About Myself

My name is Gengchen Mai (买庚辰). I am currently a Tenure-Track Assistant Professor at the Department of Geography, University of Georgia, and an Affiliated Professor and Graduate Program Faculty of the Department of Computer Science, School of Computing, UGA and the UGA Institute for Artificial Intelligence. I am also a member of the UGA Environmental Artificial Intelligence Faculty Cluster, and the Institute for Integrative Precision Agriculture (IIPA), UGA. I am currently the director of Spatially Explicit Artificial Intelligence (SEAI) Lab at UGA. Before I came to UGA, I was a Postdoctoral scholar at Stanford Artificial Intelligence Laboratory (SAIL), Department of Computer Science, Stanford University. I work with Prof. Stefano Ermon on developing spatially-explicit machine learning models for different geospatial tasks.

I got my Ph.D. in Cartography and Geographic Information Science from Department of Geography, University of California, Santa Barbara. I was a graduate student research at both Space and Time for Knowledge Organization (STKO) Lab and UCSB Spatial Center. My Ph.D. adviser is Prof. Krzysztof Janowicz. I am interested in Machine Learning/Deep Learning, Geographical Information Science (GIScience), Geographic Question Answering, NLP, Geographic Information Retrieval, Knowledge Graph, and Semantic Web. Right now, my research is highly focused on Geographic Question Answering and Spatially-Explicit Machine Learninig models. I have completed five AI/ML research based internships at Esri Inc., SayMosaic Inc., Apple Map, and Google X.

Before I become a MA/Ph.D. Student at UCSB, I got my B.S. Degree in Geographic Information System from Department of Geographical Information Science, School of Resource and Environmental Sciences, Wuhan University. During my undergraduate study, my research topic, especially undergraduate thesis, is focused on Land Use/Cover Change (LUCC), spatial analysis and spatial statistics.

Dr. Mai is looking for 1-2 M.A./Ph.D. student for Fall 2024. For students interested in joining Dr. Mai's team, please send your resume to gengchen.mai25 AT uga.edu. See more here

Research Interests

  • Spatially Explicit Artificial Intelligence & GeoAI
  • Geo-Foundation Models
  • Geographic Question Answering
  • Deep Learning on Remote Sensing
  • Urban Data Science
  • Computational Sustainability
  • GeoEthics and AI Ethics
  • Knowledge Graph
  • Nature Language Processing
  • Geographic Information Retrieval
  • Machine Learning/Deep Learning
  • GIScience
  • Spatial Data Mining
  • Spatial Statistic/Analysis

Contact

Gengchen Mai

Address:

Room 312, Geography and Geology Building, 210 Field St

Department of Geography

University of Georgia

Athens, Georgia 30602, USA

See Also:

News

2023/04/26My 1st author paper got accepted to ICML 2023. See our paper Here!

2023/03/26I received * AAG 2023 J. Warren Nystrom Award (1 award recipient every year)!

2022/08/24I am looking for fully-funded graduate student to work with me at UGA Geography. See more here.

2022/07/20I was selected as one of the Top 10 WGDC 2022 Global Young Scientist Award by Taibo.

2022/06/15I will be co-organize both GeoAI 2022 and GeoKG 2022 workshop at ACM SIGSPATIAL 2022!

2022/02/26I received AAG 2022 William L. Garrison Award for Best Dissertation in Computational Geography!

2021/08/09I started a new Postdoc at Stanford AI Lab, check out my Stanford Profiles here!

2021/07/23We have extended our GeoKG & GeoAI 2021 workshop into a Transactions in GIS special issue! Please consider submit your work here!

2021/07/13We are organizing a GeoKG & GeoAI workshop in GIScience 2021!

2021/06/14I defensed my PhD on 06/14/2021!

2020/03/31Our new ICLR 2020 paper is selected one of the Best Deep Learning Papers by neptune.ai!

Education

Master of Art

Time:

09/24/2015 – 11/31/2017

Institution:

UC Santa Barbara, Santa Barbara, CA, USA 93106

Lab:

STKO Lab

Major:

Cartography and Geographic Information Science

Bachelor of Science

Time:

09/04/2011 – 06/30/2015

Institution:

Wuhan University, Wuhan, Hubei, China 430079

Department:

Department of Geographical Information Science

Major:

Geographic Information System

Adviser:

Prof. Shiliang Su

Thesis:

Tea Plantation Expansion in Southeast of China: Process, Driving Forces and Ecological Effect


Internship

Internship Position:

AI Resident

Time:

10/2020 - 12/2020

Company:

Google X

Team:

Core AI Team

Mentor:

Dr. Hongxu Ma (Tech Lead)

Location:

Mountain View, CA, USA

Internship Position:

AI Resident

Time:

06/22/2020 - 09/11/2020

Company:

Google X

Team:

Core AI Team

Mentor:

Dr. Hongxu Ma (Tech Lead)

Location:

Mountain View, CA, USA

Topic:

Time Series Forecasting, Causal Discovery/Inference

Internship Position:

Cartographic Engineer Intern (Machine Learning)

Time:

06/17/2019 - 09/06/2019

Company:

Apple Inc.

