Ermal Toto
Director, Scientific Data, Applications and Web Development
Email: toto@wpi.edu
Phone
Department :
Information Technology Services
Dr. Ermal Toto is the Director for Scientific Data and Applications with Academic and Research Computing. He is a WPI alumnus with a MBA (’25) and PhD in Computer Science (’21). Prior to the current position Ermal has worked as a Data Scientist, Software Engineer, and Network Administrator. His research interests include emotion and mood detection using machine learning, AI and data mining. A list of publications can be found at https://scholar.google.com/citations?user=opJQ2k0AAAAJ&hl=en .
Professional Highlights & Honors
1st Place, WPI Graduate Research Innovation Exchange (GRIE) - 2016
1st Place, WPI Graduate Research Innovation Exchange (GRIE) - 2010
1st Place, National Olympiad in Informatics (Albania) - 2000
3rd Place, National Olympiad in Informatics (Albania) - 1999
Publications
- Voice Recordings from Short Mobile Sessions versus Clinical Interviews for Mental Illness Screening: A Comparative Study with Deep Transfer Learning
M.L. Tlachac, M. Reisch, A. Shrestha, R. Flores, E. Toto, E.A. Rundensteiner
ACM Transactions on Computing for Healthcare, 6(3), 1–30, 2025 - StudentSADD: Rapid Mobile Depression and Suicidal Ideation Screening of College Students during the Coronavirus Pandemic
M.L. Tlachac, R. Flores, M. Reisch, R. Kayastha, N. Taurich, V. Melican, et al.
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), 2022 - AudiFace: Multimodal Deep Learning for Depression Screening
R. Flores, M.L. Tlachac, E. Toto, E. Rundensteiner
Machine Learning for Healthcare Conference (MLHC), 609–630, 2022 - Early Mental Health Uncovering with Short Scripted and Unscripted Voice Recordings
M.L. Tlachac, R. Flores, E. Toto, E. Rundensteiner
Deep Learning Applications, Volume 4, 79–110, 2022 - Transfer Learning for Depression Screening from Follow-Up Clinical Interview Questions
R. Flores, M.L. Tlachac, E. Toto, E. Rundensteiner
Deep Learning Applications, Volume 4, 53–78, 2022 - Audibert: A Deep Transfer Learning Multimodal Classification Framework for Depression Screening
E. Toto, M.L. Tlachac, E.A. Rundensteiner
Proceedings of the 30th ACM International Conference on Information & Knowledge Management (CIKM), 2021 - EMU: Early Mental Health Uncovering Framework and Dataset
M.L. Tlachac, E. Toto, J. Lovering, R. Kayastha, N. Taurich, E. Rundensteiner
20th IEEE International Conference on Machine Learning and Applications (ICMLA), 2021 - Depression Screening Using Deep Learning on Follow-Up Questions in Clinical Interviews
R. Flores, M.L. Tlachac, E. Toto, E.A. Rundensteiner
20th IEEE International Conference on Machine Learning and Applications (ICMLA), 2021 - The Connect.Cyberinfrastructure Portal
J. Ma, S. Akbar, T. Battelle, K. Brandt, E. Brown, D. Brunson, D. Chakravorty, et al.
Practice and Experience in Advanced Research Computing (PEARC), 2021 - Moodable: On Feasibility of Instantaneous Depression Assessment Using Machine Learning on Voice Samples with Retrospectively Harvested Smartphone and Social Media Data
A. Dogrucu, A. Perucic, A. Isaro, D. Ball, E. Toto, E.A. Rundensteiner, E. Agu, et al.
Smart Health, 17, 100118, 2020 - Audio-Based Depression Screening Using Sliding Window Sub-Clip Pooling
E. Toto, M.L. Tlachac, F.L. Stevens, E.A. Rundensteiner
19th IEEE International Conference on Machine Learning and Applications (ICMLA), 2020 - Topological Data Analysis to Engineer Features from Audio Signals for Depression Detection
M.L. Tlachac, A. Sargent, E. Toto, R. Paffenroth, E. Rundensteiner
19th IEEE International Conference on Machine Learning and Applications (ICMLA), 2020 - Automated Detection of Nonmelanoma Skin Cancer Using Digital Images: A Systematic Review
A. Marka, J.B. Carter, E. Toto, S. Hassanpour
BMC Medical Imaging, 19(1), 21, 2019 - You're Making Me Depressed: Leveraging Texts from Contact Subsets to Predict Depression
M.L. Tlachac, E. Toto, E. Rundensteiner
IEEE EMBS International Conference on Biomedical & Health Informatics (BHI), 2019 - FIRE: A Two-Level Interactive Visualization for Deep Exploration of Association Rules
A. Mukherji, X. Lin, E. Toto, C.R. Botaish, J. Whitehouse, E.A. Rundensteiner, et al.
International Journal of Data Science and Analytics, 7(3), 201–226, 2019 - Improving Emotion Detection with Sub-Clip Boosting
E. Toto, B.J. Foley, E.A. Rundensteiner
Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD), 2018 - Pulse: A Real Time System for Crowd Flow Prediction at Metropolitan Subway Stations
E. Toto, E.A. Rundensteiner, Y. Li, R. Jordan, M. Ishutkina, K. Claypool, J. Luo, et al.
Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD), 2016 - Instruction System with Eyetracking-Based Adaptive Scaffolding
J.D. Gobert, E. Toto
US Patents 9,230,221 & 9,317,115, 2016 - Introducing Tablet Devices in Secondary Education: Does the Teacher Matter?
O. Yasar, J. Gobert, E. Toto, M. Margoudi, Z. Smyrnaiou, H. Montrieux, et al.
Conference of the Junior Researchers of EARLI (JURE), 2014 - Logging Student Learning via a Puerto Rico-Based Geologic Mapping Game on the Google Earth Virtual Globe
J. Gobert, E. Toto, S.C. Wild, M.M. Dordevic, D.G. De Paor
AGU Fall Meeting Abstracts, ED14C-03, 2013 - Searching for Predictors of Learning Outcomes in Non Abstract Eye Movement Logs
J.D. Gobert, E. Toto, M. Brigham, M. Sao Pedro
International Conference on Artificial Intelligence in Education (AIED), 799–802, 2013 - Leveraging Educational Data Mining for Real-Time Performance Assessment of Scientific Inquiry Skills within Microworlds
J.D. Gobert, M.A. Sao Pedro, R.S.J.d. Baker, E. Toto, O. Montalvo
Journal of Educational Data Mining, 4(1), 104–143, 2012 - The Science Assistments Project: Intelligent Tutoring for Scientific Inquiry Skills
J. Gobert, M. Sao Pedro, O. Montalvo, E. Toto, M. Bachmann, R. Baker
Proceedings of the Annual Meeting of the Cognitive Science Society, 33(33), 2011 - The Science Assistments Project: Scaffolding Scientific Inquiry Skills
J.D. Gobert, O. Montalvo, E. Toto, M. Sao Pedro, R.S.J. Baker
International Conference on Intelligent Tutoring Systems (ITS), 445, 2010