Fandel Lin

Fandel Lin is currently pursuing his Ph.D. in Computer Science at University of Southern California (USC), where he is conducting research with Prof. Craig A. Knoblock from Center on Knowledge Graphs in Information Sciences Institute (ISI).

He receives the M.S. degree in Computer and Communication Engineering (CCE) and B.S. degree in Electrical Engineering (EE) at National Cheng Kung University (NCKU), Taiwan, where he had been working with Prof. Hsun-Ping Hsieh from Urban Science and Computing Lab (UCLAB). His research interests lie in geographic information science and data mining, especially map understanding and urban computing. In addition, his researches are recognized by the best paper finalist in ACM SIGSPATIAL'21 and the second place award of ACM Student Research Competition Grand Final in 2018-19.

News.

>> [Oct 2024] We entered the finalist (top 5) for the 13th SIGSPATIAL Cup competition (GISCUP 2024) hold by ORNL and NYU, co-located with ACM SIGSPATIAL conference! The contest targets optimal minimum deployment of electric vehicles charging station network, within the state of Georgia.

>> [Aug 2024] Our work on uncertainty-bounded scheduling (centralized route planning) is accepted at the 32nd ACM International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL'24).

>> [Mar 2024] Our work on cross-region inference (spatial-temporal data mining) is accepted at the 29th International Conference on Database Systems for Advanced Applications (DASFAA'24).

>> [Nov 2023] I served as the best-poster award selection committee member at the 31st ACM International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL'23).

>> [Sep 2023] Our works on polygonal feature extraction (raster map understanding) and indirect resource cooperation (distributed route planning) are both accepted as full papers at the 31st ACM International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL'23).

>> [Apr 2023] Our work on teaching-belief understanding (educational text mining) is accepted at the 24th International Conference on Artificial Intelligence in Education (AIED'23).

>> [Dec 2022] In collaboration with Knowledge Computing Lab (led by Prof. Yao-Yi Chiang) from UMN, we (team 'ISI-UMN') secured the 1st Place for Map Feature Extraction Challenge under AI for Critical Mineral Assessment Competition hold by DARPA, USGS, MITRE, and NASA's JPL. Very proud of the team! (press release from DARPA and ISI)

>> [Jun 2022] I have received 9 domestic awards from various domains for my master thesis.

>> [Jan 2022] I have secured a national scholarship in Taiwan, which is a 4-year fellowship covering full tuition and stipend.

>> [Dec 2021] I was selected as the representative for award recipients of TSC Thesis Award at the Office of the President (press release).

>> [Nov 2021] Our ACM SIGSPATIAL'21 paper - Conntrans is selected as the best paper candidate.

>> [Sep 2021] I am fortunate to have been working with Prof. Hsun-Ping Hsieh since 2017 during my stay at National Cheng Kung University, where most of my research outcomes appertain to the inference-then-planning framework.


  • CV (PDF)
  • Google Scholar
  • dblp

    • Education

    Ph.D. in Computer Science

    Aug 2022 - Present


  • Center on Knowledge Graphs, Advisor: Prof. Craig A. Knoblock
  • University of Southern California, Los Angeles, CA, USA

    • M.S. in Computer and Communication Engineering

    Sep 2019 - Jun 2021


  • Urban Science and Computing Lab (UCLAB), Advisor: Prof. Hsun-Ping Hsieh
  • National Cheng Kung University, Tainan, Taiwan
  • Overall GPA: 4.23/4.3 (27 credits)

    • B.S. in Electrical Engineering

    Sep 2015 - Jun 2019


  • National Cheng Kung University, Tainan, Taiwan
  • Overall GPA: 3.57/4.3 (172 credits)
  • CS-Related GPA: 4.13/4.3 (71 credits)

