). March 26–28, 2008. Stanford, California.
MacDorman, K. F., Ough, S., & Ho, C.-C. (2007). Automatic emotion prediction of song excerpts: Index construction, algorithm design, and empirical comparison. Journal of New Music Research, 36(4), 283–301. doi: 10.1080/09298210801927846
MacDorman, K. F., & Kahn, P. H., Jr. (2007). Introduction to the special issue on psychological benchmarks of human–robot interaction. Interaction Studies, 8(3), 359–362. doi: 10.1075/is.8.3.02mac
Matsui, D., Minato, T., MacDorman, K. F., & Ishiguro, H. (2007). Generating natural motion in an android by mapping human motion. In M. Hackel (Ed.), Humanoid robots: Human-like machines (pp. 351–366). Vienna: I-Tech Education and Publishing.
Cowley, S. J., & MacDorman, K. F. (2006). What baboons, babies, and Tetris players tell us about interaction: A biosocial view of norm-based social learning. Connection Science, 18(4), 363–378. doi: 10.1080/09540090600879703
MacDorman, K. F., & Cowley, S. J. (2006). Long-term relationships as a benchmark for robot personhood. Proceedings of the 15th IEEE International Symposium on Robot and Human Interactive Communication((pp. 378–383). September 6–9, 2006. University of Hertfordshire, Hatfield, UK.
MacDorman, K. F., Minato, T., Shimada, M., Itakura, S., Cowley, S. J., & Ishiguro, H. (2005). Humanity is in the gaze of the beholder: Experiments with androids and people. Proceedings of the Second Conference of the International Society for Gesture Studies (p. 88). June 15–18, 2005. Lyon, France. (Abstract only)
MacDorman, K. F., Minato, T., Shimada, M., Itakura, S., Cowley, S. J., & Ishiguro, H. (2005). Assessing human likeness by eye contact in an android testbed. Proceedings of the XXVII Annual Meeting of the Cognitive Science Society (pp. 1373–1378). July 21–23, 2005. Stresa, Italy. (6 pages)
Matsui, D., Minato, T., MacDorman, K. F., & Ishiguro, H. (2005). Generating natural motion in an android by mapping human motion. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 1089–1096). August 2–6, 2005. Edmonton, Canada. doi: 10.1109/IROS.2005.1545125
Matsui, D., Minato, T., MacDorman, K. F., & Ishiguro, H. (2004). Generating an android’s humanlike motion by mapping from human motion. Proceedings of the Information Processing Society of Japan (pp. 97–100), Kansai Branch. October, 2004. Osaka, Japan. (In Japanese)
Minato, T., MacDorman, K. F., Shimada, M., Itakura, S., Lee, K., & Ishiguro, H. (2004). Evaluating humanlikeness by comparing gaze behaviors elicited by an android and a person. Proceedings of the Second International Workshop on Man–Machine Symbiotic Systems (pp. 373–383). November 23–24, 2004. Kyoto, Japan.
