We look for talented individuals in photogrammetry, 3D computer vision, machine/deep learning to fill Ph.D., postdoc, and research/software engineers positions, fully funded. There is no set deadline, we always have the capacity to work with talents. (I sometimes post specifically immediately needed positions through my LinkedIn, you can check my post as well)
Topics of interest (consistently updated):
- Structure from motion / photogrammetry / Multi-view geometry for 3D mensuration, workflow optimization and its use by citizen scientists
- Novel scene representation, e.g., NeRF, Gaussian Splatting, for large-scale aerial datasets for outdoor scene
- Computer Graphics: scene modeling, decomposition, mesh operation, polyhedral model reconstruction.
- Generative models in scene modeling and remote sensing images.
- Domain Adaptation for generalized remote sensing semantic segmentation, instance segmentation
- Interdisciplinary applications using various remote sensing image image/data sources
- specific sibling topics of the above.
We are interested in candidates with solid basics in mathematics/statistics and computer programming, preferably with a background in Geomatics, remote sensing and computer vision / machine vision. For programming language: we know that most started with Python since it is such a popular language with nice ecosystems, but we would like students to have good coding skills in C/C++ to handle system with optimized algorithm performance, or at least (for students), be prepared to learn it well during your graduate training phase. Sometimes, we offer exchange opportunities with collaborating institutes such as the German Aerospace Center, SRI-international or other institutes. Overall, We offer a great deal with training opportunities for young researchers to grow and eventually become industrial and academic leaders in the field. Interested? Drop an email to 
.
Funding mechanism and work fashion:
- Students:We will provide GRA (Graduate Research Associate) for students working on projects, most of them related to topics mentioned above (one or multiple). Sometimes I would also encourage students to apply for GTA (Graduate Teaching Associate) to gain some teaching experiences. Students in their first year or so will mostly take courses, and work with senior graduate students, get exposed to projects under various topics, in preparation to be more independent in their senior years. This will provide the students with growing experiences not only in their domain knowledge, but soft skills like advising junior students and preparing tasks. Students will also be encouraged to give talks and understand how to present ideas and works effectively.
- Postdoc/Research Staff: We will provide project-based funding, salaries are competitive. You will help the PI to manage students, research projects, delivery project products, and of course, publish whenever you can. We will work closely as a team and you will learn from the process and transition to a leader when opportunity allows. We strive to keep long-term talent. For foreigners, we have the capability to apply for working visa (e.g. H1B).
To Prospective Students: For general questions related to the application procedure, please visit the relevant web pages as shown below:
Graduate School: https://gpadmissions.osu.edu/grad/admissions.html
CEGE: https://ceg.osu.edu/general-information-how-apply
ECE: https://ece.osu.edu/futurestudents/graduate/application
ESGP: https://esgp.osu.edu/prospective-students/admissions
Please understand that due to the large number of emails I receive, I may not be able to reply to every potential applicant, while if you appear to be a qualified student with matching interests, I will contact you for further discussions. To make the communication more effective, the following are suggested when you initiate the contact: 1) Attach your CV outlining your major experiences that are closely related to our research interest; 2) Try to describe what you are interested in a specific way rather than “I am interested in remote sensing or your research”: mentioning one of our papers/projects would be ideal, and talk about what you want to do, proposing something new is also encouraged. 3) If any, demonstrate your practical experiences of programming in computer vision, photogrammetry and remote sensing.
Geomatics / Photogrammetry / Remote Sensing / Machine learning:
You will be enrolled in the Geoinformation graduate program in the Department of CEGE, or you may also be considered in the Environmental Science Graduate Program (ESGP) for studying environment-related remote sensing problems. You will be working on various image interpretation problems using information included but not limited to multi-resolution, multi-temporal, multi-spectral/hyper-spectral/LiDAR/DSM/thermal data. Specific topics will be given on particular applications related to natural and built environment. Examples are large scale monitoring of glacier movement, ecological monitoring, land-cover classification, earthquake assessment. UAV remote sensing with application to precision agriculture, crop monitoring and object detection.
In our photogrammetry research, surveying oriented photogrammetry theory and concept will be examined and applied to various precision engineering problem (aerial/satellite and close-range), geometric correction, device calibration, multi-sensory data alignment and precision deformation monitoring. Interested research direction includes planetary and satellite photogrammetry. Another interested branch is 3D city modeling, where you are expected to collaborate with team members in computer vision, to work on precise 3D polygonal model generation and attributation, serving for GIS data generation/update and analysis.
Computer Vision :
You will be enrolled in the Computer Vision and Image Processing research area in the Department of ECE. In our group, you are expected to develop innovative algorithms related to 3D vision and scene understanding, with a major focus on processing various types of top-view images such as satellite, UAV, airborne data. You will learn to understand how 3D vision could be used for precise measurements. We mostly target our work on applied Computer Vision that aims to solve real-world problems and produce prototypes software for tech demonstrations. You are also expected to work on machine learning, pattern recognition problems related to image/video/LiDAR-based target detection, as well as vision-based navigation techniques as project needs.