ML Tlachac, Michael V. Heinz, Anastasia C. Bryan, Arielle LaPreay, Geri Louise Dimas, Tingting Zhao, Nicholas C. Jacobson, and Samuel S. Ogden, \u201cDatasets of Smartphone Modalities for Depression Assessment: A Scoping Review\u201d, IEEE Transactions on Affective Computing, 2025.<\/p>\n
ML Tlachac*, Miranda Hernandez-Reisch*, Avantika Shrestha, Ricardo Flores, Ermal Toto, and Elke Rundensteiner, “Voice Recordings from Short Mobile Sessions versus Clinical Interviews for Mental Illness Screening: A Comparative Study with Deep Transfer Learning”,\u00a0 ACM Transactions on Computing for Healthcare, 2025.<\/p>\n
Ricardo Flores, ML Tlachac, Avantika Shrestha, and Elke Rundensteiner, “WavFace: A Multimodal Transformer-based Model for Depression Screening”, IEEE Journal of Biomedical and Health Informatics (J-BHI), 2025.<\/p>\n
Rebecca Lopez, Avantika Shrestha, Kevin Hickey, Xingtong Guo, ML Tlachac, Shichao Liu, and Elke Rundensteiner, “Screening Students for Stress Using Fitbit Data”, The 4th International Workshop on Multi-Modal Medical Data Analysis, 2024 IEEE International Conference on Big Data (BigData), 2024.<\/p>\n
Avantika Shrestha, ML Tlachac, Ricardo Flores, Kevin Hickey, and Elke Rundensteiner, “Multi-task Learning with Pre-trained Language Models for Mental Illness Screening”, The 9th IEEE Special Session on Machine Learning on Big Data (MLBD 2024), 2024 IEEE International Conference on Big Data (BigData), 2024.<\/p>\n
Tingting Zhao and ML Tlachac. “Bayesian Optimization with Tree Ensembles to Improve Depression Screening on Textual Datasets”, IEEE Transactions on Affective Computing (early access)<\/p>\n
ML Tlachac and Michael Heinz. “Mental Health and Mobile Communication Profiles of Crowdsourced Participants”, IEEE Journal of Biomedical and Health Informatics (early access)<\/p>\n
ML Tlachac, Michael Heinz, Miranda Reisch, and Samuel S. Ogden, “Symptom Detection with Text Message Log Distributions for Holistic Depression and Anxiety Screening”, ACM Proceedings on Interactive, Mobile, Wearable and Ubiquitous Technologies, vol 8 (1), 2024<\/p>\n
Anastasia C. Bryan, Michael V. Heinz, Abigail J. Salzhauer, George D. Price, ML Tlachac, and Nicholas C. Jacobson. “Behind the Screen: A Narrative Review on the Translational Capacity of Passive Sensing for Mental Health Assessment”, Biomedical Materials & Devices, vol 2, Springer, pages 778\u2013810, 2024<\/p>\n
Ricardo Flores, Avantika Shrestha, and Elke A. Rundensteiner. “DeepScreen: Boosting Depression Screening Performance with an Auxiliary Task”, 2023 IEEE International Conference on Big Data (BigData), 2023.<\/p>\n
Ricardo Flores*, Avantika Shrestha*, ML Tlachac, and Elke A. Rundensteiner. “Multi-Task Learning Using Facial Features for Mental Health Screening”, 2023 IEEE International Conference on Big Data (BigData), 2023.<\/p>\n
Nikola Grozdani, America Mu\u00f1oz, Alexander Pietrick, Ricardo Flores, Avantika Shrestha, Xingtong Guo, Shichao Liu, Elke Rundensteiner, \u201cWearable Wellness: Depression Screening via Fitbit Data Collected During COVID-19 Pandemic\u201d, 2023 IEEE MIT Undergraduate Research Technology Conference (URTC), 2023.<\/p>\n
ML Tlachac, Miranda Reisch, Michael Heinz, \u201cMobile Communication Log Time Series to Detect Depressive Symptoms\u201d, 45th International Conference of IEEE Engineering in Medicine and Biology Society (EMBC), 2023<\/p>\n
ML Tlachac, Walter Gerych, Kratika Agrawal, Benjamin Litterer, Nicholas Jurovich, Saitheeraj Thatigotla, Jidapa Thadajarassiri, Elke Rundensteiner, \u201cText Generation to Aid Depression Detection: A Comparative Study of Conditional Sequence Generative Adversarial Networks\u201d, IEEE International Conference on Big Data (BigData) Workshop on Big Data Analytic in Healthcare, 2022.<\/p>\n
