Research Highlights

See my publications on Google Scholar or ORCID

Funding

(Sep. 2024 - Jun. 2026)
I am very grateful to the TomKat Center for Sustainable Energy at Stanford University for funding my current research via the TomKat Center Graduate Fellowship for Translational Research. As a fellow, I am developing methods to form 3D digital twins of the wildland-urban interface to better support large-scale wildfire management.

See more at https://tomkat.stanford.edu/people/daniel-neamati-0

Our work is in collaboration with Stanford's Jasper Ridge 'Ootchamin 'Ooyakma Biological Preserve. See more at https://jrbp.stanford.edu/research/projects/3d-reconstruction-ecosystem-response-wildland-urban-interface

See more on our interdisciplinary Stanford Smoke Mesh (SMesh) Project: https://smesh.info/

(Sep. 2021 - Jun. 2024)
I am very grateful to the National Science Foundation (NSF) for funding my past research via the Graduate Research Fellowship (GRFP). With the NSF GRFP, I focused on the impact of 3D map representation on urban and suburban location services.

Active Research

(2021-Present) 3D Mapping for Sustainability and Localization

This is the core subject of my Ph.D. research. Below is a record of my published or presented research, but plenty more is on the horizon!

Journal Papers:

K. Iiyama, D. Neamati, and G Gao, Autonomous Constellation Fault Monitoring with Inter-satellite Links: A Rigidity-Based Approach. NAVIGATION. 2025 (In Review)
D. Neamati, S. Bhamidipati and G. Gao, Mosaic Zonotope Shadow Matching for Risk-Aware Autonomous Localization in Harsh Urban Environments, Artificial Intelligence. Sep 2023; DOI: 10.1016/j.artint.2023.104000.
D. Knowles, A.V. Kanhere, D. Neamati, G. Gao, gnss_lib_py: Analyzing GNSS Data with Python, SoftwareX. Sep 2024; DOI: 10.1016/j.softx.2024.101811.

Conference Papers:

D. Neamati, M. Partha, S. Gupta, and G. Gao, "Neural City Maps for GNSS Shadow Matching," Proceedings of the Institute of Navigation GNSS+ conference (ION GNSS+ 2024), Baltimore, MD.
M. Partha, D. Neamati, S. Gupta, and G. Gao, "Robust 3D Map-Matching With Visual Environment Features for Neural City Maps," Proceedings of the Institute of Navigation GNSS+ conference (ION GNSS+ 2024), Baltimore, MD.
K. Iiyama, D. Neamati, S. Gupta, and G. Gao, "Autonomous Constellation Fault Monitoring with Inter-Satellite Links: A Rigidity-Based Approach," Proceedings of the Institute of Navigation GNSS+ conference (ION GNSS+ 2024), Baltimore, MD.
D. Neamati, S. Gupta, M. Partha, and G. Gao, "Neural City Maps for GNSS NLOS Prediction," Proceedings of the Institute of Navigation GNSS+ conference (ION GNSS+ 2023), Denver, CO, Sep 2023. Best Presentation of the Session Award
D. Neamati, S. Bhamidipati, and G. Gao, "Set-Based Ambiguity Reduction in Shadow Matching with Iterative GNSS Pseudoranges," Proceedings of the Institute of Navigation GNSS+ conference (ION GNSS+ 2022), Denver, CO, Sep 2022. Best Presentation of the Session Award

Posters and Presentations:

