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INFORMATION FOR

Frederick Shic, PhD

Director, Technology and Innovation Laboratory (TIL); Co-Director, Yale Early Social Cognition Laboratory (YESCog)

Research Summary

Fred focuses on the exploration of new technologies and methodologies for enriching both our understanding of ASD and the lives of children with ASD. His current research interests include using eye-tracking to study visual social attention in ASD, computational modeling to describe gaze patterns in terms of perceptual characteristics, the development of gaze contingent interactive technologies, using electrodermal activity to index autonomic arousal in infants and toddlers, and the development of specialized software applications for both education and augmentative and alternative communication.

Specialized Terms: Autism; Eye-tracking; Gaze-contingent technology; Magnetic resonance spectroscopy; Galvanic skin response; Electrodermal activity; Augmentative and alternative communication

Coauthors

Research Interests

Autistic Disorder; Child Psychiatry; Galvanic Skin Response; Magnetic Resonance Spectroscopy; Technology

Selected Publications

  • The Uncanniness of Face SwapsWilson E, Persaud A, Esposito N, Joerg S, Patra R, Shic F, Skytta J, Jain E. The Uncanniness of Face Swaps Journal Of Vision 2022, 22: 4225. DOI: 10.1167/jov.22.14.4225.
  • A Functional Model for Studying Common Trends Across Trial Time in Eye Tracking ExperimentsDong M, Telesca D, Sugar C, Shic F, Naples A, Johnson S, Li B, Atyabi A, Xie M, Webb S, Jeste S, Faja S, Levin A, Dawson G, McPartland J, Şentürk D. A Functional Model for Studying Common Trends Across Trial Time in Eye Tracking Experiments Statistics In Biosciences 2022, 1-27. DOI: 10.1007/s12561-022-09354-6.
  • Calibration Error Prediction: Ensuring High-Quality Mobile Eye-TrackingLi B, Snider J, Wang Q, Mehta S, Foster C, Barney E, Shapiro L, Ventola P, Shic F. Calibration Error Prediction: Ensuring High-Quality Mobile Eye-Tracking 2022, 1-7. DOI: 10.1145/3517031.3529634.
  • Stratification of Children with Autism Spectrum Disorder through fusion of temporal information in eye-gaze scan-pathsAtyabi A, Shic F, Jiang J, Foster C, Barney E, Kim M, Li B, Ventola P, Chen C. Stratification of Children with Autism Spectrum Disorder through fusion of temporal information in eye-gaze scan-paths ACM Transactions On Knowledge Discovery From Data 2022 DOI: 10.1145/3539226.
  • Style transformed synthetic images for real world gaze estimation by using residual neural network with embedded personal identitiesWang Q, Wang H, Dang R, Zhu G, Pi H, Shic F, Hu B. Style transformed synthetic images for real world gaze estimation by using residual neural network with embedded personal identities Applied Intelligence 2022, 53: 1-16. DOI: 10.1007/s10489-022-03481-9.
  • Learning Oculomotor Behaviors from ScanpathLi B, Nuechterlein N, Barney E, Foster C, Kim M, Mahony M, Atyabi A, Feng L, Wang Q, Ventola P, Shapiro L, Shic F. Learning Oculomotor Behaviors from Scanpath 2021, 407-415. DOI: 10.1145/3462244.3479923.
  • Comparing Robustness and Efficiency of Closed Eye Detection in ImagesWang H, Li B, Shic F, Hu B, Wang Q. Comparing Robustness and Efficiency of Closed Eye Detection in Images 2021, 00: 6-12. DOI: 10.1109/icivc52351.2021.9526969.
