Deniz Erdogmus

About

Deniz Erdogmus is a COE Distinguished Professor at Northeastern University with a research focus on artificial intelligence, machine learning, signal and image analysis, and their applications in various domains. His work emphasizes human-centric foundational and physical AI, AI for health, quality-of-life, clinical innovation, scientific discovery, and engineered systems. Erdogmus received his BS in Electrical Engineering and Mathematics in 1997 and his MS in Electrical Engineering in 1999 from Middle East Technical University (METU) in Turkey. He earned his PhD in Electrical and Computer Engineering from the University of Florida in 2002. He has served as an associate editor for various journals and has been an active member of IEEE technical committees for MLSP and BISP. Since joining Northeastern University in 2008, Erdogmus has contributed significantly to research in signal processing, machine learning, and AI, leading projects in areas such as cyber-physical systems, biomedical AI, and human-centric AI. His research is conducted through the Cognitive Systems Laboratory (CSL), which is part of multiple institutes and consortia focused on experiential AI, robotics, signal processing, and neurotechnology. Erdogmus has received numerous honors and awards, including the 2024 Distinguished Faculty Award, the 2021 Ruth and Joel Spira Award for Excellence in Teaching, and the 2012 NSF CAREER Award, among others.

Research topics

• Artificial Intelligence
• Computer Science
• Psychology
• Cognitive psychology
• Cognitive science
• Radiology
• Medicine
• Mathematics
• Computer vision
• Neuroscience

Selected publications

• Improving the study of brain-behavior relationships by revisiting basic assumptions

  Trends in Cognitive Sciences · 2023 · 157 citations

  Neuroimaging research has been at the forefront of concerns regarding the failure of experimental findings to replicate. In the study of brain-behavior relationships, past failures to find replicable and robust effects have been attributed to methodological shortcomings. Methodological rigor is important, but there are other overlooked possibilities: most published studies share three foundational assumptions, often implicitly, that may be faulty. In this paper, we consider the empirical evidenc…

  PublisherOA PDFDOI

• Siamese neural networks for continuous disease severity evaluation and change detection in medical imaging

  npj Digital Medicine · 2020 · 133 citations

  = 0.89 for osteoarthritis), both within and between the clinical grading categories. Thus, this output can represent the continuous spectrum of disease severity at any single time point. The difference in these outputs can be used to show change over time. Alternatively, paired images from the same patient at two time points can be directly compared using the Siamese neural network, resulting in an additional continuous measure of change between images. Importantly, our approach does not require…

  DOI

• Learning Invariant Representations From EEG via Adversarial Inference

  IEEE Access · 2020 · 97 citations

  Senior authorCorresponding

  Discovering and exploiting shared, invariant neural activity in electroencephalogram (EEG) based classification tasks is of significant interest for generalizability of decoding models across subjects or EEG recording sessions. While deep neural networks are recently emerging as generic EEG feature extractors, this transfer learning aspect usually relies on the prior assumption that deep networks naturally behave as subject- (or session-) invariant EEG feature extractors. We propose a further st…

  DOI

• Multimodal Fusion of EMG and Vision for Human Grasp Intent Inference in Prosthetic Hand Control

  arXiv (Cornell University) · 2021 · 4 citations

  Objective: For transradial amputees, robotic prosthetic hands promise to regain the capability to perform daily living activities. Current control methods based on physiological signals such as electromyography (EMG) are prone to yielding poor inference outcomes due to motion artifacts, muscle fatigue, and many more. Vision sensors are a major source of information about the environment state and can play a vital role in inferring feasible and intended gestures. However, visual evidence is also…

  DOI

• The inadequacy of normative ratings for building stimulus sets in affective science.

  Emotion · 2025-06-26 · 2 citations

  articleOpen access

  = 453), participants reported their experiences as they viewed silent video clips or static images that were curated from published studies and from online search engines. Two different response formats were used. Overall, the proportion of stimulus-evoked emotion experiences that met even lenient benchmarks for validity and reliability for labeling a stimulus as pertaining to a single emotion category label was exceedingly low. Furthermore, participants frequently used more than one label for a…

  PublisherDOI

Recent grants

• SCH: INT: Collaborative Research: Multimodal Signal Analysis and Data Fusion for Post-traumatic Epilepsy

  NIH · $981k · 2019–2024

• Collaborative Research: CDI-Type I: Computational Models for the Automatic Recognition of Non-Human Primate Social Behaviors

  NSF · $156k · 2010–2014

• HCC-Small: RSVP IconCHAT - A Brain Computer Interface for Icon-based Communication

  NSF · $504k · 2009–2013

Frequent coauthors

• Jayashree Kalpathy‐Cramer

  University of Colorado Anschutz Medical Campus

  155 shared

• José C. Prı́ncipe

  University of Florida

  137 shared

• Michael F. Chiang

  National Eye Institute

  109 shared

• Tales Imbiriba

  78 shared

• J. Peter Campbell

  75 shared

• Susan Ostmo

  Oregon Health & Science University

  71 shared

• Murat Akçakaya

  University of Pittsburgh

  66 shared

• R.V. Paul Chan

  University of Illinois Chicago

  64 shared

Labs

• Cognitive Systems Laboratory (CSL)PI

Awards & honors

• 2024 Distinguished Faculty Award
• 2021 ECE Ruth and Joel Spira Award for Excellence in Teachin…
• 2021 COE Faculty Research Team Award
• 2019 COE Excellence in Mentoring Award
• 2014 COE Faculty Fellow

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