D. Neamati and G. Gao, "3D Reconstruction of Ecosystem Response," Jasper Ridge 'Ootchamin 'Ooyakma Biological Preserve - Prescribed Fire Research Convening, Feb. 2025. https://jrbp.stanford.edu/news/research-convening-prescribed-fire
D. Neamati and G. Gao, "3D Digital Twins of Environments: The Big and Small," GIS Day at Stanford: GeoAI, Nov. 2024
M. Partha, D. Neamati, and G. Gao, "Stanford Robotics Center Digital Twin," Stanford Robotics Center Grand Opening, Nov. 2024. https://src.stanford.edu/src-launch-hub and https://src.stanford.edu/demo/src-digital-twin
M. Partha, E. Biju, D. Neamati, S. Gupta, and G. Gao, "Leveraging Neural City Maps with Vision and Language," Bay Area Robotics Symposium (BARS 2024), Oct. 2024
D. Neamati, M. Partha, S. Gupta, and G. Gao, "Predicting GPS Blockage with Neural City Maps," Stanford Center for AI Safety, Aug. 2024
M. Partha, E. Biju, D. Neamati, S. Gupta, and G. Gao, "Leveraging Neural City Maps with Vision and Language," Stanford Center for AI Safety, Aug. 2024
D. Neamati, M. Partha, S. Gupta, and G. Gao, "Predicting GPS Blockage with Neural City Maps," Stanford AI Laboratories (SAIL) Affiliates Meeting, Apr. 2024
D. Neamati, M. Partha, S. Gupta, and G. Gao, "Predicting GPS Blockage with Neural City Maps," Bay Area Robotics Symposium (BARS 2023), Oct. 2023
D. Neamati, S. Bhamidipati, and G. Gao, "No Signal Is Also a Signal: Improving GPS Positioning in Urban Canyons by Turning Satellite Signal Shadows Cast by Buildings into Useful Environmental Features," Aeronautics and Astronautics Affiliates Meeting, Nov. 2022.
D. Neamati, S. Bhamidipati, and G. Gao, "Set-Based Ambiguity Reduction in Shadow Matching with Iterative GNSS Pseudoranges," Stanford Center for Position, Navigation, and Time Symposium, Oct. 2022

Magazine Article:

D. Neamati, S. Bhamidipati, and G. Gao, "No Signal is also a Signal," Inside GNSS, Mar. 2023

Past Research

(2020-2022) Learned Dynamics for Asteroid Missions

This was the focus of my Senior Thesis. Read more about it here.

Conference Paper:

D. Neamati, Y. K. Nakka, and S. J. Chung, "Learning-based methods to model small body gravity fields for proximity operations: Safety and Robustness," AIAA SCITECH 2022 Forum. January 2022, AIAA 2022-2271.

Thesis:

D. Neamati (2021) New Method and Analysis of Proximity Trajectory-Only Learned Dynamics for Small Body Gravity Fields. Senior thesis (Major), California Institute of Technology. doi:10.7907/4csx-4636. https://resolver.caltech.edu/CaltechTHESIS:05272021-220554457

(2020-2021) Fast Trajectory Optimization

This was the focus of my 2020 summer and fall research. See more here.

Conference Paper:

B. E. Jackson, T. Punnoose, D. Neamati, K. Tracy, R. Jitosho and Z. Manchester, "ALTRO-C: A Fast Solver for Conic Model-Predictive Control," 2021 IEEE International Conference on Robotics and Automation (ICRA), 2021, pp. 7357-7364, DOI: 10.1109/ICRA48506.2021.9561438.

Report and Presentation

D. Neamati, M. Hunt, and Z. Manchester, "Fast and Robust Trajectory Optimization for the Rocket Soft Landing Problem," 2020 Caltech SURF Symposium, 2020.

(2018-2019) Small-Scale Lidar Volume Estimation in Space Environments

This was my research project at NASA JPL.

Conference Papers:

G. Adams, T. Green, A. Brinkman, B. Chamberlain-Simon, D. Neamati, L. Shiraishi, K. Kriechbaum, et al. "CITADEL: An Icy Worlds Simulation Testbed." Earth and Space 2021, pp. 428-443.

Posters:

D. Neamati, A. Brinkman, T. Green, J. Foster, "Investigation of LIDAR Volume Estimation Techniques." JPL Data Science Showcase, 2019.

(2017-2018) Digital Holographic Microscopy

I conducted this research in the Caltech GALCIT department in collaboration with NASA JPL.

Journal Paper:

M. Bedrossian, M. El-Kholy, D. Neamati, & J. Nadeau, (2018). A machine learning algorithm for identifying and tracking bacteria in three dimensions using Digital Holographic Microscopy. AIMS Biophysics, 5(1), 36-49.

(2017) Martian Brines GeoChemistry

A solid combination of planetary science and aerospace engineering.

Conference Paper:

E. Fischer, G. Martinez, D. Neamati, and N. O. Renno, “The Formation of Frost and Liquid Brines on Spacecraft Materials at Mars Environmental Conditions”, AAS/Division of Planetary Sciences Meeting, vol. 49, 2017.

(2016) Hall Thruster Breathing Mode

My very first research experience was in the Plasmadynamics & Electric Propulsion Laboratory at the University of Michigan under Prof. Gallimore. I was not able to publish anything during my short stay, but I certainly learned a lot. Prof. Gallimore's willingness to take me as a high school volunteer research student really set in motion many of the research opportunities listed above.

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