Minje Kim, Ph.D.

Bio: Minje Kim is an assistant professor in the Dept. of Intelligent Systems Engineering at Indiana University, where he leads his research group, Signals and AI Group in Engineering (SAIGE). He is also an Amazon Visiting Academic, consulting for Amazon Lab126. At IU, he is affiliated with various programs and labs such as Data ScienceCognitive ScienceDept. of StatisticsCenter for Algorithms and Machine Learning, and Crisis Technologies Innovation Lab. He earned his Ph.D. in the Dept. of Computer Science at the University of Illinois at Urbana-Champaign. Before joining UIUC, He worked as a researcher in ETRI, a national lab in Korea, from 2006 to 2011. Before then, he received his Bachelor’s and Master’s degrees in the Division of Information and Computer Engineering at Ajou University (with honor) and in the Department of Computer Science and Engineering at POSTECH (Summa Cum Laude) in 2004 and 2006, respectively. During his career as a researcher, he has focused on developing machine learning models for audio signal processing applications, such as speech enhancement, source separation, MPEG audio coding, music information retrieval, etc., stressing their computational efficiency in the resource-constrained environments or in the applications involving multichannel observations. He received Richard T. Cheng Endowed Fellowship from UIUC in 2011. Google and Starkey grants also honored his ICASSP papers as an outstanding student paper in 2013 and 2014, respectively. He is an IEEE Senior Member and also an elected member of the IEEE Audio and Acoustic Signal Processing Technical Committee (2018-2020 and 2021-2023). He is serving as an Associate Editor for EURASIP Journal of Audio, Speech, and Music Processing, and as a Consulting Associate Editor for IEEE Open Journal of Signal Processing. He also serves as a reviewer, program committee member, or area chair for major machine learning and signal processing venues, such as NeurIPS, ICML, AAAI, IJCAI, ICLR, ICASSP, ISMIR, IEEE T-ASLP, etc. He is on more than 50 patents as an inventor. 

Ph.D. Candidates

Sanna Wager

Bio: I’m in the Music track of the PhD in Informatics and Computing at Indiana University. My adviser is Minje Kim. My undergraduate degree was in Bassoon Performance at Indiana University’s Jacobs School of Music, studying under Kathleen McLean. My undergraduate minor was math. I am interested in how technology influences the way people relate to music, and how we can use technology to develop our understanding of music. Music has been at the front end of technical innovation for thousands of years. Pythagoras described its deep connection to math, architecture, astronomy, and psychology; Beethoven worked with piano makers to develop instruments that could handle his compositions; conductor Herbert von Karajan was among the first to acquire the newest analog recording devices. I strive to promote interaction between the fields of acoustic music and computing so that the recent innovation in the digital world can be applied in the best possible way to music. I hope to 1) develop knowledge of music representation in technology, so that results are aesthetically convincing, 2) give musicians more general and easy access to training in music technology, and 3) encourage the development of music-related technology that helps the youngest generation connect to high-quality music as listeners and performers.
Email: scwager-at-indiana-dot-edu

Kai Zhen
(Computer Science and Cognitive Science)

Bio: I’m working on optimizing lightweight deep neural network-based end-to-end systems for speech/audio coding and enhancement. Some of these methods are found necessary to be integrated by domain knowledge in psychoacoustics and human auditory perception. Maintaining a good work-life balance has always been my target for my talent in table tennis, badminton, and opera singing. Life is complex — it has both real and imaginary parts.
Email: zhenk-at-iu-dot-edu

Sunwoo Kim
(Intelligent Systems Engineering)

Bio: I am a PhD student studying in ISE. Before IU, I lived in Singapore and then studied Physics at UIUC. Currently, my research interests are in end-to-end systems, latent feature representations, and attention mechanisms. On my free time, I like to watch TV (too much), read books (epics), play board games, and go out to eat. I love meeting people and doing things, have nice conversations so please don’t hesitate to ask. 🙂
Email: kimsunw-at-indiana-dot-edu

Ph.D. Students

Aswin Sivaraman
(Intelligent Systems Engineering)

Bio: I am a PhD student at Indiana University (IU) hailing from the Chicago suburbs. I received my BS in Electrical Engineering at the University of Illinois at Urbana-Champaign (UIUC). My research focuses on machine learning applications to music and speech processing applications, addressing tasks like noise reduction, dereverberation, style transfer, and diarization. Using deep learning approaches, I incorporate prior knowledge about digital audio and digital signal processing in order to compress neural networks or to boost model efficiency.
Email: asivara-at-iu-edu

R. David Badger
(Intelligent Systems Engineering)

Bio: I am a PhD student at IU ISE. I received my BSEE from the University of Kentucky and MS in ECE from IUPUI. My research interests include applying ML algorithms to solve RF time/frequency domain problems as well as challenges in the audio spectrum. 
Email: rdbadger-at-iu-edu

Haici Yang
(Intelligent Systems Engineering)

Bio: I joined IU ISE and SAIGE in Fall 2019. I’m still new to the field but feel excited about signal processing with machine learning, especially its potential application on music analysis and generation. A crazy musical instrument learner and passionate runner. Love outdoor activities and non-fictional books.

Email: hy17-at-iu-edu


  • Mrinmoy Maity
    • MS in Intelligent Systems Engineering (Spring 2019)
    • Now at Microsoft as a Data Scientist