Team:

Apple Map Cartographic Team

Mentor:

Nick Martinelli

Location:

Cupertino, CA, USA

Topic:

Graph Neural Network, Map Generalization

Internship Position:

Machine Learning & NLP Research Intern

Time:

06/18/2018 - 09/21/2018

Company:

SayMosaic Inc.

Location:

Palo Alto, CA, USA

Topic:

Deep Reinforcement Learning, Sequence Model, Q&A, IR, NLP

Internship Position:

Software Development Internship

Time:

06/27/2017 - 09/15/2017

Mentor:

Sathya Prasad

Location:

Redlands, CA, USA

Used Technology:

Elasticsearch, Mechine Learning/Natural Language Processing (Artificial Neural Network, Named Entity Recognition), QML


Publication

Book chapters:

4.Gengchen Mai, Ziyuan Li, Ni Lao. Spatial Representation Learning in GeoAI. In Song Gao, Yingjie Hu, Wenwen Li, et al.(Eds): Handbook of Geospatial Artificial Intelligence (GeoAI), 2023, CRC Press.

3.Song Gao, Mingxiao Li, Jinmeng Rao, Gengchen Mai, Timothy Prestby, Joseph Marks, Yingjie Hu. Automatic Urban Road Map Generation from Massive GPS Trajectories of Taxis. In Martin Werner, Yao-Yi Chiang et al.(Eds): Handbook of Big Geospatial Data, 2021, Springer. [code]

2.Bo Yan, Gengchen Mai, Yingjie Hu, Krzysztof Janowicz. Harnessing Heterogeneous Big Geospatial Data. In Martin Werner, Yao-Yi Chiang et al.(Eds): Handbook of Big Geospatial Data, 2021, Springer.

1.Song Gao, Gengchen Mai. Mobile GIS and Location-Based Services. In Bo Huang, Thomas J. Cova, and Ming-Hsiang Tsou et al.(Eds): Comprehensive Geographic Information Systems, 2017, Elsevier. Oxford, UK..

Preprint:

11.Gengchen Mai, Ni Lao, Weiwei Sun, Yuchi Ma, Jiaming Song, Chenlin Meng, Hongxu Ma, Jinmeng Rao, Ziyuan Li, Stefano Ermon. SSIF: Learning Continuous Image Representation for Spatial-Spectral Super-Resolution. arXiv preprint arXiv:2310.00413.

10.Fei Dou, Jin Ye, Geng Yuan, Qin Lu, Wei Niu, Haijian Sun, Le Guan, Guoyu Lu, Gengchen Mai, Ninghao Liu, Jin Lu, Zhengliang Liu, Zihao Wu, Chenjiao Tan, Shaochen Xu, Xianqiao Wang, Guoming Li, Lilong Chai, Sheng Li, Jin Sun, Hongyue Sun, Yunli Shao, Changying Li, Tianming Liu, Wenzhan Song. Towards Artificial General Intelligence (AGI) in the Internet of Things (IoT): Opportunities and Challenges. arXiv preprint arXiv:2309.07438.

9.Saed Rezayi, Zhengliang Liu, Zihao Wu, Chandra Dhakal, Bao Ge, Haixing Dai, Gengchen Mai, Ninghao Liu, Chen Zhen, Tianming Liu, Sheng Li. Exploring New Frontiers in Agricultural NLP: Investigating the Potential of Large Language Models for Food Applications. arXiv preprint arXiv:2306.11892.

8.Haixing Dai, Yiwei Li, Zhengliang Liu, Lin Zhao, Zihao Wu, Suhang Song, Ye Shen, Dajiang Zhu, Xiang Li, Sheng Li, Xiaobai Yao, Lu Shi, Quanzheng Li, Zhuo Chen, Donglan Zhang, Gengchen Mai*, Tianming Liu*. AD-AutoGPT: An Autonomous GPT for Alzheimer's Disease Infodemiology. arXiv preprint arXiv:2306.10095. *Corresponding author

7.Yucheng Shi, Hehuan Ma, Wenliang Zhong, Gengchen Mai, Xiang Li, Tianming Liu, Junzhou Huang. ChatGraph: Interpretable Text Classification by Converting ChatGPT Knowledge to Graphs. arXiv preprint arXiv:2305.03513.

