Information-Theoretic AI
Transfer entropy, mutual information, uncertainty analysis, causal inference, and interpretable AI for nonlinear systems.
Information-Theoretic AI • Statistical Signal Processing • Causal Machine Learning
Researcher working at the intersection of information theory, statistical signal processing, transfer entropy, speech/audio intelligence, Bayesian modeling, and causal analysis of complex systems.
Special Faculty Member, Carnegie Mellon University
Assistant Professor, Antalya Bilim University
My research develops data-driven and probabilistic methods for understanding dependence, causality, and uncertainty in signals and complex dynamical systems. A central theme is the use of information-theoretic quantities—especially transfer entropy and mutual information—to move beyond correlation and identify directional relationships in speech, neural, climate, remote-sensing, and industrial data.
Research Themes
Transfer entropy, mutual information, uncertainty analysis, causal inference, and interpretable AI for nonlinear systems.
Audio watermarking, steganalysis, speech biometrics, voice disguise detection, and secure voice technologies.
Bayesian filtering, particle filtering, non-Gaussian modeling, heavy-tailed distributions, and time-varying AR processes.
Information-theoretic analysis of climate feedbacks, aerosol bias correction, and nonlinear Earth-system relationships.
Selected Projects
Development of advanced signal processing techniques for perceptually transparent and robust audio watermarking, including amplitude, phase, spread-spectrum, and feature-based strategies across time and frequency domains.
Transfer entropy and mutual information methods for identifying nonlinear cause-effect dependencies among climate variables, including applications to cloud coverage, sea surface temperature, and aerosol optical depth analysis.
Voice biometrics, forensic anthropometry from speech, voice disguise analysis, and computer vision methods for mission-readiness evaluation.
Statistical design of experiments, process analytics, anomaly detection, industrial data analysis, and patented contributions to materials and manufacturing research.
Publications
For better Google Scholar indexing, each publication should eventually receive its own HTML page with title, authors, abstract, DOI, PDF link, BibTeX, and keywords.
Teaching
Introduction to Generative AI, machine learning foundations, probability, stochastic processes, and information theory.
Digital signal processing, statistical signal processing, speech processing, and time-series analysis.
Feedback and control systems, circuit theory, robotics, telecommunications, and laboratory-based engineering education.
Talks, Awards, and Service
Keynote speaker, ACDSA International Conference on Artificial Intelligence, Computer, Data Sciences and Applications.
Best Paper Award, International Workshop on Biometrics and Forensics.
Senior Member of IEEE.
NATO-TUBITAK Research Fellowship, Consiglio Nazionale delle Ricerche, Italy.
Contact
For research collaboration, invited talks, student advising, and academic communication, please use the contact links below.
Email: d.gencaga@ieee.org
CMU Email: denizg@andrew.cmu.edu
Location: Pittsburgh, PA / Antalya, Turkey