    • Publication

    Journal Article

    1. Fandel Lin and Hsun-Ping Hsieh. "Exploiting Network Structure in Multi-Criteria Distributed and Competitive Stationary-Resource Searching" ACM Transactions on Spatial Algorithms and Systems (TSAS). 2023.
    2. Fandel Lin and Hsun-Ping Hsieh. "Multicriteria Route Planning for In-Operation Mass Transit under Urban Data" Applied Sciences. 2022.
    3. Fandel Lin and Hsun-Ping Hsieh. "A Grid-Based Two-Stage Parallel Matching Framework for Bi-Objective Euclidean Traveling Salesman Problem" ACM Transactions on Spatial Algorithms and Systems (TSAS). 2022.
    4. Fandel Lin and Hsun-Ping Hsieh. "Traveling Transporter Problem: Arranging New Circular Route in Public Transportation System Based on Heterogeneous Non-Monotonic Urban Data" ACM Transactions on Intelligent Systems and Technology (TIST). 2022.
    5. Hsun-Ping Hsieh, Fandel Lin, Nai-Yu Chen, and Tzu-Hsin Yang. "A Decision Framework to Recommend Cruising Locations for Taxi Drivers under the Constraint of Booking Information" ACM Transactions on Management Information Systems (TMIS). 2022.
    6. Hsun-Ping Hsieh, Fandel Lin, Jiawei Jiang, Tzu-Ying Kuo, and Yu-En Chang. "Inferring Long-Term Demand of Newly Established Stations for Expansion Areas in Bike Sharing System" Applied Sciences. 2021.
    7. Fandel Lin and Hsun-Ping Hsieh. "A Joint Passenger Flow Inference and Path Recommender System for Deploying New Routes and Stations of Mass Transit Transportation" ACM Transactions on Knowledge Discovery from Data (TKDD). 2021.
    8. Hsun-Ping Hsieh and Fandel Lin. "Recommending taxi routes with an advance reservation- a multi-criteria route planner" International Journal of Urban Sciences (RJUS). 2021.
    9. Hsun-Ping Hsieh, Fandel Lin, Cheng-Te Li, Ian En-Hsu Yen, and Hsin-Yu Chen. "Temporal Popularity Prediction of Locations for Geographical Placement of Retail Stores" Knowledge and Information Systems (KAIS). 2019.