Cowley, S. J., & MacDorman, K. F. (1995). Simulating conversations: The communion game. AI & Society, 9(2–3), 116–137. doi: 10.1007/BF01210600
Uncanny Valley
MacDorman, K. F. (2024). Does mind perception explain the uncanny valley effect? A meta-regression analysis and (de)humanization experiment. Computers in Human Behavior: Artificial Humans. doi: 10.1016/j.chbah.2024.100065
Stein, J.-P., & MacDorman, K. F. (2024). After confronting one uncanny valley, another awaits. Nature Reviews Electrical Engineering. doi: 10.1038/s44287-024-00041-w
Diel, A., Weigelt, S., & MacDorman, K. F. (2022). A meta-analysis of the uncanny valley's independent and dependent variables. ACM Transactions on Human–Robot Interaction, 11(1), 1, 1–33. doi: 10.1145/3470742
Diel, A., & MacDorman, K. F. (2021). Creepy cats and strange high houses: Support for configural processing in testing predictions of nine uncanny valley theories. Journal of Vision, 21(4), 1–20. doi: 10.1167/jov.21.4.1
MacDorman, K. F. (2021). La critique théâtrale de Chikamatsu Monzaemon et sa relation à la vallée de l’étrange : Traduction et commentaire de la préface de Naniwa Miyage. e-Phaïstos : Revue d’histoire des techniques, 9(1), 1–20. doi: 10.4000/ephaistos.8706
MacDorman, K. F. (2019). La vallée de l’étrange de Mori Masahiro : Importance et impact sur l’esthétique et la conception des robots. e-Phaïstos : Revue d’histoire des techniques, 7(2), 1–18. doi: 10.4000/ephaistos.5333
MacDorman, K. F. (2019). In the uncanny valley, transportation predicts narrative enjoyment more than empathy, but only for the tragic hero. Computers in Human Behavior, 94, 140–153. doi: 10.1016/j.chb.2019.01.011
MacDorman, K. F. (2019). Masahiro Mori und das unheimliche Tal: Eine Retrospektive. In K. D. Haensch, L. Nelke, & M. Planitzer (Eds.), Uncanny interfaces (pp. 220–234). Hamburg, Germany: Textem. ISBN 978-3864852176 doi: 10.5281/zenodo.3226274
Mori, M. (2019). Das unheimliche Tal (K. F. MacDorman & V. Schwind, trans.). In K. D. Haensch, L. Nelke, & M. Planitzer (Eds.), Uncanny interfaces (pp. 212–219). Hamburg, Germany: Textem. ISBN 978-3864852176 doi: 10.5281/zenodo.3226987
Dai, Z., & MacDorman, K. F. (2018). The doctor’s digital double: How warmth, competence, and animation promote adherence intention. PeerJ Computer Science, 4(e168), 1–29. doi: 10.7717/peerj-cs.168
Ho, C.-C., & MacDorman, K. F. (2017). Measuring the uncanny valley effect: Refinements to indices for perceived humanness, attractiveness, and eeriness. International Journal of Social Robotics, 9(1), 129–139. doi: 10.1007/s12369-016-0380-9
MacDorman, K. F., & Chattopadhyay, D. (2017). Categorization-based stranger avoidance does not explain the uncanny valley. Cognition, 161, 129–135. doi: 10.1016/j.cognition.2017.01.009
Chattopadhyay, D., & MacDorman, K. F. (2016). Familiar faces rendered strange: Why inconsistent realism drives characters into the uncanny valley. Journal of Vision, 16(11):7, 1–25. doi: 10.1167/16.11.7
MacDorman, K. F., & Chattopadhyay, D. (2016). Reducing consistency in human realism increases the uncanny valley effect; increasing category uncertainty does not. Cognition, 146, 190–205. doi: 10.1016/j.cognition.2015.09.019
MacDorman, K. F., & Entezari, S. (2015). Individual differences predict sensitivity to the uncanny valley. Interaction Studies, 16(2), 141–172. doi: 10.1075/is.16.2.01mac
Patel, H., & MacDorman, K. F. (2015). Sending an avatar to do a human’s job: Compliance with authority persists despite the uncanny valley. Presence, 24(1), 1–23. doi: 10.1162/PRES_a_00212
MacDorman, K. F., Srinivas, P., & Patel, H. (2013). The uncanny valley does not interfere with level 1 visual perspective taking. Computers in Human Behavior, 29(4), 1671–1685. doi: 10.1016/j.chb.2013.01.051
MacDorman, K. F., & Srinivas, P. (2013). Uncanny valley and motor empathy: Identifying movement synchronization with humanlike characters. Grace Hopper Celebration of Women in Computing Conference. October 2–5. Minneapolis, MN.
Srinivas, P., MacDorman, K. F., & Patel, H. (2013). The uncanny valley and motor empathy. IUPUI Research Day. April 5, 2013. Indianapolis, Indiana.
Mitchell, W. J., Szerszen, K. A., Sr., Lu, A. S. & MacDorman, K. F. (2012). A mismatch in the human realism of face and voice produces an uncanny valley. IUPUI Research Day. April 13, 2012. Indianapolis, Indiana.
Srinivas, P., Patel, H., & MacDorman, K. F. (2012). The uncanny valley and empathy: A study of the effects of human likeness and eeriness on empathetic associations during an image categorization task. IUPUI Research Day. April 13, 2012. Indianapolis, Indiana.
