my main research interests, along with relevant publications

You can find below a list of research topics I have worked on, along with indicative relevant publications. Note that a few of them might fall within multiple categories.

Representation Learning

Feature Aggregation

Information-theoretic Learning

Adaptive Normalization for Deep Learning

Lightweight Machine/Deep Learning

Knowledge Distillation

Adaptive Computational Graphs for DL N. Passalis, and A. Tefas, “Adaptive Inference for Face Recognition leveraging Deep Metric Learning-enabled Early Exits,” European Signal Processing Conference (EUSIPCO), 2021

Dimensionality Reduction

Lighweight Architectures


Timeseries Analysis

Timeseries analysis

Trading using Deep Reinforcement Learning

Robotics Perception

Deep Reinforcement Learning for Robotics Control

Perception and Control

Active Perception

Photonic Neuromorphic Deep Learning

Ex-situ training for photonic neuromorphic architectures

Noise-resilient Deep Learning

Other Deep Learning Topics

Deep Generative Models

Privacy Preserving Learning

Few-shot Learning

Exploratory Data Analysis

Sentiment Analysis

Multimodal Fusion

Neural Style Transfer

Brain Decoding


Visual Question Answering

Action Recognition

Information Retrieval