About Me:

Hi, I’m Joe! I’m a third-year Ph.D. student passionate about using robotics to improve everyday life.

My work inherits from human neuroscience and psychology to create robot platforms capable of functioning with and around humans.

I’m part of the Department of Mechanical Engineering at Temple University where I work in the Temple Robotics and Artificial Intelligence Laboratory (TRAIL) under the guidance of Dr. Philip Dames.

Focus Areas

Computer Vision

Neural Rendering

3D Gaussian Splatting

3D Reconstruction

Robotics

Control Policies

Bimanual Manipulation

World Modelling

Publications

[J2] J. N. Bruno, O. Shorinwa, C. He, X. Lui, T. Chen, P. Dames and M. Schwager, “Cooperative Prediction Model for Ego-Centric Collaboration,” (In Progress).

[C4] C. He, X. Liu, G. S. Camps, J. N. Bruno, G. Sartoretti, and M. Schwager, “Demystifying diffusion policies: Action memorization and simple lookup table alternatives,” arXiv preprint arXiv:2505.05787, 2025. (Under review at ICLR 2026).

[J1] T. Chen, O. Shorinwa, J. N. Bruno, A. Swann, J. Yu, W. Zeng, K. Nagami, P. Dames, and M. Schwager, “Splat-Nav: Safe real-time robot navigation in Gaussian splatting maps,” IEEE Trans. Robot., vol. 41, 2025.

[C3] A. Bose, J. N. Bruno, and L. Bai, “Time-constrained finite-horizon path planning solution for micromouse extreme problem,” Proc. IEEE Mobile Ad-Hoc and Smart Systems (MASS), 2022.
[C2] J. N. Bruno, F. D. Moran, H. I. Khajanchi, and A. A. Adegbege, “Analog solver for embedded model predictive control with application to quadruple tank system,” Proc. American Control Conf. (ACC), 2021.

[C1] H. I. Khajanchi, J. N. Bruno, and A. A. Adegbege, “An embedded FPGA architecture for real-time model predictive control,” Proc. Int. Federation of Automatic Control (IFAC), 2020.