Mori, M. (2012). The uncanny valley (K. F. MacDorman & Norri Kageki, Trans.). IEEE Robotics and Automation, 19(2), 98–100. (Original work published in 1970). doi: 10.1109/MRA.2012.2192811
Mitchell, W. J., Szerszen, Sr., K. A., Lu, A. S., Schermerhorn, P. W., Scheutz, M., & MacDorman, K. F. (2011). A mismatch in the human realism of face and voice produces an uncanny valley. i-Perception, 2(1), 10–12. doi: 10.1068/i0415
Srinivas, P., Patel, H., Ho, C.-C., & MacDorman, K. F. (2011). An uncanny valley of visual perspective taking: A study of the effect of character human likeness and eeriness on altercentric intrusions during a dot counting task. IUPUI Research Day. April 8, 2011. Indianapolis, Indiana.
Ho, C.-C., & MacDorman, K. F. (2010). Revisiting the uncanny valley theory: Developing and validating an alternative to the Godspeed indices. Computers in Human Behavior, 26(6), 1508–1518 doi: 10.1016/j.chb.2010.05.015
MacDorman, K. F., Coram, J. A., Ho, C.-C., & Patel, H. (2010). Gender differences in the impact of presentational factors in human character animation on decisions in ethical dilemmas. Presence: Teleoperators and Virtual Environments, 19(3), 213–229. doi: 10.1162/pres.19.3.213
MacDorman, K. F., Vasudevan, S. K., & Ho, C.-C. (2009). Does Japan really have robot mania? Comparing attitudes by implicit and explicit measures. AI & Society, 23(4), 485–510. doi: 10.1007/s00146-008-0181-2
MacDorman, K. F., Green, R. D., Ho, C.-C., & Koch, C. (2009). Too real for comfort: Uncanny responses to computer generated faces. Computers in Human Behavior, 25(3), 695–710. doi: 10.1016/j.chb.2008.12.026
Green, R. D., MacDorman, K. F., Ho, C.-C., & Vasudevan, S. K. (2008). Sensitivity to the proportions of faces that vary in human likeness. Computers in Human Behavior, 24(5), 2456–2474. doi: 10.1016/j.chb.2008.02.019
Ho, C.-C., MacDorman, K. F., & Pramono, Z. A. D. (2008). Human emotion and the uncanny valley: A GLM, MDS, and ISOMAP analysis of robot video ratings. Proceedings of the Third ACM/IEEE International Conference on Human–Robot Interaction (pp. 169–176). March 11–14, 2008. Amsterdam. doi: 10.1145/1349822.1349845
MacDorman, K. F. (2007). Charting the uncanny valley. International Conference on Computer Graphics and Interactive Techniques ACM SIGGRAPH 2007 panels. August 5–9. San Diego, USA.
MacDorman, K. F. (2007). The future of very humanlike robots in science and society. 38th International Symposium on Robotics. June 12–14. Chicago, USA.
MacDorman, K. F. (2007). The uncanny valley. 2007 NMC Summer Conference. June 6–9, 2007. Indianapolis, USA.
MacDorman, K. F. (2006). Subjective ratings of robot video clips for human likeness, familiarity, and eeriness: An exploration of the uncanny valley. ICCS/CogSci-2006 Long Symposium: Toward Social Mechanisms of Android Science (pp. 26–29). July 26, 2006. Vancouver, Canada.
MacDorman, K. F. (2005). Androids as experimental apparatus: Why is there an uncanny valley and can we exploit it? CogSci-2005 Workshop: Toward Social Mechanisms of Android Science (pp. 108–118). July 25–26, 2005. Stresa, Italy.