6.Ehsan Latif*, Gengchen Mai*, Matthew Nyaaba*, Xuansheng Wu, Ninghao Liu, Guoyu Lu, Sheng Li, Tianming Liu, Xiaoming Zhai. Artificial General Intelligence (AGI) for Education. arXiv preprint arXiv:2304.12479. *Equal contribution

5.Jielu Zhang, Zhongliang Zhou, Gengchen Mai, Lan Mu, Mengxuan Hu, Sheng Li. Text2Seg: Remote Sensing Image Semantic Segmentation via Text-Guided Visual Foundation Models. arXiv preprint arXiv:2304.10597.

4.Gengchen Mai,Weiming Huang, Jin Sun, Suhang Song, Deepak Mishra, Ninghao Liu, Song Gao, Tianming Liu, Gao Cong, Yingjie Hu, Chris Cundy, Ziyuan Li, Rui Zhu, Ni Lao. On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligence. arXiv preprint arXiv:2304.06798.

3.Guoyu Lu, Sheng Li, Gengchen Mai, Jin Sun, Dajiang Zhu, Lilong Chai, Haijian Sun, Xianqiao Wang, Haixing Dai, Ninghao Liu, Rui Xu, Daniel Petti, Changying Li, Tianming Liu, Changying Li. AGI for Agriculture. arXiv preprint arXiv:2304.06136.

2.Gengchen Mai, Yao Xuan, Wenyun Zuo, Krzysztof Janowicz, Ni Lao. Sphere2Vec: Multi-Scale Representation Learning over a Spherical Surface for Geospatial Predictions. arXiv preprint arXiv:2201.10489.

1.Ling Cai, Krzysztof Janowicz, Bo Yan, Gengchen Mai. Learning Time and Type Aware Representations for Urban Zones. SSRN.

Peer-Reviewed Major Publications:

2024

57.JAG 2024 Danhuai Guo, Yingxue Yu, Shiyin Ge, Song Gao, Gengchen Mai, Huixuan Chen. SpatialScene2Vec: A Self-Supervised Contrastive Representation Learning Method for Spatial Scene Similarity Evaluation.. International Journal of Applied Earth Observation and Geoinformation.

56.ICLR 2024 Rohin Manvi, Samar Khanna, Gengchen Mai, Marshall Burke, David B. Lobell, Stefano Ermon. GeoLLM: Extracting Geospatial Knowledge from Large Language Models, In: Proceedings of the Twelfth International Conference on Learning Representations (ICLR 2024), May 7 - 11, 2024, Vienna, Austria. [OpenReview] [ArXiv] * Top Machine Learning Conference

2023

55.IJGIS 2023 Yingjie Hu*, Gengchen Mai*, Chris Cundy, Kristy Choi, Ni Lao, Wei Liu, Gaurish Lakhanpal, Ryan Zhou, Kenneth Joseph. Fusing geo-knowledge and GPT-3 for extracting location descriptions from disaster-related social media messages.. International Journal of Geographical Information Science. [DOI] * Co-first author

54.IJUS 2023 Jiaxin Du, Xinyue Ye, Piotr Jankowski, Tom Sanchez, Gengchen Mai. Artificial Intelligence Enabled Participatory Planning: A Review.. International Journal of Urban Sciences. [DOI]

53.SIGSPATIAL 2023 Hao Li, Jiapan Wang, Johann Maximilian Zollner, Gengchen Mai, Ni Lao and Martin Werner. Rethink Geographical Generalizability with Unsupervised Self-Attention Model Assemble: A Case Study of OpenStreetMap Missing Building Detection in Africa, In: Proceedings of ACM SIGSPATIAL 2023, Nov 13 - 16, 2023, Hamburg, Germany. [ResearchGate] * Acceptance Rate 20.1%

52.SIGSPATIAL 2023 Jinmeng Rao, Song Gao, Gengchen Mai and Krzysztof Janowicz. Building Privacy-Preserving and Secure Geospatial Artificial Intelligence Foundation Models (Vision Paper), In: Proceedings of ACM SIGSPATIAL 2023, Nov 13 - 16, 2023, Hamburg, Germany. [Vision Paper] [ArXiv] * Acceptance Rate 46.7%

51.SIGSPATIAL 2023 Yiqun Xie, Zhaonan Wang, Gengchen Mai, Yanhua Li, Xiaowei Jia, Song Gao and Shaowen Wang. "Geo"-AI Foundation Models: Reality, Gaps and Opportunities (Vision Paper), In: Proceedings of ACM SIGSPATIAL 2023, Nov 13 - 16, 2023, Hamburg, Germany. [Vision Paper] * Acceptance Rate 46.7%

