Konstantinos N. Plataniotis
Professor
Studies image and signal processing, machine learning and affective computing.
Konstantinos N. Plataniotis's lab at Toronto works on signal processing & information theory, speech enhancement & signal processing and affective & health speech. 94 papers since 2023, 31 at top venues, mostly ICASSP and ICLR. 3 PhD students and 3 master's students. 16 alumni. Applications close .
At a glance
- papers, 2023–2026
- 25/ year
- at T1 venues
- 33%
- PhD students
- 3
- MS students
- 3
- alumni listed
- 16
Papers by yearfrom DBLP, 2023–2026
- 17 papers2026 · T1 7 · collecting
- 21 papers2025 · T1 7
- 34 papers2024 · T1 10
- 22 papers2023 · T1 7
T1 venuesOtherVenues: ICASSP, ICLR, CVPR, AAAI, ECCV
Research focuspaper titles that use each topic's words
- Signal processing & information theory5 papers
- Speech enhancement & signal processing5 papers
- Affective & health speech0 papers
- affective computing0 papers
- affective0 papers
Paper list
From DBLP.
202617 papers
- IEEE Signal Process. Lett.An Adaptive Non-Linear Graph Filter in Semi-Supervised Graph Based Classification (opens in a new tab)
- ICLR (T1)ASMIL: Attention-Stabilized Multiple Instance Learning for Whole-Slide Imaging (opens in a new tab)
- ECCV (T1)CARA: Collision-Aware Resolution Adaptation for Multiresolution Hash Encoding Based Image Fitting (opens in a new tab)
- ICLR (T1)CL-DPS: A Contrastive Learning Approach to Blind Nonlinear Inverse Problem Solving via Diffusion Posterior Sampling (opens in a new tab)
- WACVComp4D: Compositional 4D Scene Generation (opens in a new tab)
- ICLR (T1)DreamPhase: Offline Imagination and Uncertainty-Guided Planning for Large-Language-Model Agents (opens in a new tab)
- Trans. Mach. Learn. Res.Dynamic Neural Graph Encoding of Inference Processes in Deep Weight Space (opens in a new tab)
- Frontiers Comput. Sci.Editorial: Deep learning for industrial applications (opens in a new tab)
- IEEE Signal Process. Mag.From Coordination to Execution: Positioning the IEEE Signal Processing Society at the Core of IEEE's Artificial Intelligence Ecosystem [From the Editor] (opens in a new tab)
- IEEE Internet Things J.HF-IDS: A Heuristic Factors-Based Semi-Supervised Model for Intrusion Detection Systems in IoT Networks (opens in a new tab)
- IEEE Signal Process. Mag.IEEE Signal Processing Society: State of Society [State of Society] (opens in a new tab)
- PIMRCLearning Identity Beyond Activity: Open-Set User Verification with WiFi CSI (opens in a new tab)
202521 papers
- WF-IoTA Hybrid LoRa and Wi-Fi Mesh System for Multi-Floor Elderly Tracking and Monitoring (opens in a new tab)
- ICIPAdvancements in Medical Image Classification Through Fine-Tuning Natural Domain Foundation Models (opens in a new tab)
- IEEE Syst. J.Distributed Anomaly Detection With Attention-Guided Diffusion Models and Client-Side Defect Generation (opens in a new tab)
- CVPR (T1)Emphasizing Discriminative Features for Dataset Distillation in Complex Scenarios (opens in a new tab)
- WF-IoTEnhancing LOS/NLOS Classification in UWB with Robust Feature Engineering (opens in a new tab)
- Pattern RecognitionFedPnP: Personalized graph-structured federated learning (opens in a new tab)
- IEEE Open J. Commun. Soc.Hierarchical Multimodal Federated Learning Over Cell-Free Massive MIMO Systems (opens in a new tab)
- IEEE Signal Process. Mag.IEEE Signal Processing Society: State of the Society (opens in a new tab)
- PIMRCLarge-Scale Federated Learning for Hybrid Cell-Free Massive MIMO and Visible Light Communication Systems (opens in a new tab)