Avantika Shrestha, ML Tlachac, Ricardo Flores, Elke Rundensteiner, \u201cBERT Variants for Depression Screening with Typed and Transcribed Responses\u201d, In Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp\/ISWC \u201922 Adjunct), 2022.<\/p>\n
Ricardo Flores, ML Tlachac, Avantika Shrestha, and Elke A. Rundensteiner, \u201cTemporal Facial Features for Depression Screening\u201d, In Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp\/ISWC \u201922 Adjunct), 2022.<\/p>\n
ML Tlachac and Samuel S. Ogden \u201cLeft on Read: Reply Latency for Anxiety & Depression Screening\u201d, In Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp\/ISWC \u201922 Adjunct), 2022.<\/p>\n
ML Tlachac, Avantika Shrestha, Mahum Shah, Benjamin Litterer, and Elke Rundensteiner, \u201cAutomated Construction of Lexicons to Improve Depression Screening with Text Messages\u201d, IEEE Journal of Biomedical and Health Informatics (J-BHI) Special Issue on Advancing Biomedical Discovery & Healthcare Delivery Through Digital Technologies, pp 1-8, 2022.<\/p>\n
ML Tlachac, Miranda Reisch, Brittany Lewis, Ricardo Flores, Lane Harrison, and Elke Rundensteiner, \u201cImpact Assessment of Stereotype Threat on Mobile Depression Screening using Bayesian Estimation\u201d, Healthcare Analytics, Elsevier, 2022.<\/p>\n
Ricardo Flores, ML Tlachac, Ermal Toto, Elke Rundensteiner, \u201cAudiFace: Multimodal Deep Learning for Depression Screening\u201d, Machine Learning for Healthcare, 2022.<\/p>\n
Ricardo Flores, ML Tlachac, Ermal Toto, Elke Rundensteiner, \u201cTransfer Learning for Depression Screening from Follow-up Clinical Interview Questions\u201d, Deep Learning Applications (DLAV), vol 4, Springer, 2022.<\/p>\n
ML Tlachac, Ricardo Flores, Ermal Toto, Elke Rundensteiner, \u201cEarly Mental Health Uncovering with Short Scripted and Unscripted Voice Recordings\u201d, Deep Learning Applications (DLAV), vol 4, Springer, 2022.<\/p>\n
ML Tlachac, Ricardo Flores, Miranda Reisch, Katie Housekeeper, Elke Rundensteiner, \u201cDepreST-CAT: Retrospective Smartphone Call and Text Logs Collected During the COVID-19 Pandemic to Screen for Mental Illnesses\u201d, ACM Proceedings on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), vol. 6, no. 2, 2022.<\/p>\n
ML Tlachac, Ricardo Flores, Miranda Reisch, Rimsha Kayastha, Nina Taurich, Veronica Melican, Connor Bruneau, Hunter Caouette, Joshua Lovering, Ermal Toto, Elke Rundensteiner, \u201cStudentSADD: Rapid Mobile Depression and Suicidal Ideation Screening of College Students during the Coronavirus Pandemic\u201d, ACM Proceedings on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), vol. 6, no. 2, 2022.<\/p>\n
Saskia Senn, ML Tlachac, Ricardo Flores, Elke Rundensteiner, \u201cEnsembles of BERT for Depression Classification\u201d, 44th International Conference of IEEE Engineering in Medicine and Biology Society (EMBC), Accepted.<\/p>\n
ML Tlachac, Ermal Toto, Joshua Lovering, Rimsha Kayastha, Nina Taurich, Elke Rundensteiner, \u201cEMU: Early Mental Health Uncovering Framework and Dataset\u201d, 20th IEEE International Conference on Machine Learning and Applications (ICMLA) Special Session Machine Learning in Health, 2021.<\/p>\n
Ricardo Flores, ML Tlachac, Ermal Toto, Elke Rundensteiner, \u201cDepression Screening Using Deep Learning on Follow-up Questions in Clinical Interviews\u201d, 20th IEEE International Conference on Machine Learning and Applications (ICMLA), 2021.<\/p>\n