50.ISPRS PHOTO 2023 Gengchen Mai, Yao Xuan, Wenyun Zuo, Yutong He, Jiaming Song, Stefano Ermon, Krzysztof Janowicz, Ni Lao. Sphere2Vec: A General-Purpose Location Representation Learning over a Spherical Surface for Large-Scale Geospatial Predictions.. ISPRS Journal of Photogrammetry and Remote Sensing, 202 (2023): 439-462. [DOI] [Website] [Code] [ArXiv] [ResearchGate]

49.ICML 2023 Gengchen Mai, Ni Lao, Yutong He, Jiaming Song, Stefano Ermon. CSP: Self-Supervised Contrastive Spatial Pre-Training for Geospatial-Visual Representations, In: Proceedings of the Fortieth International Conference on Machine Learning (ICML 2023), Jul 23 - 29, 2023, Honolulu, Hawaii, USA. [Website] [Code] [ArXiv] [Presentation] * Top 1 Machine Learning Conference

48.GEOI 2023 Gengchen Mai, Chiyu Max Jiang, Weiwei Sun, Rui Zhu, Yao Xuan, Ling Cai, Krzysztof Janowicz, Stefano Ermon, Ni Lao. Towards General-Purpose Representation Learning of Polygonal Geometries. GeoInformatica, 27(2), (2023): 289-340. DOI:10.1007/s10707-022-00481-2 [arxiv paper] * AAG 2023 J. Warren Nystrom Award (1 award recipient every year)

47.TGIS 2023 Yanlin Qi, Gengchen Mai*, Rui Zhu, Micheal Zhang. EVKG: An Interlinked and Interoperable Electric Vehicle Knowledge Graph for Smart Transportation System. Transactions in GIS, 27, no. 4 (2023): 949-974. [DOI] [arxiv paper] *Corresponding author

46.ISPRS PHOTO 2023 Weiming Huang, Daokun Zhang, Gengchen Mai, Xu Guo, Lizhen Cui. Learning region representations with POIs and hierarchical graph infomax. The ISPRS Journal of Photogrammetry and Remote Sensing, 196 (2023): 134-145.

45.AGILE 2023 Meilin Shi, Kitty Currier, Zilong Liu, Krzysztof Janowicz, Nina Wiedemann, Judith Verstegen, Grant McKenzie, Anita Graser, Rui Zhu, and Gengchen Mai. Thinking Geographically about AI Sustainability, In: Proceedings of AGILE 2023.

44.FOIS 2023 Cogan Shimizu, Shirly Stephen, Rui Zhu, Kitty Currier, Mark Schildhauer, Dean Rehberger, Pascal Hitzler, Krzysztof Janowicz, Colby K. Fisher, Mohammad Saeid Mahdavinejad, Antrea Christou, Adrita Barua, Abhilekha Dalal, Sanaz Saki Norouzi, Zilong Liu, Meilin Shi, Ling Cai, Gengchen Mai, Zhangyu Wang, and Yuanyuan Tian. The KnowWhereGraph Ontology: A Showcase. In the 13th International Conference on Formal Ontology in Information Systems (FOIS 2023), July 17-20, 2023, Sherbrooke, Québec, Canada.

43.FOIS 2023 Shirly Stephen, Kitty Currier, Mark Schildhauer, Ling Cai, Yuanyuan Tian, Cogan Shimizu, Kryzstof Janowicz, Pascal Hitzler, Anna Lopez-Carr, Andrew Schroeder, Rui Zhu, Dean Rehberger, Gengchen Mai, Zilong Liu, and Colby Fisher. Expertise Ontology: Modeling Expertise in the Context of Emergency Management. In the 13th International Conference on Formal Ontology in Information Systems (FOIS 2023), July 17-20, 2023, Sherbrooke, Québec, Canada.

2022

42.TGIS 2022 Gengchen Mai, Yingjie Hu, Song Gao, Ling Cai, Bruno Martins, Johannes Scholz, Jing Gao, and Krzysztof Janowicz. Symbolic and Subsymbolic GeoAI: Geospatial Knowledge Graphs and Spatially Explicit Machine Learning. Transactions in GIS [Editorial], 26, no. 8 (2022): 3118-3124.

41.GEOI 2022 Ling Cai, Krzysztof Janowicz, Rui Zhu, Zhangyu Wang, Gengchen Mai. HyperQuaternionE: A Hyperbolic Embedding Model for Qualitative Spatial and Temporal Reasoning. GeoInformatica, (2022): 1-39. DOI:10.1007/s10707-022-00469-y.