    Conference Proceeding

    1. Binh Vu, Craig A. Knoblock, Basel Shbita, and Fandel Lin. "Exploiting Distant Supervision to Learn Semantic Descriptions of Tables with Overlapping Data" International Semantic Web Conference (ISWC'24), Baltimore, MD, 2024. (full paper, 26/111 = 23.4%)
    2. Binh Vu, Craig A. Knoblock, and Fandel Lin. "Results of GRAMS+ at SemTab 2024" Semantic Web Challenge on Tabular Data to Knowledge Graph Matching (SemTab @ ISWC'24), Baltimore, MD, 2024. (oral, short paper, Challenge accuracy track)
    3. Fandel Lin, Craig A. Knoblock, and Binh Vu. "A Hierarchical Voronoi Approach to Deploying New Charging Stations in an Existing Network" ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL'24), Atlanta, GA, 2024. (oral, short paper, GISCUP track)
    4. Fandel Lin, Han Zhang, T. K. Satish Kumar, and Craig A. Knoblock. "An Integrated Approach to Multi-Agent Scheduling with Bounded Objectives" ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL'24), Atlanta, GA, 2024. (short paper, 79/136 = 58.1%)
    5. Fandel Lin and Hsun-Ping Hsieh. "A Hierarchy-Aware Approach to Cross-Region Spatial-Temporal Inference of Unarchived Event in Urban Mobility Infrastructure" International Conference on Database Systems for Advanced Applications (DASFAA'24), Gifu, Japan, 2024. (short paper, 239/971 = 24.6%)
    6. Basel Shbita, Namrata Sharma, Binh Vu, Fandel Lin, and Craig A. Knoblock. "Constructing a Knowledge Graph of Historical Mining Data" International Workshop on Geospatial Linked Data (GeoLD @ ESWC'24), Hersonissos, Greece, 2024. (workshop paper)
    7. Fandel Lin, Craig A. Knoblock, Basel Shbita, Binh Vu, Zekun Li, and Yao-Yi Chiang. "Exploiting Polygon Metadata to Understand Raster Maps - Accurate Polygonal Feature Extraction" ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL'23), Hamburg, Germany, 2023. (full paper, 38/189 = 20.1%)
    8. Fandel Lin and Craig A. Knoblock. "Indirect Cooperation in Distributed Stationary-Resource Searching with Predefined Destinations" ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL'23), Hamburg, Germany, 2023. (full paper, 38/189 = 20.1%)
    9. Fandel Lin, Ding-Ying Guo, and Jer-Yann Lin. "A Machine-Learning Approach to Recognizing Teaching Beliefs in Narrative Stories of Outstanding Professors" International Conference on Artificial Intelligence in Education (AIED'23), Tokyo, Japan, 2023. (oral, short paper, 67/251 = 26.7%)
    10. Fandel Lin and Hsun-Ping Hsieh. "Conntrans: A Two-Stage Concentric Annealing Approach for Multi-Criteria Distributed Competitive Stationary Resource Searching" ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL'21), Beijing, China, 2021. (full paper, 34/152 = 22.4%) (Invited to TSAS Best Papers Special Issue of the ACM SIGSPATIAL 2021)
    11. I-Ying Wu, Fandel Lin, and Hsun-Ping Hsieh. "Dual-Attention Multi-Scale Graph Convolutional Networks for Highway Accident Delay Time Prediction" ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL'21), Beijing, China, 2021. (full paper, 34/152 = 22.4%)
    12. Fandel Lin and Hsun-Ping Hsieh. "A Goal-Prioritized Algorithm for Additional Route Deployment on Existing Mass Transportation System" IEEE International Conference on Data Mining (ICDM'20), Sorrento, Italy, 2020. (oral, short paper, 183/930 = 19.7%)
    13. Jie-Yu Fang, Fandel Lin, and Hsun-Ping Hsieh. "A Multi-Criteria System for Recommending Taxi Routes with an Advance Reservation" European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD'20), Ghent, Belgium, 2020. (full paper, ADS track, 65/236 = 27.5%)
    14. Fandel Lin, Hsun-Ping Hsieh, and Jie-Yu Fang. "A Route-Affecting Region Based Approach for Feature Extraction in Transportation Route Planning" European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD'20), Ghent, Belgium, 2020. (full paper, ADS track, 65/236 = 27.5%)
    15. Fandel Lin, Jie-Yu Fang, and Hsun-Ping Hsieh. "A Gaussian-Prioritized Approach for Deploying Additional Route on Existing Mass Transportation with Neural-Network-Based Passenger Flow Inference" IEEE Congress on Evolutionary Computation (IEEE CEC'20), Glasgow, United Kingdom, 2020. (full paper)
    16. Sheng-Ting Chien, Fandel Lin, Chiunghui Tsai, and Hsun-Ping Hsieh. "An Efficient Method for Recommending Branch Locations to Reduce the Transportation Distance between Stations and Urban Events" IEEE International Workshop on Mobile Data Management, Mining, and Computing on Social Network (MobiSocial @ IEEE MDM'20), Versailles, France, 2020. (workshop paper)
    17. Fandel Lin, Jie-Yu Fang, and Hsun-Ping Hsieh. "Customizing Your Own Route with QQIP. A Quantitative and Qualitative Itinerary Planner for New Transportation Routes" ACM International Conference on World Wide Web (WWW'20), Taipei, Taiwan, 2020. (demo paper)
    18. Fandel Lin, Shiuan-Tyng Lin, Jie-Yu Fang, and Hsun-Ping Hsieh. "Traffic Light Control with Real-Time Vehicle License Plate Recognition" ACM International Conference on World Wide Web (WWW'20), Taipei, Taiwan, 2020. (poster paper)
    19. Fandel Lin and Hsun-Ping Hsieh. "A Convolutional Approach for Estimating Popularity of New Branch Stores" ACM International Conference on World Wide Web (WWW'20), Taipei, Taiwan, 2020. (poster paper)
    20. Fandel Lin and Hsun-Ping Hsieh. "An Intelligent and Interactive Route Planning Maker for Deploying New Transportation Services" ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL'18), Seattle, WA, 2018. (SRC paper)

    Tutorial

    1. Hsun-Ping Hsieh and Fandel Lin. "AI Governance: Advanced Urban Computing on Informatics Forecasting and Route Planning" International Conference on Database Systems for Advanced Applications (DASFAA’21), Taipei, Taiwan. April 2021.

    Thesis

    1. Fandel Lin. "An Inference-then-Planning Framework for Multi-Criteria Competitive and Cooperative Route Planning Built on Heterogeneous Urban Data: A Case Study on Transportation" Master Thesis, National Cheng Kung University, June 2021.

    Award

    International

  • Finalist (Top 5), ACM SIGSPATIAL Cup competition (GISCUP), ACM SIGSPATIAL, 2024.
  • AIED 2023 Conference Scholarship (Conference Grant), AIED, 2023.
  • 1st Place, Map Feature Extraction Challenge, AI for Critical Mineral Assessment Competition, Defense Advanced Research Projects Agency (DARPA), 2022.
  • Best Paper Finalist, ACM SIGSPATIAL, 2021. (one of the 5 best papers)
  • IEEE CIS Conference Grant for Young Professionals and Graduate Students, IEEE CEC, 2020.
  • 2nd Place, ACM Student Research Competition Grand Final, ACM Award Banquet, 2019.
  • 1st Place, ACM SIGSPATIAL Student Research Competition, ACM SIGSPATIAL, 2018.
  • ACM Student Research Competition Travel Award, ACM SIGSPATIAL, 2018.