  • Magnetic Resonance SpectroscopyShic F. Magnetic Resonance Spectroscopy 2021, 2789-2795. DOI: 10.1007/978-3-319-91280-6_1946.
  • Video Games, Use ofShic F. Video Games, Use of 2021, 5057-5067. DOI: 10.1007/978-3-319-91280-6_302.
  • Upright/Inverted FiguresShic F. Upright/Inverted Figures 2021, 4964-4965. DOI: 10.1007/978-3-319-91280-6_300.
  • Eye-TrackingShic F. Eye-Tracking 2021, 1930-1936. DOI: 10.1007/978-3-319-91280-6_1474.
  • Selection of Eye-Tracking Stimuli for Prediction by Sparsely Grouped Input Variables for Neural Networks: towards Biomarker Refinement for AutismLi B, Barney E, Hudac C, Nuechterlein N, Ventola P, Shapiro L, Shic F. Selection of Eye-Tracking Stimuli for Prediction by Sparsely Grouped Input Variables for Neural Networks: towards Biomarker Refinement for Autism 2020, 1-8. DOI: 10.1145/3379155.3391334.
  • P.507 Visual activity monitoring and social attention in autism spectrum disorder: effect of context and ageKaliukhovich D, Manyakov N, Bangerter A, Ness S, Skalkin A, Boice M, Shic F, Pandina G. P.507 Visual activity monitoring and social attention in autism spectrum disorder: effect of context and age European Neuropsychopharmacology 2019, 29: s357-s358. DOI: 10.1016/j.euroneuro.2019.09.513.
  • A Facial Affect Analysis System for Autism Spectrum DisorderLi B, Mehta S, Aneja D, Foster C, Ventola P, Shic F, Shapiro L. A Facial Affect Analysis System for Autism Spectrum Disorder 2019, 00: 4549-4553. DOI: 10.1109/icip.2019.8803604.
  • Social Influences on Executive Functioning in AutismLi B, Atyabi A, Kim M, Barney E, Ahn A, Luo Y, Aubertine M, Corrigan S, St. John T, Wang Q, Mademtzi M, Best M, Shic F. Social Influences on Executive Functioning in Autism 2018, 1-13. DOI: 10.1145/3173574.3174017.
  • 5.30 Prospective, Observational Cohort Study of Jake®, an Autism Knowledge Engine: Correlation of Behavior Ratings With Eye TrackingPandina G, Manyakov N, Bangerter A, Lewin D, Jagannatha S, Boice M, Skalkin A, Dawson G, Goodwin M, Hendren R, Leventhal B, Shic F, Ness S. 5.30 Prospective, Observational Cohort Study of Jake®, an Autism Knowledge Engine: Correlation of Behavior Ratings With Eye Tracking Journal Of The American Academy Of Child & Adolescent Psychiatry 2017, 56: s263-s264. DOI: 10.1016/j.jaac.2017.09.313.
  • 3.31 Building Predictive Models for Autism Spectrum Disorder Based on Biosensor DataJagannatha S, Sargsyan D, Manyakov N, Skalkin A, Bangerter A, Ness S, Lewin D, Dawson G, Shic F, Goodwin M, Hendren R, Leventhal B, Pandina G. 3.31 Building Predictive Models for Autism Spectrum Disorder Based on Biosensor Data Journal Of The American Academy Of Child & Adolescent Psychiatry 2017, 56: s213. DOI: 10.1016/j.jaac.2017.09.179.
  • P.7.f.002 Prospective, observational cohort study of JAKE™, an autism knowledgePandina G, Manyakov N, Bangerter A, Lewin D, Jagannatha S, Boice M, Skalkin A, Dawson G, Goodwin M, Hendren R, Leventhal B, Shic F, Ness S. P.7.f.002 Prospective, observational cohort study of JAKE™, an autism knowledge European Neuropsychopharmacology 2017, 27: s1118. DOI: 10.1016/s0924-977x(17)31937-5.
  • An Exploratory Analysis Targeting Diagnostic Classification of AAC App Usage PatternsAtyabi A, Li B, Ahn Y, Kim M, Barney E, Shic F. An Exploratory Analysis Targeting Diagnostic Classification of AAC App Usage Patterns 2017, 1633-1640. DOI: 10.1109/ijcnn.2017.7966047.