- ICLR (T1)Learning to Adapt Frozen CLIP for Few-Shot Test-Time Domain Adaptation (opens in a new tab)
- IEEE Signal Process. Mag.Maintaining Standards, Broadening Reach: ICIP's Next Steps [President's Message] (opens in a new tab)
- IEEE AccessMulti-Modal Federated Learning Over Cell-Free Massive MIMO Systems for Activity Recognition (opens in a new tab)
202434 papers
- ICASSP (T1)A Robust Quantile Huber Loss with Interpretable Parameter Adjustment in Distributional Reinforcement Learning (opens in a new tab)
- Neural ComputationActive Inference and Reinforcement Learning: A Unified Inference on Continuous State and Action Spaces Under Partial Observability (opens in a new tab)
- ICLR (T1)Adapting to Distribution Shift by Visual Domain Prompt Generation (opens in a new tab)
- ICASSP (T1)AQF: Assessing the Quality of Hyperspectral Reconstruction with a Learnable Metric (opens in a new tab)
- CVPR WorkshopATOM: Attention Mixer for Efficient Dataset Distillation (opens in a new tab)
- BMVC WorkshopCan Pretrained Face Verification Models Distinguish True Identity from Deepfakes? (opens in a new tab)
- IEEE Internet Things J.CLSA: Contrastive-Learning-Based Survival Analysis for Popularity Prediction in MEC Networks (opens in a new tab)
- ECCV (T1)Data-to-Model Distillation: Data-Efficient Learning Framework (opens in a new tab)
- NeurIPS (T1)Diffusion4D: Fast Spatial-temporal Consistent 4D generation via Video Diffusion Models (opens in a new tab)
- ICHMSDigital AirComp-Assisted Federated Edge Learning with Adaptive Quantization (opens in a new tab)
- ECCV (T1)Distribution Alignment for Fully Test-Time Adaptation with Dynamic Online Data Streams (opens in a new tab)
- Phys. Commun.Enhancing security for physical layer communication in RIS-aided MIMO-NOMA systems in the presence of an eavesdropper (opens in a new tab)
202322 papers
- IEEE AccessA Conformal Leaky-Wave Antenna Design for IoMT-Based WBANs (opens in a new tab)
- IEEE Trans. Mob. Comput.A Kernel Method to Nonlinear Location Estimation With RSS-Based Fingerprint (opens in a new tab)
- ICASSP (T1)A New Probabilistic Distance Metric with Application in Gaussian Mixture Reduction (opens in a new tab)
- ICASSP (T1)A Unified Uncertainty-Aware Exploration: Combining Epistemic and Aleatory Uncertainty (opens in a new tab)
- DSPCoPo: Self-supervised Contrastive Learning for Popularity Prediction in MEC Networks (opens in a new tab)
- DSPCross Attention-based Fusion of Deep and Radiomics Features for Lung Nodule Invasiveness Prediction (opens in a new tab)
- ICCV (T1)DataDAM: Efficient Dataset Distillation with Attention Matching (opens in a new tab)
- IEEE AccessDistillation and Ordinary Federated Learning Actor-Critic Algorithms in Heterogeneous UAV-Aided Networks (opens in a new tab)
- IEEE AccessDL4ALL: Multi-Task Cross-Dataset Transfer Learning for Acute Lymphoblastic Leukemia Detection (opens in a new tab)
- Frontiers Comput. Sci.Editorial: Deep neural computing for advanced automotive system applications (opens in a new tab)
- IEEE Trans. Comput. Soc. Syst.Federated Learning and Blockchain-Enabled Fog-IoT Platform for Wearables in Predictive Healthcare (opens in a new tab)
- IEEE Internet Things J.Graph Federated Learning for CIoT Devices in Smart Home Applications (opens in a new tab)
Where alumni went16 listed
Apply to TorontoFall 2027
Computer Science MSc/PhD
- Round
- Single round (Dec 1)
- Opens
- —
- GRE
- optional
- English
- TOEFL/IELTS if applicable
- Fee
- CAD 135
Confirmed on the program page.
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