In audio processing, he works on noise robustness, computational auditory scene analysis, microphone array processing, and source separation. In speech recognition, he works on basic research issues that need to be addressed for better automatic speech recognition. In neural networks, he is interested in specialized architectures for signal processing, learning, and information routing.

In addition to all of these topics, a major part of his research is focused on privacy preserving algorithms for speech and audio processing. Speech is possibly the most private form of communication; yet, when a speech processing engine such as a voice authentication system or a speech recognition service operates, it requires complete access to the voice recording. This has security, privacy, and economic implications, such as snoopers or malicious systems who may use the data to derive undesired information (e.g. speaker demographics), create fake recordings, or impersonate the user. His team continues to develop various cryptographic and other techniques to deal with these problems.