Dr. Erik Linstead

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Recent Creative, Scholarly Work and Publications

Slingerland, P., Mandrake, L., Doran, G., Goel, A., Perry, L., Feather, M., Kaufman, J., Bycroft, B., Fesq, L., Linstead, E., Ono, M., Amini, R. “Adapting a Trusted AI Framework to Space Mission Autonomy.” IEEE Aerospace Conference. Big Sky, MT. March, 2022.

Ali, R., Rodeghiero, K., Zuch, A., Syed, S., Linstead, E. “An Application of Neural Embedding Models for Representing Artistic Periods.” International Conference on Artificial Intelligence in Music, Sound, Art and Design. April, 2022.

Perera, S., Allali, M., Linstead, E., El-Askary, H. “Deriving Drought Vulnerability Index Using Geographically Weighted Principal Component Analysis (GWPCA) and K-Means Clustering for Nile Basin.” International Geoscience and Remote Sensing Symposium (IGARSS). Kuala Lumpur, Malaysia. July, 2022.

Atchison, A., Pinto, G., Woodward, A., Stevens, E., Dixon, D., Linstead, E. “An Application of Document Embeddings to Identifying Challenging Behaviors in Autism Spectrum Disorder From Clinical Notes.” International Conference on Machine Learning and Applications (ICMLA). Nassau, Bahamas. December, 2022.

Phan, MT., Tomaszewski, DM., Arbuckle, C., Yang, S., Jenkins, B., Fortier, MA., Heyming, T., Linstead, E., Donaldson, C., Kain, Z. “Evaluating the 0–10 Point Pain Scale on Adolescent Opioid Use in US Emergency Departments.” Journal of Clinical Medicine. 2022.

Parlett-Pelleriti, C., Stevens, E., Dixon, D., Linstead, E. “Applications of Unsupervised Machine Learning in Autism Spectrum Disorder Research: A Review.” Review Journal of Autism and Developmental Disorders. 2022.

Liang, D., Frederick, D., Lledo, E., Rosenfield, N., Berardi, V., Linstead, E., Maoz, U. “Examining the Utility of Nonlinear Machine Learning Approaches versus Linear Regression for Predicting Body Image Outcomes: The U.S. Body Project I.” Body Image. 2022.

Ali, R., Pinto, G., Lawrie, E., Linstead, E. “A Large-Scale Sentiment Analysis of Tweets Pertaining to the 2020 US Presidential Election.” Journal of Big Data. 2022.

Ali, R., Kashefi, A., Gorman, A., Walsh, J, Linstead, E. “Automated Identification of Astronauts on Board the International Space Station: A Case Study in Space Archaeology.” Acta Astronautica. 2022.

Springer, T., Linstead, E., Zhao, P., Parlett-Pelleriti, C. “Toward QoS-Based Embedded Machine Learning.” Electronics. 2022.

Perera, S., Allali, M., Linstead, E., El-Askary, H. “Landuse Landcover Change Detection in the Mediterranean Region Using a Siamese Neural Network and Image Processing.” International Geoscience and Remote Sensing Symposium (IGARSS). Brussels, Belgium. July, 2021.

Atchison, A., Pinto, G., Woodward, A., Stevens, E., Dixon, D., Linstead, E. “Classifying Challenging Behaviors in Autism Spectrum Disorder with Word Embeddings.” International Conference on Machine Learning and Applications (ICMLA). Pasadena, CA. December, 2021.

Stevens, L., Linstead, E., Hall, J., Kao, D. “The association between coffee intake and incident heart failure risk - a machine learning analysis of the Framingham Heart, Atherosclerosis Risk in Communities study, and Cardiovascular Health Studies.” Circulation Heart Failure. 2021.

Li, W., Perera, S., Linstead, E., Thomas, R., El-Askary, H., Piechota, T., Struppa, D. “Investigating decadal changes of multiple hydrological products and land cover changes in the Mediterranean Region for 2009-2018.” Earth Systems and Environment. 2021.

Springer, T., Eiroa-Lledo, E., Stevens, E., Linstead, E. “On-Device Deep Learning Inference for System-on-Chip (SoC) Architectures.” Electronics. 2021.

Ali, R., Fong, G., Linstead, E. “Project Metamorphosis: Designing a Dynamic Framework for Converting Musical Compositions into Paintings.” Leonardo. 2021.