    • Domestic

  • NSF Travel Grant, ACM SIGSPATIAL, USA, 2024.
  • NSF Travel Grant, ACM SIGSPATIAL, USA, 2023.
  • ITS Paper Award, Intelligent Transportation Society of Taiwan (ITS), Taiwan, 2022.
  • Best Master Thesis Award, Taiwan Geographic Information Society (TGIS), Taiwan, 2022.
  • Best Master Thesis Award, Taiwan Institute of Information and Computing Machinery (IICM), Taiwan, 2022.
  • Pilot Project on Scholarships for Taiwanese Studying in the Focused Fields at Top Foreign University, Ministry of Education, Taiwan, 2022. (4-year fellowship: full tuition + $22,800 USD per year)
  • Best Master Thesis Award, Operations Research Society of Taiwan (ORSTW), Taiwan, 2021.
  • Master Thesis Award (3rd Place), The Chinese Institute of Electrical Engineering (CIEE), Taiwan, 2021.
  • Best Master Thesis Award, IEEE Tainan Section, Taiwan, 2021.
  • Best Master Thesis Award, Taiwan Association for Web Intelligence Consortium (WIC), Taiwan, 2021.
  • Best Master Thesis Award, Taiwanese Association for Artificial Intelligence (TAAI), Taiwan, 2021.
  • ITS Paper Award, Intelligent Transportation Society of Taiwan (ITS), Taiwan, 2021.
  • Best Master Thesis Award, Taiwan Information Storage Association (TISA), Taiwan, 2021.
  • Advanced Paper Award (Best Master Thesis), TSC Thesis Award, Taiwan Management Institute, Taiwan, 2021. (top 4/936, 1st Place in AI-Information Track)
  • Honorary Member of the Phi Tau Phi Scholastic Honor Society, Taiwan, 2021.
  • 2nd Place, Competition of Application for Electronic Toll Collection in Traffic Management, Freeway Bureau, Ministry of Transportation and Communications, Taiwan, 2020.
  • 5th Place, AI CUP Artificial Intelligence Analysis and Classification of Thesis, Ministry of Education, Taiwan, 2019.
  • 2nd Place, Big Data Analytics for Smart Cities, Tainan City Government, Taiwan, 2019.
  • College Student Research Creativity Award, Ministry of Science and Technology, Taiwan, 2019. (top 200/3123 = 6.4%)
  • 6th Place (Top 0.26%), Collegiate Programming Examination, ACM-ICPC Taiwan Council, 2019.
  • Distinguished Honor Award, T-CAT Information Security Contest, Ministry of Science and Technology, Taiwan, 2019. (top 7/248 = 2.8%)
  • Outstanding Engineering Student Fellowship, Chinese Institute of Engineers, Taiwan, 2019. (Award to 10 engineering seniors in Taiwan)
  • 3rd Place, Open Source Software Competition, Ministry of Education, Taiwan, 2018.
  • Silver Medal, Creative Software Applications Contest, Ministry of Education, Taiwan, 2018.
  • Champion, StoryMap Programming Contest, Esri, Taiwan, 2015.
  • Third Prize, Geography Olympiad Research Contest, Taiwan, 2013.

    • University

  • Viterbi School Doctoral Fellowship Top Off, University of Southern California, Los Angeles, CA, USA, 2022-2025.
  • 2nd Place, College of Electrical Engineering and Computer Science (EECS) Research Competition, National Cheng Kung University, Tainan, Taiwan, 2021.
  • 2nd Place, Undergraduate Research Competition, National Cheng Kung University, Tainan, Taiwan, 2019.
  • Best Course Project, Web Programming Course, National Cheng Kung University, Tainan, Taiwan, 2017.

    • Talk

    Conference Tutorial

  • Hsun-Ping Hsieh and Fandel Lin. "AI Governance: Advanced Urban Computing on Informatics Forecasting and Route Planning" International Conference on Database Systems for Advanced Applications (DASFAA’21), Taipei, Taiwan. April 2021.

    • Seminar

  • Fandel Lin. "Application of Spatial Data Mining in Urban Computing" Department of Public Policy and Management, I-Shou University, Kaohsiung, Taiwan. May 2021.
  • Fandel Lin. "Introduction to Data Engineering in Smart City Governance" Department of Public Policy and Management, I-Shou University, Kaohsiung, Taiwan. April 2021.

