Ayano Hiranaka

I am a CS PhD student at University of Southern California (USC) co-advised by Professor Daniel Seita and Professor Erdem Biyik.

Prior to coming to USC, I completed my Master's degree at Stanford University, where I was a research assistant at Stanford Vision and Learning Lab (SVL). I received my undergraduate degree in mechanical engineering from the University of Illinois at Urbana-Champaign (UIUC).

I have also been fortunate to work as a research intern at Sony AI's Deep Generative Modeling team in Tokyo.

My experiences are a unique blend of computer science and mechanical engineering, ranging from AI to robotics to mechanical design.

Email  /  CV  /  Google Scholar  /  Github

Publications

I design AI agents, both embodied and non-embodied, that co-evolve with humans through effective communication and collaboration. My research focuses on creating learning processes where humans help AI agents learn, and AI agents, in turn, foster human growth. I am passionate about building human-AI teams that achieve shared understanding and long-term development through mutual adaptation and continuous learning.

Improving robot trajectories by learning reward functions aligned with human preferences, utilizing a joint represntation space of robot trajectory and natural language feedback.

Finetuning text-to-image diffusion models for a variety of tasks in a human-feedback-efficient manner by combining feedback-aligned representation learning and feedback-guided image generation. Work during internship at Sony AI.

Brain-robot interface system for everyday activities using EEG signal decoding, primitive skills, and robot intelligence aided by foundation models.

Combining intuitive skill-based action space and human evaluative feedback, enabling a more safe and sample efficient long-horizon task learning in the real world.

A sample-efficient RLHF framework for low-level robot control policy leveraging a human-interpretable high-level state representation for active query.

Research Projects

Mechatronic system that detect, track, and collect spectral data from moving, light-emitting objects in the night sky.
Mentored and sponsored by Prof. Nick Glumac.

Real-time identification of a note played on a piano with a probabilistic approach using a feedback particle filtering algorithm.
Mentored by Prof. Amirhossein Taghvaei and Prof. Prashant Mehta.

Investigation of atomization-based cutting fluid spray condition to maximize tool life for deep micro-drilling. Automatic drill parameter measurements from microscope images using keypoint detection.
Mentored by Dr. Amy Lee and Prof. Shiv Kapoor.

Miscllaneous Projects

In progress retro-style simulaiton RPG in Unity.
Personal hobby project.

AR piano using real-time hand keypoint tracking from RGB webcam stream.
CS231A Computer Vision from 3D Reconstruction to Recognition course project.

Drum-player humanoid simulator that playes the beats speficied by a user.
CS225A Experimental Robotics course project.

A vegetable slicer operating from single crank input, quadruped walking robot, and steel ball transporter mechanism.