  • P.1.c.012 A multi-center, observational study to explore the relationship between exploratory biomarkers and functional dimensions in adults with autistic spectrum disordersDel Valle Rubido M, Hollander E, McCracken J, Shic F, Noeldeke J, Boak L, Khwaja O, Sadikhov S, Fontoura P, Umbricht D. P.1.c.012 A multi-center, observational study to explore the relationship between exploratory biomarkers and functional dimensions in adults with autistic spectrum disorders European Neuropsychopharmacology 2016, 26: s193. DOI: 10.1016/s0924-977x(16)31031-8.
  • 47.2 EYE TRACKING IN EARLY AUTISM SPECTRUM DISORDER: UTILITY AS A MARKER IN CLINICAL TRIALSShic F. 47.2 EYE TRACKING IN EARLY AUTISM SPECTRUM DISORDER: UTILITY AS A MARKER IN CLINICAL TRIALS Journal Of The American Academy Of Child & Adolescent Psychiatry 2016, 55: s333. DOI: 10.1016/j.jaac.2016.07.397.
  • 1.32 THE JANSSEN AUTISM KNOWLEDGE ENGINE (JAKE™): A SET OF TOOLS AND TECHNOLOGIES TO ASSESS POTENTIAL BIOMARKERS FOR AUTISM SPECTRUM DISORDERSNess S, Manyakov N, Bangerter A, Lewin D, Jagannatha S, Boice M, Skalkin A, Dawson G, Goodwin M, Hendren R, Leventhal B, Shic F, Cioccia W, Pandina G. 1.32 THE JANSSEN AUTISM KNOWLEDGE ENGINE (JAKE™): A SET OF TOOLS AND TECHNOLOGIES TO ASSESS POTENTIAL BIOMARKERS FOR AUTISM SPECTRUM DISORDERS Journal Of The American Academy Of Child & Adolescent Psychiatry 2016, 55: s110. DOI: 10.1016/j.jaac.2016.09.033.
  • Mobile Ascertainment of Smoking Status Through Breath: A Machine Learning ApproachValencia S, Smith M, Atyabi A, Shic F. Mobile Ascertainment of Smoking Status Through Breath: A Machine Learning Approach 2016, 1-7. DOI: 10.1109/uemcon.2016.7777917.
  • Hybrid Calibration for Eye Tracking: Smooth Pursuit Trajectory with Anchor PointsWang Q, Barney E, Wall C, DiNicola L, Foster C, Ahn Y, Li B, Katarzyna C, Shic F. Hybrid Calibration for Eye Tracking: Smooth Pursuit Trajectory with Anchor Points Journal Of Vision 2016, 16: 1355. DOI: 10.1167/16.12.1355.
  • A Thermal Emotion Classifier for Improved Human-Robot InteractionBoccanfuso L, Wang Q, Leite I, Li B, Torres C, Chen L, Salomons N, Foster C, Barney E, Ahn Y, Scassellati B, Shic F. A Thermal Emotion Classifier for Improved Human-Robot Interaction 2016, 718-723. DOI: 10.1109/roman.2016.7745198.
  • Modified DBSCAN algorithm on oculomotor fixation identificationLi B, Wang Q, Barney E, Hart L, Wall C, Chawarska K, de Urabain I, Smith T, Shic F. Modified DBSCAN algorithm on oculomotor fixation identification 2016, 337-338. DOI: 10.1145/2857491.2888587.
  • Thermographic eye trackingWang Q, Boccanfuso L, Li B, Ahn A, Foster C, Orr M, Scassellati B, Shic F. Thermographic eye tracking 2016, 307-310. DOI: 10.1145/2857491.2857543.
  • Optimality of the distance dispersion fixation identification algorithmLi B, Wang Q, Boccanfuso L, Shic F. Optimality of the distance dispersion fixation identification algorithm 2016, 339-340. DOI: 10.1145/2857491.2888588.
  • Emotional Robot to Examine Different Play Patterns and Affective Responses of Children with and Without ASDBoccanfuso L, Barnev E, Foster C, Ahn Y, Chawarska K, Scassellati B, Shic F. Emotional Robot to Examine Different Play Patterns and Affective Responses of Children with and Without ASD 2016, 19-26. DOI: 10.1109/hri.2016.7451729.