Gardner-Hoag, J., Novack, M., Parlett-Pelleriti, C., Stevens, E., Dixon, D., Linstead, E. “Identifying Challenging Behavior Profiles and Exploring their Impact on Treatment Efficacy in Autism Spectrum Disorder using Unsupervised Machine Learning.” JMIR Medical Informatics. 2021.

Phan, M., Tomaszewski, D., Arbuckle, C., Yang, S., Donaldson, C., Fortier, M., Jenkins, B., Linstead, E., Kain, Z. “Racial and Ethnic Disparities in Opioid Use for Adolescents at US Emergency Departments.” BMC Pediatrics. 2021.

LaHaye, N., Garay, M., Bue, B., El-Askary, H., Linstead, E. “A Quantitative Validation of Multi-Modal Image Fusion and Segmentation for Object Detection and Tracking.” Remote Sensing. 2021.

El-Askary, H., Fawzy, A., Thomas, R., Li, W., LaHaye, N., Linstead, E., Piechota, T., Struppa, D., Sayed, MA. “Assessing the Vertical Displacement of the Grand Ethiopian Renaissance Dam during Its Filling Using DInSAR Technology and Its Potential Acute Consequences on the Downstream Countries.” Remote Sensing. 2021.

Eiroa-Lledo, E., Bechtel, A., Daskas, E., Foster, L., Pirzadeh, R., Rodeghiero, K., Linstead, E. “Do Experienced Programmers put too Much Confidence in Comments?” International Conference on Software Engineering and Knowledge Engineering (SEKE). Pittsburgh, PA. July, 2020.

Ali, R., Linstead, E. “Modeling Topic Exhaustion for Programming Languages on StackOverflow.” International Conference on Software Engineering and Knowledge Engineering (SEKE). Pittsburgh, PA. July, 2020.

Perera, S., Li, W., Linstead, E., El-Askary, H. “Forecasting Vegetation Health in the Mena Region by Predicting Vegetation Indicators with Machine Learning Models.” International Geoscience and Remote Sensing Symposium (IGARSS). Waikoloa, Hawaii. July, 2020.

Ali, R., Parlett-Pelleriti, C., Linstead, E. “Cheating Death: A Statistical Survival Analysis of Publicly Available Python Projects.” International Conference on Mining Software Repositories (MSR). Seoul, South Korea. May, 2020.

Bergh, A., Harnack, P., Atchison, A., Ott, J., Eiroa-Lledo, E., Linstead, E. "A Curated Set of Labeled Code Tutorial Images for Deep Learning.” International Conference on Machine Learning and Applications (ICMLA). Miami, FL. December, 2020.

Parlett-Pelleriti, P., Linstead, E. "A Hierarchical Bayesian IRT Analysis of Children’s Risk Propensity.” International Conference on Machine Learning and Applications (ICMLA). Miami, FL. December, 2020.

Anden, R., Linstead, E. “Predicting eye movement and fixation patterns on scenic images using Machine Learning for Children with Autism Spectrum Disorder.” Workshop in Artificial Intelligence Techniques for BioMedicine and HealthCare (AIBH). Seoul, South Korea. December, 2020.

Griffiths, A., Hanson, A., Giannantonio, C., Mathur, S., Hyde, K., Linstead, E. “Developing Employment Environments where Individuals with ASD Thrive: Using Machine Learning to Explore Employer Policies and Practices.” Brain Sciences. 2020.

Ott, J., Linstead, E., LaHaye, N., Baldi, P. “Learning in the Machine: To Share or Not to Share.” Neural Networks. 2020.

Stevens, L., Kao, D., Hall, J. Goerg, C., Abdo, K., Linstead, E. “ML-MEDIC: An Interactive Visual Analysis Tool Facilitating Clinical Applications of Machine Learning for Precision Medicine.” Applied Sciences. 2020.

Ali, R., Graves, J., Wu, S., Lee, J., Linstead, E. “A Machine Learning Approach to Delineating Neighborhoods from Geocoded Appraisal Data.” International Journal of Geo-Information. 2020.

Best, N., Ott, J., Linstead, E. “Exploring the Efficacy of Transfer Learning in Mining Image-Based Software Artifacts.” Journal of Big Data. 2020.

Ott, J., Pritchard, M., Best, N., Linstead, E., Curcic, M., Baldi, P. “A Fortran-Keras Deep Learning Bridge for Scientific Computing.” Scientific Programming. 2020.

Rosenfield, N., Linstead, E. “Exploring the Eating Disorder Examination Questionnaire, Clinical Impairment Assessment, and Autism Quotient to Identify Eating Disorder Vulnerability: A Cluster Analysis.” Machine Learning and Knowledge Extraction. 2020.