MacDorman, K. F. (2005). Mortality salience and the uncanny valley. Proceedings of the IEEE-RAS International Conference on Humanoid Robots (pp. 339–405). December 5–7, 2005. Tsukuba, Japan. doi: 10.1109/ICHR.2005.1573600
Symbol Emergence
Belpaeme, T., Cowley, S. J., & MacDorman, K. F. (Eds.). (2009). Symbol grounding. Amsterdam: John Benjamins. (167 pages)
Chalodhorn, R., MacDorman, K. F., & Asada, M. (2009). Humanoid robot motion recognition and reproduction. Advanced Robotics, 23(3), 349–366. doi: 10.1163/156855308X397569
MacDorman, K. F. (2007). Life after the symbol system metaphor. Interaction Studies, 8(1), 143–158. doi: 10.1075/bct.21.08mac
MacDorman, K. F., Nobuta, H., Koizumi, S., & Ishiguro, H. (April 2007). Memory-based attention control in a distributed vision system that recognizes group activity at a subway station. IEEE Multimedia, 14(2), 38–49. doi: 10.1109/MMUL.2007.39
Chalodhorn, R., MacDorman, K. F., & Asada, M. (2004). An algorithm that recognizes and reproduces distinct types of humanoid motion based on periodically-constrained nonlinear PCA. In D. Nardi, M. Riedmiller, C. Sammut, & J. Santos-Victor (Eds.), RoboCup 2004: Robot Soccer World Cup VIII (Lecture Notes in Artificial Intelligence, Vol. 3276, pp. 370–380). Berlin: Springer.
Chalodhorn, R., MacDorman, K. F., & Asada, M. (2004). An algorithm that recognizes and reproduces distinct types of humanoid motion based on periodically constrained nonlinear PCA. Proceedings of the Eighth RoboCup International Symposium (pp. 370–380). July 5–7, 2004. Lisbon, Portugal.
Chalodhorn, R., MacDorman, K. F., & Asada, M. (2004). Automatic extraction of abstract actions from humanoid motion data. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 2781–2786). September 28–October 2, 2004. Sendai, Japan.
MacDorman, K. F., Chalodhorn, R., & Asada, M. (2004). Periodic nonlinear principal component neural networks for humanoid motion segmentation, generalization, and generation. Proceedings of the Seventeenth International Conference on Pattern Recognition (pp. 537–540). August 23–26, 2004. Cambridge, UK.
MacDorman, K. F., Chalodhorn, R., Ishiguro, H., & Asada, M. (2004). Protosymbols that integrate recognition and response. Proceedings of the Fourth International Workshop on Epigenetic Robotics. August 25–27, 2004. Genoa, Italy.
MacDorman, K. F., Nobuta, H., Ikeda, T., Koizumi, S., & Ishiguro, H. (2004). A memory-based distributed vision system that employs a form of attention to recognize group activity at a subway station. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (Vol. 2, pp. 1704–1709). September 28–October 2, 2004. Sendai, Japan.
MacDorman, K. F., Nobuta, H., Minato, T., & Ishiguro, H. (2004). Memory-based recognition of human behavior based on sensory data of high dimensionality. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (Vol. 1, pp. 571–576). September 28–October 2, 2004. Sendai, Japan.
MacDorman, K. F., Chalodhorn, R., & Ishiguro, H. (2004). Learning to recognize and reproduce abstract actions from proprioception. Third International Conference on Development and Learning: Developing Social Brains. October 20–22, 2004. La Jolla, California.
Marubayashi, N., & MacDorman, K. F. (2004). Inquiry into the mechanism of symbol emergence based on affect and its robotic implementation. Proceedings of the Second International Symposium on Emergent Mechanisms of Communication in the Brain. March 2004. Awaji Yumebutai, Japan.
Asada, M., MacDorman, K. F., Ishiguro, H., & Kuniyoshi, Y. (2001). Cognitive developmental robotics as a new paradigm for the design of humanoid robots. Robotics and Autonomous Systems, 37(2–3), 185–193.
MacDorman, K. F., Tatani, K., Miyazaki, Y., Koeda, M., & Nakamura, Y. (2001). Protosymbol emergence based on embodiment: Robot experiments. ICRA 2001: Proceedings of the IEEE International Conference on Robotics and Automation (pp. 1968–1974). May 21–26, 2001. Seoul National University, Seoul, Korea.
Tatani, K., MacDorman, K. F., & Nakamura, Y. (2001).原始記号を学習するサバイバルを目的とした移動ロボット A mobile robot that learns protosymbols for survival. Proceedings of the Japan Society of Mechanical Engineers Conference on Robotics and Mechatronics (ROBOMEC 2001), 608(2P1-B10), 1037-1802.
