UROP Research Mentor Project Submission Portal: Submission #678

serial: '678'
sid: '14006'
uuid: d10ef586-b1e8-4866-a9c9-f5b2ae71cc8b
uri: /urop-research-mentor-project-submission-portal
created: '1720622316'
completed: '1720627076'
changed: '1724638024'
in_draft: '0'
current_page: ''
remote_addr: 69.246.137.249
uid: '0'
langcode: en
webform_id: urop_project_proposal_portal
entity_type: node
entity_id: '1116'
locked: '0'
sticky: '0'
notes: ''
metatag: meta
data:
  roundtable_info: {  }
  approximately_how_many_hours_a_week_would_the_research_assistant: '10'
  are_you_currently_looking_for_students_: 'Yes'
  confirmation_1: '1'
  contact_email_fsu_email: ''
  contact_email_fsu_email2: ''
  contact_email_fsu_email_if_affiliated_: guang.wang@fsu.edu
  faculty_advisor_confirmation: ''
  faculty_advisor_name: ''
  faculty_advisor_s_fsu_email: ''
  fsu_college: 'Arts and Sciences'
  fsu_department_if_applicable_: 'Computer Science'
  headshot_optional_: ''
  if_the_project_location_is_off_campus_does_the_student_need_to_p: ''
  mentoring_philosophy: 'My mentoring goal is to encourage every student to learn something. Based on my previous mentoring experiences, I think all students are talented and my role as a teacher is to guide them to knock on the correct door. To this end, my mentoring philosophy concentrates on the following two principles: (i) inclusiveness and equity to each student, and (ii) encouraging students to ask questions. I treat all students with respect and maintain academic fairness. In addition, I strive to create an equal learning environment and make students feel comfortable and supported. I think students can improve their performance after they know what they do not know, and a very effective way is by asking questions, so I usually encourage students to ask questions.'
  mentor_handbook_and_faqs: '1'
  name_of_other_faculty_collaborator_if_applicable_: ''
  number_of_assistants_needed_faculty_postdoc_max_6_graduate_stude: '2'
  other_faculty_collaborator_s_preferred_pronouns: ''
  overall_research_project_description: |
    Despite billions of dollars of federal investments that promote transportation electrification, the state of Florida is still largely left behind with very low EV penetration and few charging resources. EV usage may be more beneficial for environmental, social, and economic sustainability. A key challenge for large-scale EV adoption is the inaccessibility of public charging infrastructure. Hence, in this project, we propose to develop a data-driven optimization framework for EV charging infrastructure deployment. In doing so, we aim to address multiple complicated technical and real-world challenges by performing the following tasks.
    (i) Understanding the current charging station distribution in Florida.
    (ii) Predicting charging demand in a fine-grained region, e.g., census block or zip code level. 
    (iii) Combining the predicted charging demand with other real-world conditions like population and POI distributions, we plan to design a decision-support tool to help deploy charging infrastructure by balancing different practical factors, such as (a) improving charging infrastructure accessibility and fairness to satisfy charging demand of EVs in different regions, (b) increasing charging resource utilization to improve the profitability of operators, and (c) reducing potential impacts on power grids, etc.
  please_add_any_additional_information_here: ''
  please_provide_a_link_to_your_publications_a_video_clip_or_a_web: www.guangwang.me
  please_select_the_choice_that_most_accurately_describes_your_exp: 'Fully Remote'
  please_select_the_location_of_your_project_: 'On FSU Main Campus'
  position_availability_for_student_research: 'Flexible schedule'
  position_title: Faculty
  primary_research_mentor_name: 'Guang Wang'
  project_keywords: 'Data Science, AI, Electric Vehicle, Smart Cities'
  relevant_student_major_s_: 'Computer Science, Data Science'
  research_mentor_preferred_pronoun2: ''
  research_mentor_pronouns: ''
  research_mentor_supervisor_if_different_from_above_: 'Lin Jiang'
  research_tasks_for_student_research_assistant_s_: 'Students will conduct a comprehensive literature review about electric vehicle (EV) adoption and charging infrastructure deployment. Different datasets including mobility data, charging station data, and US census data will be analyzed. Machine learning models will be built for charging station siting and charging demand prediction.'
  roundtable_times_and_zoom_links: ''
  skills_that_research_assistants_may_need_: |-
    Data collection and analysis skills are required.
    Experience in Python is required.
  title_of_the_project: 'Optimal Deployment of Electric Vehicle Charging Stations Across the State of Florida'
  update_url: 'https://cre.fsu.edu/urop-research-mentor-project-submission-portal?token=qSihCKQABpHNDcMVHSUGKRYZZLa1LmJT5PGlF35wj6k'
  urop_performance_evaluation: '1'
  urop_poster_presentation: '1'
  when_potential_research_assistants_are_reaching_out_via_email_2: ''
  when_potential_research_assistants_are_reaching_out_via_email_wh: ''
  when_students_are_reaching_out_via_email_what_is_your_preferreda: ''
  would_you_like_to_participate_in_the_urop_research_mentor_round2: 'No'
  would_you_like_to_participate_in_the_urop_research_mentor_roundt: ''
  year: '2024'