Maoz, U., Linstead, E. “Brain Imaging and Artificial Intelligence.” In “Casting Light on the Dark Side of Brain Imaging.” A. Raz and R. Thibault, editors. Academic Press. 2019.

Boyd, L., Day, K., Abdo, K., Wasserman, B., Linstead, E., Hayes, G. “Paper Prototyping Comfortable VR Play for Diverse Sensory Needs.” CHI Conference on Human Factors in Computing Systems. Late Breaking Work. Glasgow, UK. May, 2019.

LaHaye, N., El-Askary, H., Linstead, E. “Evaluating the Plausibility of Including SAR Ingest and Analysis Capabilities in Unsupervised Deep Learning Framework for Multi-Modal Object Tracking and Detection.” International Conference on Space Mission Challenges for Information Technology. Pasadena, CA. July, 2019. (extended abstract)

Woodward, D., Stevens, E., Linstead, E. “Generating Transit Light Curves with Variational Autoencoders.” International Conference on Space Mission Challenges for Information Technology. Pasadena, CA. July, 2019.

Hyde, K., Griffiths, A., Giannantonio, C., Hanson, A., Mathur, S., Linstead, E. “Exploring the Landscape of Employers for Individuals with Autism Spectrum Disorder.” International Conference on Machine Learning and Applications (ICMLA). Boca Raton, FL. December, 2019.

Springer, T., Linstead, E. “Adaptive QoS-Based Real-Time Communication Framework for WSANs.” Information Technology, Electronics and Mobile Communication Conference (IEMCON). Vancouver, Canada. October, 2019.

Hyde, K., Novack, M., LaHaye, N., Parlett, C., Hong, E., Anden, R., Dixon, D., Linstead, E. “Applications of Supervised Machine Learning in Autism Spectrum Disorder Research: A Review.” Review Journal of Autism and Developmental Disorders. 2019.

Parlett, C., Lin, G., Jones, M., Linstead, E., Jaeggi, S. “Exploring Age-Related Metamemory Differences using Modified Brier Scores and Hierarchical Clustering.” Open Psychology. 2019.

Rosenfield, N., Lamkin, K., Re, J., Day, K., Boyd, L., Linstead, E. “A Virtual Reality System for Practicing Conversation Skills for Children with Autism.” Multimodal Technologies and Interaction. 2019.

Arbuckle, C., Tomaszewski, D., Aronson, B., Brown, L., Schommer, J., Morisky, D., Linstead, E. “Exploring the Impact of Information Source on Medication Adherence in the Digital Age.” Computers in Biology and Medicine. 2019.

Ott, J., Atchison, A., Linstead, E. “Exploring the Applicability of Low-Shot Learning in Mining Software Repositories.” Journal of Big Data. 2019.

Stevens, E., Dixon, D., Novack, M., Granpeesheh, D., Smith, T., Linstead, E. “Identification and Analysis of Behavioral Phenotypes in Autism Spectrum Disorder via Unsupervised Machine Learning.” International Journal of Medical Informatics. 2019.

LaHaye, N., Ott, J., Garay, M., El-Askary, H., Linstead, E. “Toward Generic, Multi-Modal Object Tracking and Image Fusion with Unsupervised Deep Learning.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2019.

Gapper, J., El-Askary, H., Linstead, E., Piechota, T. “Coral Reef Change Detection in Remote Pacific Islands using Support Vector Machine Classifiers.” Remote Sensing. 2019.

Boyd, L., Gupta, S., Vikmani, S., Gutierrez, C., Yang, J., Linstead, E., Hayes, G. “vrSocial: Toward Immersive Therapeutic VR System for Children with Autism.” CHI Conference on Human Factors in Computing Systems. Montreal, Canada. April, 2018.

Ott, J., Atchison, A., Harnack, P., Best, N. Anderson, H., Firmani, C., Linstead, E. “Learning Lexical Features of Programming Languages from Imagery Using Convolutional Neural Networks.” International Conference on Program Comprehension. Gothenburg, Sweden. May, 2018.

Ott, J., Atchison, A., Harnack, P., Bergh, A., Linstead, E. “A Deep Learning Approach to Identifying Source Code in Images and Video.” International Conference on Mining Software Repositories. Gothenburg, Sweden. May, 2018.

Atchison, A., Anderson, H., Berardi, C., Best, N., Firmani, C., German, R., Linstead, E. “Poster: A Topic Analysis of the R Programming Language.” International Conference on Software Engineering. Gothenburg, Sweden. May, 2018.