  • P.7.d.011 Results from a phase I proof-of-mechanism study with a vasopressin 1A receptor antagonist in autism spectrum disorderDel Valle Rubido M, Umbricht D, Shic F, McCracken J, Scahill L, Khwaja O, Squassante L, Boak L, Bolognani F, Fontoura P, Wall C, Jou R, Loomis R, Lyons M, Gavaletz A, Cowen J, Apelian T, Jeste S, Ferretti C, Taylor B, Berlin G, Noone R, Antar L, Hollander E. P.7.d.011 Results from a phase I proof-of-mechanism study with a vasopressin 1A receptor antagonist in autism spectrum disorder European Neuropsychopharmacology 2015, 25: s646-s647. DOI: 10.1016/s0924-977x(15)30917-2.
  • Interactive eye tracking for gaze strategy modificationWang Q, Celebi F, Flink L, Greco G, Wall C, Prince E, Lansiquot S, Chawarska K, Kim E, Boccanfuso L, DiNicola L, Shic F. Interactive eye tracking for gaze strategy modification 2015, 247-250. DOI: 10.1145/2771839.2771888.
  • Linking Volitional Preferences for Emotional Information to Social Difficulties A Game Approach using the Microsoft KinectWeng M, Walt C, Kim E, Whitaker L, Perlmutter M, Wang Q, Lebowitz E, Shic F. Linking Volitional Preferences for Emotional Information to Social Difficulties A Game Approach using the Microsoft Kinect 2015, 588-594. DOI: 10.1109/acii.2015.7344629.
  • Autonomously Detecting Interaction with an Affective Robot to Explore Connection to Developmental AbilityBoccanfuso L, Kim E, Snider J, Wang Q, Wall C, DiNicola L, Greco G, Shic F, Scassellati B, Flink L, Lansiquot S, Chawarska K, Ventola P. Autonomously Detecting Interaction with an Affective Robot to Explore Connection to Developmental Ability 2015, 1-7. DOI: 10.1109/acii.2015.7344543.
  • Potential Clinical Impact of Positive Affect in Robot Interactions for Autism InterventionKim E, Daniell C, Makar C, Elia J, Scassellati B, Shic F. Potential Clinical Impact of Positive Affect in Robot Interactions for Autism Intervention 2015, 8-13. DOI: 10.1109/acii.2015.7344544.
  • Mapping Connections between Biological-Emotional Preferences and Affective Recognition an Eye-Tracking Interface for Passive Assessment of Emotional CompetencyWall C, Wang Q, Weng M, Kim E, Whitaker L, Perlmutter M, Shic F. Mapping Connections between Biological-Emotional Preferences and Affective Recognition an Eye-Tracking Interface for Passive Assessment of Emotional Competency 2015, 21-27. DOI: 10.1109/acii.2015.7344546.
  • Development of an untethered, mobile, low-cost head-mounted eye trackerKim E, Naples A, Gearty G, Wang Q, Wallace S, Wall C, Kowitt J, Friedlaender L, Reichow B, Volkmar F, Shic F, Perlmutter M. Development of an untethered, mobile, low-cost head-mounted eye tracker 2014, 247-250. DOI: 10.1145/2578153.2578209.
  • Saliency-based Bayesian modeling of dynamic viewing of static scenesCampbell D, Chang J, Chawarska K, Shic F. Saliency-based Bayesian modeling of dynamic viewing of static scenes 2014, 51-58. DOI: 10.1145/2578153.2578159.
  • A smooth pursuit calibration techniqueCelebi F, Kim E, Wang Q, Wall C, Shic F. A smooth pursuit calibration technique 2014, 377-378. DOI: 10.1145/2578153.2583042.
  • Eye-TrackingShic F. Eye-Tracking 2013, 1208-1213. DOI: 10.1007/978-1-4419-1698-3_1474.
  • Video Games, Use ofShic F. Video Games, Use of 2013, 3255-3265. DOI: 10.1007/978-1-4419-1698-3_302.
  • Upright/Inverted FiguresShic F. Upright/Inverted Figures 2013, 3204-3205. DOI: 10.1007/978-1-4419-1698-3_300.
  • Magnetic Resonance SpectroscopyShic F. Magnetic Resonance Spectroscopy 2013, 1783-1789. DOI: 10.1007/978-1-4419-1698-3_1946.