Asada, M., MacDorman, K. F., Ishiguro, H., & Kuniyoshi, Y. (2000). Cognitive developmental robotics as a new paradigm for the design of humanoid robots. Humanoids 2000: Proceedings of the First IEEE-RAS International Conference on Humanoid Robots, September 7–8, 2000. MIT, Cambridge, MA.
MacDorman, K. F. (2000). Responding to affordances: Learning and projecting a sensorimotor mapping. Proceedings of IEEE International Conference on Robotics and Automation (pp. 3253–3259). April 24–28, 2000. San Francisco, California.
MacDorman, K. F., Tatani, K., & Nakamura, Y. (2000). Emergence of primitive symbols from robot dynamics. Proceedings of the 18th Annual Conference of the Robotics Society of Japan (pp. 787–788). September 12–14, 2000. Ritsumeikan University, Kusatsu, Japan. (in Japanese)
MacDorman, K. F., Tatani, K., Miyazaki, Y., & Koeda, M. (2000). Proto-symbol emergence. Proceedings of IROS-2000: IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 1619–1625). October 30–November 5, 2000. Kagawa University, Takamatsu, Japan.
MacDorman, K. F. (1999). Grounding symbols through sensorimotor integration. Journal of the Robotics Society of Japan, 17(1), 20–24. doi: 10.7210/jrsj.17.20
Nakamura, T., Sato, T., Kuniyoshi, Y., Hiraki, K. F., Shibata, T., Asada, M., MacDorman, K. F., & Tani, J. (1999). Why is cognitive robotics promising? (なぜ認知ロボティクスは有望なのか?) Journal of the Robotics Society of Japan, 17(1), 38–43. (in Japanese) doi: 10.7210/jrsj.17.38
MacDorman, K. F. (1998). Feature learning, multiresolution analysis, and symbol grounding: A peer commentary on Schyns, Goldstone, and Thibaut’s “The development of features in object concepts.” Behavioral and Brain Sciences, 21(1), 32–33.
MacDorman, K. F., & Miyazaki, Y. (1998). Robots that recognize affordances: A predictive approach. Proceedings of the 16th Annual Conference of the Robotics Society of Japan (Vol. 2, pp. 901–902). September 18–20, 1998. Hokkaido University, Sapporo, Japan.
MacDorman, K. F. (1997). Memory must also mesh affect: A peer commentary on Glenberg’s “What memory is for.” Behavioral and Brain Sciences, 20(1), 29.
MacDorman, K. F. (1997). A path to symbol-grounded robots. Meiji University International Exchange Programs Guest Lecture Series, 2. Center for International Programs, Meiji University.
MacDorman, K. F. (1997). How to ground symbols adaptively. In S. O’Nuallain, P. McKevitt, & E. MacAogain (Eds.), Readings in computation, content and consciousness (pp. 137–178). Amsterdam: John Benjamins.
MacDorman, K. F. (1997). Symbol grounding: Learning categorical and sensorimotor predictions for coordination in autonomous robots. Technical Report No. 423. Computer Laboratory, Cambridge (e-mail librarian@cl.cam.ac.uk).
MacDorman, K. F. (1995). How to ground symbols adaptively: A preliminary report. Reaching for Mind: Foundations of Cognitive Science Workshop, AISB-95: Tenth Biennial Conference on Artificial Intelligence and Cognitive Science. April 3–4, 1995. Sheffield, UK.
Sensorimotor Learning
Oyama, E., Maeda, T., Gan, J. Q., Rosales, E. M., MacDorman, K. F., Tachi, S. & Agah, A. (2005). Inverse kinematics learning for robotic arms with fewer degrees of freedom by modular neural network systems. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 833–840). August 2–6, 2005. Edmonton, Canada. doi: 10.1109/IROS.2005.1545084
MacDorman, K. F. (2003). Pattern recognition and intelligent systems: Partition networks. Proceedings of the Conference of the Information Processing Society (pp. 87–92), Kansai Branch. (In Japanese)
Oyama, E., Maeda, T. Tachi, S., MacDorman, K. F., & Agah, A. (2002). On the use of forward kinematic models in visually guided hand position control: Analysis based on ISLES model. Neurocomputing, 44–46, 965–972.