Springer, T., Linstead, E. “Adaptive QoS-Based Resource Management Framework for IoT/Edge Computing.” 2018 9th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), New York City, NY. November, 2018.

Hong, E., Burns, C., Stevens, E., Dixon, D., Linstead, E. “Topography and Function of Challenging Behaviors in Individuals with Autism Spectrum Disorder.” Advances in Neurodevelopmental Disorders. 2018.

Boyd, L., Day, K., Stewart, N., Abdo, K., Lamkin, K., Linstead, E. “Leveling the Playing Field: Supporting Neurodiversity via Virtual Realities.” Innovation and Technology – Journal of the National Academy of Inventors. 2018. (in press)

Gapper, J., El-Askary, H., Linstead, E., Piechota, T. "Development of a Robust Classifier and Evaluation of Generalization Properties for Multiple Shallow Benthic Habitats in the Pacific Ocean Using Remote Sensing Data." Remote Sensing. 2018.

Tomaszewski, D., Arbuckle, C., Yang, S., Linstead, E. "Trends in Opioid Use in Pediatric Patients In United States Outpatient Hospital Departments From 2006-2015." JAMA Network Open. 2018.

Arbuckle, C., Tomaszewski, D., Aronson, B., Brown, L., Schommer, J., Morisky, D., Linstead, E. “Evaluating Factors Impacting Medication Adherence Among Rural, Urban, and Suburban Populations.” Journal of Rural Health. 2018.

Atchison, A., Berardi, C., Best, N., Stevens, E., Linstead, E. “A Time Series Analysis of TravisTorrent Builds: To Everything There is a Season.” International Conference on Mining Software Repositories (MSR). Buenos Aires, Argentina. May, 2017.

Stevens, E., Atchison, A., Stevens, L., Hong, E., Granpeesheh, D., Dixon, D., Linstead, E. “A Cluster Analysis of Challenging Behaviors in Autism Spectrum Disorders.” International Conference on Machine Learning and Applications (ICMLA). Cancun, Mexico. December, 2017.

Arbuckle, C., Greenberg, M., Bergh, A., German, R., Sirago, N., Linstead, E. “T-Time: A Data Repository of T Cell and Calcium Release-Activated Calcium Channel Activation Imagery.” BMC Research Notes. August, 2017.

Linstead, E., Dixon, D., Hong, E., Burns, C., French, R., Novack, M., Granpeesheh, D. “An Evaluation of the Effects of Intensity and Duration on Outcomes across Treatment Domains for Children with Autism Spectrum Disorder.” Nature Translational Psychiatry. 2017.

El-Askary, H. LaHaye, N., Linstead, E., Sprigg, W., Yacoub, M. "Remote sensing observation of annual dust cycle and possible causality of Kawasaki disease outbreaks in Japan" Global Cardiology Science and Practice. 2017.

Linstead, E., Burns, R., Nguyen, D., Tyler, D. “AMP: A Platform for Managing and Mining Data in the Treatment of Autism Spectrum Disorder.” International Conference on Engineering in Medicine and Biology (EMBC). Lake Buena Vista, FL. August, 2016.

Linstead, E.. Dixon, D., Granpeesheh, D., French, R., German, R., Stevens, E. “Intensity and Learning Outcomes in the Treatment of Children with Autism Spectrum Disorder.” Journal of Behavior Modification. 2016.

Dixon, D., Linstead, E., Granpeesheh, D., French, R., Stevens, E., Stevens, L., Novack, M., Powell, A. “An evaluation of the impact of supervision intensity, supervisor qualifications, and caseload on outcomes in the treatment of autism spectrum disorder.” Behavior Analysis in Practice. June 2016.

Dixon, D., Burns, C., Granpeesheh, D., Powell, A., Linstead, E. “A Program Evaluation of Home and Center-Based Treatment for Autism Spectrum Disorder.” Behavior Analysis in Practice. October 2016.

Linstead, E., German, R., Dixon, D., Granpeesheh, D, Powell, A., Novack, M. “An Application of Neural Networks to Predicting Mastery of Learning Outcomes in the Treatment of Autism Spectrum Disorder.” International Conference on Machine Learning and Applications. Miami, FL. December 2015.

Arbuckle, C., Greenberg, M., Linstead, E. “Detection and Tracking of T Cells in Time Lapse Imaging.” ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (BCB). Atlanta, GA. September 2015.