Ishwarya Ananthabhotla

Machine Learning and Audio Research Scientist, Musician and Audio Enthusiast.

About Me Publications Music & Writing Radio Shows Assistive Tech @ MIT

About Me

I am currently a Research Scientist on the Meta Reality Labs Research Audio Team. At present, I work on machine learning applied to problems in room acoustics, spatial audio, auditory perception, and behavior and communication understanding in conversations. More generally, my research interests lie at the intersection of machine learning, signal processing, cognition, and audio.

I completed my Bachelors in Electrical Engineering and Computer Science from MIT in 2015, my M.Eng. from MIT in 2016, and my PhD from Prof. Joe Paradiso's Responsive Environments group at the MIT Media Lab in 2021. My dissertation work entailed exploring methods to build statistical models of how our brains interact with the sounds around us, and translating these models to the auditory interfaces of the future to facilitate more meaningful, compelling experiences. I was supported by the NSF Graduate Research Fellowship from 2016-2019, and was supported by the 2020 Apple AI/ ML Fellowship through the end of my PhD. Outside of research, I enjoy singing, playing instruments, and writing; while at MIT, I also enjoyed DJ-ing at the WMBR radio station.

Publications

(Accepted) The Audio-Visual Conversational Graph: From an Egocentric-Exocentric Perspective
Wenqi Jia, Miao Liu, Hao Jiang, Ishwarya Ananthabhotla, James M. Rehg, Vamsi Krishna Ithapu, Ruohan Gao. CVPR, 2024.

(Accepted) Self‑motion as Supervision for Egocentric Audiovisual Localization.
Calvin Murdock, Ishwarya Ananthabhotla, Hao Lu, Vamsi Krishna Ithapu. ICASSP, 2024.

(Accepted) On HRTF Notch Frequency Prediction Using Anthropometric Features and Neural Networks.
Lior Arbel, Ishwarya Ananthabhotla, Zamir Ben‑Hur, David Lou Alon, Boaz Rafaely. ICASSP, 2024.

(Accepted) Hearing Loss Detection from Facial Expressions in One‑on‑one Conversations.
Yufeng Yin, Ishwarya Ananthabhotla, Vamsi Krishna Ithapu, Stavros Petridis, Yu‑Hsiang Wu, Christi Miller. ICASSP, 2024.

A Two‑Dimensional Threshold Test for Reverberation Time and Direct‑to‑Reverberant Ratio.
Nils Meyer‑Kahlen, Sebastià Amengual Garí, Ishwarya Ananthabhotla, Paul Calamia. I3DA, 2023.

Autonomous Room Acoustic Measurements Using Rapidly‑Exploring Random Trees and Gaussian Processes.
Georg Gotz, Ishwarya Ananthabhotla, Sebastià Amengual Garí, Paul Calamia. Forum Acusticum, 2023.

Towards Improved Room Impulse Response Estimation for Speech Recognition.
Anton Ratnarajah, Ishwarya Ananthabhotla, Vamsi Krishna Ithapu, Pablo Hoffmann, Dinesh Manocha, Paul Calamia. ICASSP, 2023.

Towards the Prediction of Perceived Room Acoustical Similarity.
Hannes Helmholz, Ishwarya Ananthabhotla, Paul Calamia, Sebastià Amengual Garí. AES AVAR, 2022. Best Student Paper.

Towards “Gestalt” Computation in Sound.
Ishwarya Ananthabhotla, David B. Ramsay, Joseph A. Paradiso. NeurIPS Workshop on Machine Learning for Creativity and Design, 2022.

Modifying Causal Uncertainty in Sound Objects.
Tal Boger, Ishwarya Ananthabhotla, Joseph A. Paradiso. ACM Audio Mostly, 2021.

Cognitive Audio Interfaces: Mediating Sonic Information with an Understanding of How We Hear.
Ishwarya Ananthabhotla, David B. Ramsay, Clement Duhart, Joseph A. Paradiso. IEEE Pervasive Computing, 2021.

A Framework for Designing Head‑related Transfer Function (HRTF) Distance Metrics that Capture Localization Perception.
Ishwarya Ananthabhotla, Vamsi Krishna Ithapu, W. Owen Brimijoin. JASA Express Letters, 2021.

Using a Neural Network Codec Approximation Loss to Improve Source Separation Performance in Limited Capacity Networks.
Ishwarya Ananthabhotla, Sebastian Ewert, Joseph A. Paradiso. IJCNN Special Session on Deep Neural Audio Processing, 2020.

Towards a Perceptual Loss: Using a Neural Network Codec Approximation as a Loss for Generative Audio Models.
Ishwarya Ananthabhotla, Sebastian Ewert, Joseph A. Paradiso. ACM Multimedia, 2019.

The Intrinsic Memorability of Everyday Sounds.
Ishwarya Ananthabhotla*, David B. Ramsay*, Joseph A. Paradiso. AES Immersive and Interactive Audio, 2019.

HCU400: An Annotated Dataset for Exploring Aural Phenomenology through Causal Uncertainty.
Ishwarya Ananthabhotla*, David B. Ramsay*, Joseph A. Paradiso. ICASSP 2019.

SoundSignaling: Realtime, Stylistic Modification of a Personal Music Corpus for Information Delivery.
Ishwarya Ananthabhotla and Joseph A. Paradiso. ACM IMWUT, 2018.

VisualSoundtrack: An Approach to Style Transfer in the Context of Soundtrack Composition.
Ishwarya Ananthabhotla, Joseph A. Paradiso. International Computer Music Conference (ICMC), 2017.

Music & Writing

Music

Music is perhaps my biggest passion. I've been learning and singing Carnatic music since I was five or six years old, and I have always been captivated by the artform's expressive nature and lyrical beauty. It has provided me with a sense of comfort, an avenue of relaxation, and a bridge into a past rich with culture, tradition, and faith. I also enjoy singing lighter forms of classical music, and enjoy jamming with friends and family. Over the years, I've learned to play a variety of instruments including the piano, violin, harmonium, and naal (a cousin of the tabla). I also enjoy dabbling in song writing, music production, and mixing and mastering in my spare time.

Some performances and recordings across genres: Sruthi Laya TCD 2014, MIT C-Show 2016, Someone Like You (Arr.) 2015

Writing

Many of my friends know me as perpetually having my head buried in a journal, scribbling down some thought or other. I've loved writing short stories and poetry since I was in elementary school, and after taking several fantastic creative writing classes here at MIT, I've had the opportunity to refine my writings and grow as an author. Some of my writing was awarded one of MIT's Ilona Karmel prizes, and I've written a few plays that have aired on my WMBR production, "The Daydream Company."

Assistive Technology Club & Hackathon

In my last few years at MIT, Assistive Technologies is a space that has become particularly close to my heart. After being inspired by Professor Seth Teller and his incredible class on designing AT (6.811), I worked closely with a team of students to organize ATHack 2014, MIT's first Assistive Technologies Hackathon! Since then, I have been involved with nine instances of the hackathon, which has continued on as an annual MIT event. The aim of both the class and the hackathon is to bring together "co-designers" in the community who live with disabilities and student engineers to work towards innovative solutions.

Media: MIT News on ATHack2017, MIT News on ATHack2015, An article from the MIT Lincoln Lab, Continuing the Legacy: Assistive Technology at MIT, Perkins on ATHack2015

Interested in sponsoring, getting involved, or learning about past projects? Check out the group's page below.