Mohamad Qadri

I am a second year PhD student at the Robotics Institute at Carnegie Mellon University, where I work with Michael Kaess in the the Robotics Perception Lab . I work on statistical methods for state estimation. I am interested in developing algorithms for efficient and robust inference at the intersection of linear algebra and probabilistic graphical models.

I completed my Masters in Robotics at CMU working with George Kantor on Simultaneous Localization and Mapping (SLAM) in agricultural environments. Prior to that, I worked with Simon Lucey and Laszlo Jeni on monocular 3D reconstruction. In my undergrad, I majored in Electrical Engineering at the University of Maryland - College Park.

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Neural Implicit Surface Reconstruction using Imaging Sonar
Mohamad Qadri, Michael Kaess, Ioannis Gkioulekas
ICRA, 2023
arXiv / video / code

We present a technique for dense 3D reconstruction of objects using an imaging sonar. We represent the geometry as a neural implicit function.

Conditional GANs for Sonar Image Filtering with Applications to Underwater Occupancy Mapping
Tianxiang Lin, Akshay Hinduja, Mohamad Qadri, Michael Kaess
ICRA, 2023
arXiv / video

This paper presents a novel application of conditional Generative Adversarial Networks (cGANs) to train a model to produce noise-free sonar images.

Runahead A*: Speculative Parallelism for A* with Slow Expansions
Mohammad Bakhshalipour, Mohamad Qadri, Seyed Borna Ehsani, Dominic Guri, Maxim Likhachev Phillip B. Gibbons
ICAPS, 2023

We go beyond traditional parallelism of the A* algorithm and introduce RA* (Runahead A*) which performs speculative parallelism of A*.

InCOpt: Incremental Constrained Optimization Using the Bayes Tree
Mohamad Qadri, Paloma Sodhi, Joshua G. Mangelson, Frank Dellaert, Michael Kaess
IROS, 2022
paper / video / code

We present an Augmented Lagrangian-based incremental constrained optimizer that views matrix operations as message passing over the Bayes tree.

RACOD: algorithm/hardware co-design for mobile robot path planning
Mohammad Bakhshalipour, Seyed Borna Ehsani, Mohamad Qadri, Dominic Guri, Maxim Likhachev Phillip B. Gibbons
ISCA, 2022

RACOD is an algorithm/hardware co-design for mobile robot path planning. It consists of two main components: CODAcc, a hardware accelerator for collision detection; and RASExp, an algorithm extension for runahead path exploration.

Autonomous Apple Fruitlet Sizing and Growth Rate Tracking using Computer Vision
Harry Freeman, Mohamad Qadri, Abhisesh Silwal, Paul O'Connor, Zachary Rubinstein, Daniel Cooley, George Kantor
In Submission at IEEE Transactions on Robotics (T-RO)
arXiv / video

We develop a computer vision method to size and track the growth rates of apple fruitlets. Fruitlets are sized using a combination of deep learning algorithms and are associated across days using a novel Attentional Graph Neural Network approach.

Toward Semantic Scene Understanding for Fine-Grained 3D Modeling of Plants
Mohamad Qadri, Harry Freeman, , Eric Schneider , George Kantor
AIAFS AAAI, (2021)
paper / video

In this paper, we use semantics and environmental priors to construct accurate 3D maps of agricultural environments.

Robotic Vision for 3D Modeling and Sizing in Agriculture
Mohamad Qadri,
Masters thesis

Other Projects

Semi-Supervised Learning via Offline Pseudolabel Generation and Consistency Regularization
Mohamad Qadri, Maggie Collier
Exploring the link between Geodesically Convex Optimization and Contraction Analysis
Mohamad Qadri, Chiheb Boussemma
A study of Joint-Space Control of Non-Linear Robotics manipulators
Mohamad Qadri

Source code