Sudarsana Reddy Kadiri
Research Assistant Professor of Electrical and Computer Engineering
Education
Biography
Dr. Sudarsana Reddy Kadiri is a Research Assistant Professor in the Department of Electrical and Computer Engineering at the Viterbi School of Engineering, University of Southern California (USC). He is affiliated with the Signal Analysis and Interpretation Laboratory (SAIL), directed by Prof. Shrikanth Narayanan. His current research focuses on advancing the frontiers of bio-marking human health through multimodal signal analysis. His work integrates methodologies from signal processing, machine learning, and deep learning to extract meaningful indicators of health and well-being from speech, physiological, and neurological signals. Beyond this core focus, his interests span signal processing, speech and language technologies, affective computing, digital health, and auditory neuroscience.Prior to his current role, Dr. Kadiri served as a Research Scientist at USC and held research appointments at Aalto University, Finland, as a Research Fellow and Postdoctoral Researcher. He received his Ph.D. from IIIT-Hyderabad and his B.Tech. from JNTU-Hyderabad, India. He has co-supervised one Ph.D. and four master’s theses, and currently co-advises two doctoral students. He has authored over 90 peer-reviewed publications and regularly serves as a reviewer for IEEE, Elsevier, Springer, and other leading journals and conferences. His recognitions include the Tata Consultancy Services (TCS) Fellowship and two sub-challenge awards in the ACM-MM ComParE Challenge 2022.
Research Summary
Dr. Kadiri’s research addresses healthcare challenges across the lifespan by developing scalable, interpretable, and multimodal biomarkers that integrate behavioral, physiological, and neurological signals. He focuses on uncovering causal links among these modalities in clinical populations to enable early detection, risk estimation, and intervention monitoring. His work spans developmental and clinical stages—ranging from identifying early social and communicative disruptions in children with neurodevelopmental conditions (e.g., Autism), to modeling mental health risk in young adults, and tracking cognitive and emotional decline in older adults within the aging population. These efforts advance research across neurodevelopmental, psychiatric, and neurodegenerative disorders, contributing to effective, evidence-based digital health solutions.His broader research interests include:
• Bio-marking of health from multimodal signals, including speech, EEG, ECG, eye-tracking, and other physiological data
• Speech and language technologies, including speech recognition, synthesis, and prosody analysis
• AI and ML for healthcare, with applications in voice/speech disorders, autism, depression/suicidality, and cognitive decline
• Computational paralinguistics and affective computing, Biomedical signal processing
• Analysis of speech, singing voice, behavioral, and social signals
• Auditory perception and cognitive processing
Appointments
- Ming Hsieh Department of Electrical and Computer Engineering
- EEB 428
- Hughes Aircraft Electrical Engineering Center
- 3740 McClintock Ave., Los Angeles, CA 90089
- USC Mail Code: 2564
- (213) 512-7388
- skadiri@usc.edu