Ermal Toto, ML Tlachac, Elke Rundensteiner, \u201cAudiBERT: A Deep Transfer Learning Multimodal Classification Framework for Depression Screening\u201d, 30th ACM International Conference on Information and Knowledge Management (CIKM) Applied Research Track, 2021 (best applied paper<\/strong>).<\/p>\n Edwin Boudreaux, Elke Rundensteiner, Feifan Liu, Bo Wang, Celine Larkin, Emmanuel Agu, Samiran Ghosh, Joshua Semeter, Gregory Simon, Rachel Davis-Martin, “Applying Machine Learning Approaches to Suicide Prediction Using Healthcare Data: Overview and Future Directions”, Frontiers in Psychiatry Journal, section Mood and Anxiety Disorders, 2021.<\/p>\n ML Tlachac, Veronica Melican, Miranda Reisch, Elke Rundensteiner, \u201cMobile Depression Screening with Time Series of Text Logs and Call Logs\u201d, 17th IEEE EMBS International Conference on Biomedical & Health Informatics (BHI), 2021.<\/p>\n ML Tlachac, Katherine Dixon-Gordon, Elke Rundensteiner, “Screening for Suicidal Ideation with Text Messages”, 17th IEEE EMBS International Conference on Biomedical & Health Informatics (BHI), 2021.<\/p>\n ML Tlachac, Adam Sargent, Ermal Toto, Randy Paffenroth, Elke Rundensteiner, “Topological Data Analysis to Engineer Features from Audio Signals for Depression Detection”, 19th IEEE International Conference on Machine Learning and Applications (ICMLA), 2020.<\/p>\n Ermal Toto, ML Tlachac, Francis Lee Stevens, Elke Rundensteiner, \u201cAudio-based Depression Screening using Sliding Window Sub-clip Pooling\u201d, 19th IEEE International Conference on Machine Learning and Applications (ICMLA), 2020.<\/p>\n Ada Dogrucu, Alex Perucic, Anabella Isaro, Damon Ball, Ermal Toto, Elke A. Rundensteiner, Emmanuel Agu, Rachel Davis-Martin, Edwin Boudreaux, \u201cMoodable: On feasibility of instantaneous depression assessment using machine learning on voice samples and retrospectively harvested smartphone and social media data,\u201d Smart Health, 2020.<\/p>\n ML Tlachac and Elke Rundensteiner, \u201cDepression screening from text message reply latency,\u201d in 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE, 2020, pp. 1\u20134.<\/p>\n ML Tlachac and Elke Rundensteiner, \u201cScreening for depression with retrospectively harvested private versus public text,\u201d IEEE Journal of Biomedical and Health Informatics, volume 24, no. 11, 2020, pp. 3326-3332.<\/p>\n ML Tlachac, Ermal Toto, Elke Rundensteiner, “You’re Making Me Depressed: Leveraging Texts from Contact Subsets to Predict Depression”, 2019 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI), 2019, pp. 1-4.<\/p>\n Walter Gerych, Emmanuel Agu, and Elke Rundensteiner, “Classifying Depression in Imbalanced Datasets Using an Autoencoder- Based Anomaly Detection Approach,” 2019 IEEE 13th International Conference on Semantic Computing (ICSC), 2019.<\/p>\n Ermal Toto, Brandon J. Foley, Elke A. Rundensteiner, “Improving Emotion Detection with Sub-clip Boosting”, ECML\/PKDD 2018.<\/p>\n Conference and Journal Papers: ML Tlachac, Michael V. Heinz, Anastasia C. Bryan, Arielle LaPreay, Geri Louise Dimas, Tingting Zhao, Nicholas C. Jacobson, and Samuel S. Ogden, \u201cDatasets of Smartphone Modalities… Continue Reading<\/a><\/p>\n","protected":false},"author":2,"featured_media":0,"parent":0,"menu_order":5,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"https:\/\/emutivo.wpi.edu\/index.php\/wp-json\/wp\/v2\/pages\/26"}],"collection":[{"href":"https:\/\/emutivo.wpi.edu\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/emutivo.wpi.edu\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/emutivo.wpi.edu\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/emutivo.wpi.edu\/index.php\/wp-json\/wp\/v2\/comments?post=26"}],"version-history":[{"count":73,"href":"https:\/\/emutivo.wpi.edu\/index.php\/wp-json\/wp\/v2\/pages\/26\/revisions"}],"predecessor-version":[{"id":2125,"href":"https:\/\/emutivo.wpi.edu\/index.php\/wp-json\/wp\/v2\/pages\/26\/revisions\/2125"}],"wp:attachment":[{"href":"https:\/\/emutivo.wpi.edu\/index.php\/wp-json\/wp\/v2\/media?parent=26"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}\n
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