  • Bridging the research gapKim E, Paul R, Shic F, Scassellati B. Bridging the research gap ACM Transactions On Human-Robot Interaction 2012, 1: 26-54. DOI: 10.5898/jhri.1.1.kim.
  • Autism, Eye-Tracking, EntropyShic F, Chawarska K, Bradshaw J, Scassellati B. Autism, Eye-Tracking, Entropy 2008, 73-78. DOI: 10.1109/devlrn.2008.4640808.
  • The incomplete fixation measureShic F, Scassellati B, Chawarska K. The incomplete fixation measure 2008, 111-114. DOI: 10.1145/1344471.1344500.
  • Measuring Context: The Gaze Patterns of Children with Autism Evaluated from the Bottom-UpShic F, Scassellati B, Lin D, Chawarska K. Measuring Context: The Gaze Patterns of Children with Autism Evaluated from the Bottom-Up 2007, 70-75. DOI: 10.1109/devlrn.2007.4354067.
  • PITFALLS IN THE MODELING OF DEVELOPMENTAL SYSTEMSSHIC F, SCASSELLATI B. PITFALLS IN THE MODELING OF DEVELOPMENTAL SYSTEMS International Journal Of Humanoid Robotics 2007, 4: 435-454. DOI: 10.1142/s0219843607001084.
  • A Behavioral Analysis of Computational Models of Visual AttentionShic F, Scassellati B. A Behavioral Analysis of Computational Models of Visual Attention International Journal Of Computer Vision 2006, 73: 159-177. DOI: 10.1007/s11263-006-9784-6.
  • Social development [robots]Scassellati B, Crick C, Gold K, Kim E, Shic F, Sun G. Social development [robots] IEEE Computational Intelligence Magazine 2006, 1: 41-47. DOI: 10.1109/mci.2006.1672987.
  • How Not to Evaluate a Developmental SystemShic F, Scassellati B. How Not to Evaluate a Developmental System 2006, 5218-5225. DOI: 10.1109/ijcnn.2006.247275.
  • How Not to Evaluate a Developmental SystemShic F, Scassellati B. How Not to Evaluate a Developmental System 2006, 5218-5225. DOI: 10.1109/ijcnn.2006.1716826.
  • Reply to letter to the editorLin A, Nguy C, Shic F, Ross B. Reply to letter to the editor Toxicology Letters 2002, 129: 265. DOI: 10.1016/s0378-4274(02)00023-1.
  • Shic, F., & Scassellati, B. (2007b). A Behavioral Analysis of Computational Models of Visual Attention. International Journal of Computer Vision, 73(2), 159-177. doi:10.1007/s11263-006-9784-6Shic, F., & Scassellati, B. (2007b). A Behavioral Analysis of Computational Models of Visual Attention. International Journal of Computer Vision, 73(2), 159-177. doi:10.1007/s11263-006-9784-6
  • Shic, F., Jones, W., Klin, A., & Scassellati, B. (2006). Swimming in the Underlying Stream: Computational Models of Gaze in a Comparative Behavioral Analysis of Autism. In 28th Annual Conference of the Cognitive Science Society. Presented at the 28th Annual Conference of the Cognitive Science Society. (Best Applied Computational Modeling Paper)Shic, F., Jones, W., Klin, A., & Scassellati, B. (2006). Swimming in the Underlying Stream: Computational Models of Gaze in a Comparative Behavioral Analysis of Autism. In 28th Annual Conference of the Cognitive Science Society. Presented at the 28th Annual Conference of the Cognitive Science Society. (Best Applied Computational Modeling Paper)

Clinical Trials

ConditionsStudy Title
Child Development & Autism; Children's Health; Mental Health & Behavioral ResearchComponents of Emotional Processing in Young Children with ASD
Child Development & Autism; Genetics - Adult; Genetics - Pediatric; Mental Health & Behavioral ResearchPivotal Response Treatment for Children With Autism Spectrum Disorders (PRT)