Oyama, E., MacDorman, K. F., Maeda, T., Tachi, S., & Agah, A. (2002). A new model of the visual feedback coordinate transformation in humans based on disturbance noise and feedback error that accounts for time delays. IEEE/RSJ International Conference on Intelligent Robots and Systems (Vol. 2, pp. 950–957). September 30–October 4, 2002. EPFL, Lausanne, Switzerland.
Oyama, E., Maeda, T., Tachi, S., MacDorman, K. F., & Agah, A. (2002). On the use of forward kinematic models in visually guided hand position control: Analysis based on ISLES model. In J. M. Bower (Ed.), Computational Neuroscience: Trends in Research 2002 (pp. 965–972). New York: Elsevier. doi: 10.1016/S0925-2312(02)00498-8
Oyama, E., MacDorman, K. F., Agah, A., Maeda, T., & Tachi, S. (2001). Coordinate transformation learning of a hand position feedback controller with time delay. Neurocomputing, 38–40(1–4), 1503–1509.
Oyama, E., Agah, A., MacDorman, K. F., Maeda, T., & Tachi, S. (2001). A modular neural network architecture for inverse kinematics model learning. Neurocomputing, 38–40(1–4), 797–805.
Oyama, E., Chong, N. Y., Agah, A., Maeda, T., Tachi, S., & MacDorman, K. F. (2001). Learning a coordinate transformation for a human visual feedback controller based on disturbance noise and the feedback error signal. ICRA 2001: Proceedings of the IEEE International Conference on Robotics and Automation (Vol. 4, pp. 4186–4193). May 21–26, 2001. Seoul National University, Seoul, Korea.
Tatani, K., & MacDorman, K. F. (1999). Planning to learn versus learning to plan. Proceedings of the 17th Annual Conference of the Robotics Society of Japan (pp. 641–642). September 9–11, 1999. Tokai University, Hiratsuka. (in Japanese)
MacDorman, K. F. (1999). Heuristics for projecting a sensorimotor mapping. Proceedings of ISR-99: 30th International Symposium on Robotics (pp. 169–176). October 27–29, 1999. Tokyo.
MacDorman, K. F. (1999). Partition nets: An efficient on-line learning algorithm. Proceedings of ICAR-99: Ninth International Conference on Advanced Robotics (pp. 529–535), October 25–27, 1999. Tokyo.
Mitsuda, T., Miyazaki, Y., Maru, N., MacDorman, K. F., & Miyazaki, F. (1998). Precise planar positioning using visual servoing based on coarse optical flow. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (Vol. 2, pp. 712–717). October 13–18, 1998. Victoria, Canada.
Mitsuda, T., Miyazaki, Y., Maru, N., MacDorman, K. F., Nishikawa, A., & Miyazaki, F. (1999). Visual servoing based on coarse optical flow. Proceedings of the Fourteenth IFAC World Congress (Vol. B, pp. 53–58). Beijing.
Nakawaki, D., Cisek, R., MacDorman, K. F., Joo, S., & Miyazaki, F. (1998). Coaching information determined from dynamic modeling based on a total energy analysis. Proceedings of the 16th Annual Conference of the Robotics Society of Japan (Vol. 1, pp. 45–46). September 18–20, 1998. Hokkaido University, Sapporo, Japan.
Consciousness
MacDorman, K. F. (2004). Extending the medium hypothesis: The Dennett-Mangan controversy and beyond. The Journal of Mind and Behavior, 25(3), 237–257.
MacDorman, K. F. (2004). What “unfilling in” says about the nature of representation in the brain. Proceedings of the Second International Symposium on Emergent Mechanisms of Communication in the Brain. March 1–3, 2004. Awaji Yumebutai, Japan.
Sommerhoff, G., & MacDorman, K. F. (1994). An account of consciousness in physical and functional terms: A target for research in the neurosciences. Integrative Physiological and Behavioral Science, 29(2), 151–181. doi: 10.1007/BF02691012
Bioinformatics
Huang, H., Wu, X., Sonachalam, M., Mandape, S. N., Pandey, R., MacDorman, K. F., Wan, P. & Chen, J. Y. (2012). PAGED: A pathway and gene-set enrichment database to enable molecular phenotype discoveries. BMC Bioinformatics, 13(Suppl 15), S2. doi: 10.1186/1471-2105-13-S15-S2
Wu, X., Huang, H., Sonachalam, M., Pandey, R., MacDorman, K. F., & Chen, J. (2012). Network-mapping proteomics data analysis for identifying colorectal cancer biomarker candidates. Great Lakes Bioinformatics Conference (International Society of Computational Biology). May 15–17, 2012. Ann Arbor, Michigan.
