Bio: I’m an assistant professor at Indiana University. I’m with the Department of Intelligent Systems Engineering at the School of Informatics, Computing, and Engineering. I also belong to a few other academic programs and research centers: Data Science, Cognitive Science (core member), Department of Statistics (affiliated), and Center for Algorithms and Machine Learning (CAML). I earned my PhD in the Department of Computer Science at the University of Illinois at Urbana-Champaign. Before joining UIUC, I worked as a researcher in ETRI, a national lab in Korea, from 2006 to 2011. I received my 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. My research focuses on developing machine learning algorithms applied to audio processing, stressing their computational efficiency in the resource-constrained environments or in the applications involving large unorganized datasets. I received Richard T. Cheng Endowed Fellowship from UIUC in 2011. Google and Starkey grants also honored my ICASSP papers as the outstanding student papers in 2013 and 2014, respectively. I was selected as an outstanding teaching assistant for the course “Machine Learning for Signal Processing” in the Fall 2015, too. CV (pdf)
Bio: I’m in my fourth year of 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. Homepage: http://homes.sice.indiana.edu/scwager/ Email: scwager-at-indiana-dot-edu
Kai Zhen
Bio: I’m working on optimizing lightweight deep neural network-based end-to-end systems for speech 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. Homepage: http://pages.iu.edu/~zhenk Email: zhenk-at-iu-dot-edu
Ph.D. Students
Sunwoo Kim
Bio: I am a second yearPhD student studying in CS/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. 🙂 Homepage: http://kimsunwoo.com Email: kimsunw-at-indiana-dot-edu CV
Aswin Sivaraman
Bio: I am a first-year 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 current research interests lie in machine learning approaches to speech and music applications, such as audio compression or autotune. Homepage: http://aswinsivaraman.com Email: asivara-at-iu-edu CV
R. David Badger
Bio: I am a first year PhD student at IU SICE ISE. I received my BSEE from the University of Kentucky and MSECE from IUPUI. My research interests include applying ML algorithms to solve RF time/frequency domain problems as well as challenges in the audio spectrum.
