Project Mentor
Dr. Hanlin Zhou
Department: Geography, Sustainability, Community and Urban Studies
Research Project Overview:
Seasonal rainfall and coastal flooding pose significant threats to the lives and property of Connecticut residents. Beyond the physical risks, recent studies have increasingly examined flood risk perception and related cognitive inequities.
This project focuses on major flood-prone cities in Connecticut, analyzing public perceptions of flood risks based on visual cues from street-view images. Leveraging machine learning techniques, we will develop flood risk perception maps for these areas, offering valuable insights for social assessments of flood management strategies. The SHARE apprentice will assist with data collection and processing. Additionally, they will have the opportunity to learn street-view image processing and geocoding, depending on their interest.
Role of a SHARE Summer Apprentice:
Through this apprenticeship, the student will gain hands-on experience in geospatial data collection, image processing, and spatial data analysis. Additionally, those who are interested and capable will have the opportunity to learn Python-based image processing techniques and explore key concepts in flood risk research. This experience will enhance their analytical skills and provide valuable exposure to interdisciplinary research in geospatial data science and environmental science.
The apprentice will work closely with the faculty member and PhD students in the research group, gaining research collaboration experiences. The apprentice will not only help solve the real-world flood problems in our Connecticut, but will also have the opportunity to present the findings at the undergraduate research symposium. Additionally, the apprentice’s contributions may be included in research publications, further enhancing their research experience and professional development.
Summer Schedule/Time Commitment:
The SHARE apprentice will work approximately 90 hours over the summer, with a flexible schedule to accommodate other commitments such as summer courses or internships. We will begin individual meetings in late May, followed by the main research work starting in June and concluding before mid-August.
The faculty member plan to hold weekly virtual group meetings, lasting 30 minutes to 1 hour, to discuss progress and provide feedback. Outside of these meetings, the apprentice will have flexibility in completing tasks independently. Weekly hours may vary, but we will ensure a steady pace to meet the total hour requirement. Additionally, the apprentice is encouraged to reach out to the faculty mentor and PhD students at any time with questions regarding their tasks.
The faculty member will offer the SHARE apprentice both flexibility and mentorship, providing a supportive research experience. Interested students should be prepared for consistent participation throughout the summer.
Preferred Qualifications:
This apprenticeship is research focused. It is expected that the prospective student has a strong interest in a research career. Preferred qualifications for this apprenticeship include an interest in geospatial analysis, environmental science, or data science. While prior experience with image processing is beneficial, it is not required—students who are eager to learn and engage with new computational techniques are encouraged to apply.
Familiarity with GIS, Python, or data analysis tools is a plus but not mandatory. Strong attention to detail, problem-solving skills, and the ability to work independently while collaborating in a research setting will be valuable for success in this project.
To Apply:
The application opens on Saturday, March 1, 2025. Click here to submit an online application for this research apprenticeship through the Quest Portal. The application deadline is Friday, March 28, 2025, at 11:59pm.
Click here to view an outline of the general application questions. In addition to the general questions, students will be asked to respond to the following questions:
- Do you have any prior experience with flood resilience research or related environmental studies? If so, please describe your involvement and any relevant coursework, projects, or research experiences. (750 words max)
- Do you have experience with image processing? If so, please specify any software, programming languages (e.g., Python, GIS tools), or techniques you have used. If you do not have prior experience, please describe any technical skills you have that may be relevant to this apprenticeship. (750 words max)
Please note:
All students hired for a SHARE Summer apprenticeship must complete a federal I-9 form and present original documents in person to OUR staff as part of the hiring process. Visit this U.S. Citizenship and Immigration Services page for more information about acceptable documents. You cannot begin working until this is complete. Students are encouraged to plan ahead for this. For example, if you are going home for spring break, consider bringing original documents back to campus with you.