Wee, K. B., Pramono, Z. A. D., Wang, J. L., MacDorman, K. F., Lai, P. S., & Yee, W. C. (2008). Dynamics of co-transcriptional pre-mRNA folding influences the induction of dystrophin exon skipping by antisense oligonucleotides. PLoS ONE 3(3), e1844, 1–14. PMID: 18365002 doi: 10.1371/journal.pone.0001844
Wee, K. B., Pramono, Z. A. D., Wang, J. L., MacDorman, K. F., Yee, W. C., & Lai, P. S. (2007). Accounting for pre-mRNA co-transcriptional folding in selection of antisense oligonucleotide targets for induction of exon skipping in DMD. Neuromuscular Disorders, 17(9–10), 782–783. doi: 10.1016/j.nmd.2007.06.078
Wee, K. B., Pramono, Z. A. D., Wang, J. L., MacDorman, K. F., Yee, W. C., & Lai, P. S. (2007). Accounting for pre-mRNA co-transcriptional folding in selection of antisense oligonucleotide targets for induction of exon skipping in DMD. Proceedings of the 12th International Congress of the World Muscle Society. October 17–20, 2007. Taormina, Italy.
Human-Computer Interaction
Patnaik, A., Bhuyan, M. K., & MacDorman, K. F. (2024). A two-branch multi-scale residual attention network for single image super-resolution in remote sensing imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. doi: 10.1109/JSTARS.2024.3371710
Dutta, H. P. J., Bhuyan, M. K., Neog, D. R., MacDorman, K. F., and Laskar, R. H. (2023). Efficient hand segmentation for rehabilitation tasks using a convolution neural network with attention. Expert Systems with Applications, 234, 121046. doi: 10.1016/j.eswa.2023.121046
Dutta, H. P. J., Bhuyan, M. K., Neog, D. R., MacDorman, K. F., & Laskar, R. H. (2023). Patient assistance system based on hand gesture recognition. IEEE Transactions on Instrumentation and Measurement, 72, 1–13, Art. No. 5018013. doi: 10.1109/TIM.2023.3282655
Dutta, H. P. J., Bhuyan, M. K., Neog, D. R., MacDorman, K. F., and Laskar, R. H. (2023). A hand gesture-operated system for rehabilitation using an end-to-end detection framework. IEEE Transactions on Artificial Intelligence. doi: 10.1109/TAI.2023.3251309
Chakraborty, B. K., Bhuyan, M. K., & MacDorman, K. F. (2021). Skin detection in video under uncontrolled illumination. Multimedia Tools and Applications, 80, 24319–24341. doi: 10.1007/s11042-021-10728-z
Dai, Z., & MacDorman, K. F. (2021). Creepy, but persuasive: In a virtual consultation, physician bedside manner, rather than the uncanny valley, predicts adherence. Frontiers in Virtual Reality, 2 (739038), 1–18. doi: 10.3389/frvir.2021.739038
Lin, C., Šabanović, S., Dombrowski, L., Miller, A. D., Brady, E., & MacDorman, K. F. (2021). Parental acceptance of children’s storytelling robots: A projection of the uncanny valley of AI. Frontiers in Robotics and AI, 8(579993), 1–15. doi: 10.3389/frobt.2021.579993
Spatola, N. & MacDorman, K. F. (2021). Why real citizens would turn to artificial leaders. ACM Digital Government: Research and Practice, 2(3), 26, 1–24. doi: 10.1145/3447954
Lin, C., MacDorman K. F., Šabanović, S., Miller, A. D., & Brady, E. L. (2020). Parental expectations, concerns, and acceptance of storytelling robots for children. HRI ’20: Companion of the 2020 ACM/IEEE International Conference on Human–Robot Interaction (pp. 346–348), March 2020. doi: 10.1145/3371382.3378376
Chakraborty, B. K., Sarma, D., Bhuyan, M. K., & MacDorman, K. F. (2017). A review of constraints on vision-based gesture recognition for human–computer interaction. IET Computer Vision, 11(8), 1–13. doi: 10.1049/iet-cvi.2017.0052
