Research Highlights
Funding
(Sep. 2021 - Jun. 2024)
I am very grateful to the National Science Foundation (NSF) for funding my current research via the Graduate Research Fellowship (GRFP). With the NSF GRFP, I get the incredible opportunity to engage in research with significant intellectual merit and broader impacts.
Active Research
(2021-Present) Urban 3D Map-Aided GNSS Localization
This is the core subject of my Ph.D. research. Below is a list of the research that is out there, but there is plenty more on the horizon!
Journal Papers:
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." In Preprint: https://arxiv.org/abs/2404.08854
Conference Papers:
D. Neamati, S. Gupta, M. Partha, and G.Gao, "Neural City Maps for GNSS Shadow Matching," Proceedings of the Institute of Navigation GNSS+ conference (ION GNSS+ 2024), Baltimore, MD. Abstract Accepted
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:
D. Neamati, S. Gupta, M. Partha, and G.Gao, "Predicting GPS Blockage with Neural City Maps," Stanford AI Laboratories Affiliates Meeting, Apr. 2024
D. Neamati, S. Gupta, M. Partha, 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.