    • Service

    Technical Program Committee

  • IARIA International Conference on Advances in Satellite and Space Communications (SPACOMM) (2020-2022)

    • Best-Poster Award Selection Committee

  • ACM International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL) (2023)

    • External Reviewer

  • IEEE Transactions on Geoscience and Remote Sensing (2024-present)
  • Transportation Research Part E: Logistics and Transportation Review (2022-2023, 2024-present)
  • Journal of Information Science and Engineering (2023, 2024)
  • Journal of Traffic and Transportation Engineering (English Edition) (2022)
  • IEEE Congress on Evolutionary Computation (2022-2023)

    • Sub-Reviewer

  • ACM Transactions on Data Science (2019-2020)
  • ISWC (2022-2024)
  • ACM WWW (2021), ACM KDD (2020-2022), ACM WSDM (2020)
  • ACM SIGKDD - Urban Computing (2019)

    • Student Volunteer

  • International Conference on Artificial Intelligence in Education (2023)
  • Symposium on the Future of Computing Research (2022)

    • Miscellaneous

    Teaching Experience

  • Teaching Assistant, Application of Big Data Analytics and Data Mining Techniques to Spatial Planning, UP 6772, NCKU (SP20)

    Mar 2020 - Jul 2020

  • Teaching Assistant, Data Engineering for Smart Cities, CCE 5502, NCKU (FA19)

    Sep 2019 - Jan 2020

  • Teaching Assistant, Discrete Mathematics, EE 4600, NCKU (FA18)

    Sep 2018 - Jan 2019

  • Lecturer, Programming Language, Electrical Engineering Summer Camp, NCKU

    Jul 2017


    • Working Experience

  • Research Assistant, USC Information Sciences Institute, Marina del Rey, CA, USA. Advisor: Prof. Craig A. Knoblock

    Aug 2022 - Present

  • Airman, Republic of China Air Force (ROCAF), Taiwan. Mandatory Military Service

    Oct 2021 - Jan 2022

  • Research Assistant, Urban Science and Computing Lab, NCKU, Taiwan. Advisor: Prof. Hsun-Ping Hsieh

    Aug 2017 - Oct 2021


    • Grant and Contract Project

  • Principal Investigator (PI), "Route Planning and Passenger Flow Prediction for Public Transportation Services", Undergraduate Student Research Project of Ministry of Science and Technology (MOST), Taiwan ($1.6k USD)

    Aug 2018 - Feb 2019

  • Collaborator, "AI for Map Geolocation and Extraction to Find Critical Minerals", DARPA Small Business Technology Transfer (STTR) Program, Defense Advanced Research Projects Agency (DARPA), United States. ($469k USD, overall $1.8m USD)

    Sep 2023 - Mar 2025

  • Collaborator, "Extracting Models of Minerals from Knowledge", DARPA Artificial Intelligence Exploration (AIE) Program – Critical Mineral Assessments with AI Support, Defense Advanced Research Projects Agency (DARPA), United States. ($1m USD)

    Aug 2023 - Jan 2025

  • Collaborator (Unfunded), "The Application of Natural Language Processing in the Identification of the Teaching Ideas of Professors: Taking the Stories of Outstanding Teachers in National Taiwan University as Examples", Ministry of Science and Technology (MOST), Taiwan ($15k USD)

    Jan 2022 - Feb 2023

  • Project Main Executor, "An Intelligent and Interactive and Transportation Deploying Assistant for Constructing New Routes and Stations", The Pilot Directions for the Einstein Program, Ministry of Science and Technology (MOST), Taiwan ($165k USD)

    Jan 2020 - Oct 2021

  • Project Main Executor, "An Innovative Location-Based Recommender System for Urban Construction", Ministry of Science and Technology (MOST), Taiwan ($35k USD)

    Aug 2019 - Jan 2020

  • Project Main Executor, "A Machine Hunter for Spotting Hazardous Air Polluted Locations from Urban Big Data", Ministry of Science and Technology (MOST), Taiwan ($33k USD)

    Aug 2017 - Jul 2018


    • Skill

  • Programming: Java/JSP, C/C++, SQL, Python, PHP, JavaScript, RDF/OWL, SPARQL.
  • Tool: QGIS, ArcGIS, LaTeX.
  • Language: Chinese (native), English (TOEFL 105/120), Japanese (JLPT N2 certificated), and Taiwanese Minnan.