Bhuyan, M. K., MacDorman, K. F., Kar, M. K., Neog, D. R., Lovell, B. C., & Gadde, P. (2015). Hand pose recognition from monocular images by geometrical and texture analysis. Journal of Visual Languages and Computing, 28, 39–55. doi: 10.1016/j.jvlc.2014.12.001
Bhuyan, M. K., Kumar, D. A., MacDorman, K. F., & Iwahori, Y. (2014). A novel set of features for continuous hand gesture recognition. Journal on Multimodal User Interfaces, JMUI-D-12-00038R3. doi: 10.1007/s12193-014-0165-0
Patel, H., Bayliss L. C., Ivory, J. D., Woodard, K., & McCarthy, A., & MacDorman, K. F. (2014). Receptive to bad reception: Jerky motion can make persuasive messages more effective. Computers in Human Behavior, 32, 32–39. doi: 10.1016/j.chb.2013.11.012
Bayliss, L., McCarthy, A., Woodard, K., Dennis, L., Ivory, J. D., Patel, H., & MacDorman, K. F. (2012). Receptive to bad reception: Can jerky video make persuasive messages more effective? Proceedings of the Conference of the International Communication Association, Information Systems Division. May 24–28, 2012. Phoenix, Arizona.
BenMessaoud, C. B., Kharrazi, H., & MacDorman, K. F. (2011). Facilitators and barriers to adopting robotic-assisted surgery: Contextualizing the Unified Theory of Acceptance and Use of Technology. PLoS ONE, 6(1): e16395. doi: 10.1371/journal.pone.0016395
Faiola, A., Ho, C.-C., Tarrant, M. A., & MacDorman, K. F. (2011). The aesthetic dimensions of US and South Korean responses to web home pages: A cross-cultural comparison. International Journal of Human-Computer Interaction, 27(2), 131–150. doi: 10.1080/10447318.2011.537173
MacDorman, K. F., Whalen, T. J., Ho, C.-C., & Patel, H. (2011). An improved scale for measuring usability from novice and expert performance. International Journal of Human-Computer Interaction, 27(3), 1–23. doi: 10.1080/10447318.2011.540472
Mitchell, W. J., Ho, C.-C., Patel, H., & MacDorman, K. F. (2011). Does social desirability bias favor humans? Explicit–implicit evaluations of synthesized speech support a new HCI model of impression management. Computers in Human Behavior, 27(1), 402–412. doi: 10.1016/j.chb.2010.09.002
Pfaff, M. S., Newlon, C. M., Patel, H., & MacDorman, K. F. (2010). Information fusion for civilians: The prospects of mega-collaboration. In Hall, D. L., & Jordan, J. (Eds.), Human centered information fusion (pp. 211–229). Norwood, Mass.: Artech House.
Newlon, C. M., Pfaff, M., Patel, H., de Vreede, G.-J., & MacDorman, K. F. (2009). Mega-collaboration: The inspiration and development of an interface for large-scale disaster response. In Proceedings of the Sixth International ISCRAM Conference. May 10–13, 2009. Gothenburg, Sweden. (8 pages)
Faiola, A., & MacDorman, K. F. (2008). The influence of holistic and analytic cognitive styles on online information design: Toward a communication theory of cultural cognitive design. Information, Communication & Society, 11(3), 46–72. doi: 10.1080/13691180802025418
Newlon, C. M., Faiola, A., & MacDorman, K. F. (2008). Building the mega-collaboration interface: Behavioral, cultural, and cognitive factors in visualization support. Proceedings of the 12th International Conference on Information Visualisation (IV2008, pp. 509–514). July 8–11, 2008. London.
Newlon, C. M., MacDorman, K. F., & Scerri, P. (2008). A new model for mega-collaboration. HCI for Emergencies, ACM SIGCHI (pp. 1–7). April 5–10, 2008. Florence, Italy.