40.IJGIS 2022 Rui Zhu, Krzysztof Janowicz, Ling Cai, Gengchen Mai. Reasoning over Higher-order Qualitative Spatial Relations via Spatially Explicit Neural Networks. International Journal of Geographical Information Science, 36, no. 11 (2022): 2194-2225.

39.IJGIS 2022 Gengchen Mai, Krzysztof Janowicz, Yingjie Hu, Song Gao, Bo Yan, Rui Zhu, Ling Cai, Ni Lao. A Review of Location Encoding for GeoAI: Methods and Applications. International Journal of Geographical Information Science, 36, no. 4 (2022): 639-673. DOI:10.1080/13658816.2021.2004602 [arxiv paper]

38.JGSA 2022 Gengchen Mai, Weiming Huang, Ling Cai, Rui Zhu, Ni Lao. Narrative Cartography with Knowledge Graphs. Journal of Geovisualization and Spatial Analysis, 6, no. 1 (2022): 4. DOI:10.1007/s41651-021-00097-4. [arxiv paper]

37.SWJ 2022 Krzysztof Janowicz, Cogan Shimizu, Pascal Hitzler, Gengchen Mai, Shirly Stephen, Rui Zhu, Ling Cai, Lu Zhou, Mark Schildhauer, Zilong Liu, Zhangyu Wang, Meilin Shi. Diverse Data! Diverse Schemata?. Semantic Web Journal, 13, no. 1 (2022): 1-3.

36.AIMag 2022 Krzysztof Janowicz, Pascal Hitzler, Wenwen Li, Dean Rehberger, Mark Schildhauer, Rui Zhu, Cogan Shimizu, Colby Fisher, Ling Cai, Gengchen Mai, Joseph Zalewski, Lu Zhou, Shirly Stephens, Seila Gonzalez, AnnaLopez Carr, Andrew Schroeder, Dave Smith, Dawn Wright, Sizhe Wang, Yuanyuan Tian, Zilong Liu. Know, Know Where, KnowWhereGraph: A Densely Connected, Cross-Domain Knowledge Graph and Geo-Enrichment Service Stack for Applications in Environmental Intelligence. AI Magazine, 43, no. 1 (2022): 30-39. DOI:10.1002/aaai.12043.

35.SIGSPATIAL 2022 Gengchen Mai, Chris Cundy, Kristy Choi, Yingjie Hu, Ni Lao, Stefano Ermon. Towards a Foundation Model for Geospatial Artificial Intelligence, In: Proceedings of ACM SIGSPATIAL 2022. [Vision Paper] * Acceptance Rate 22.2%

34.SIGSPATIAL 2022 Amna Elmustafa, Erik Rozi, Yutong He, Gengchen Mai, Stefano Ermon, David Lobel and Marshall Burke. Understanding Economic Development in Rural Africa using Satellite Imagery, Building footprints and Deep Models, In: Proceedings of ACM SIGSPATIAL 2022. [Short Paper] * Acceptance Rate 46.3%

33.AGILE 2022 Rui Zhu, Krzysztof Janowicz, Gengchen Mai, Ling Cai and Meilin Shi. COVID-Forecast-Graph: An Open Knowledge Graph for Consolidating COVID-19 Forecasts and Economic Indicators via Place and Time, In: Proceedings of AGILE 2022.

32.AGILE 2022 Zilong Liu, Krzysztof Janowicz, Ling Cai, Rui Zhu, Gengchen Mai and Meilin Shi. Geoparsing: Solved or Biased? An Evaluation of Geographic Biases in Geoparsing, In: Proceedings of AGILE 2022.

31.ESWC 2022 Zilong Liu, Meilin Shi, Krzysztof Janowicz, Stephanie Delbecque, Gengchen Mai, Rui Zhu and Pascal Hitzler. LD Connect: A Linked Data Portal for IOS Press Scientometrics, In: Proceedings of ESWC 2022.

2021

30.IJCKG 2021 Rui Zhu, Cogan Shimizu, Shirly Stephen, Lu Zhou, Ling Cai, Gengchen Mai, Krzysztof Janowicz, Mark Schildhauer, Pascal Hitzler. SOSA-SHACL: Shapes Constraint for the Sensor, Observation, Sample, and Actuator Ontology, In: Proceedings of IJCKG 2021.

29.IJCKG 2021 Cogan Shimizu, Rui Zhu, Gengchen Mai, Mark Schildhauer, Krzysztof Janowicz, and Pascal Hitzler. A Pattern for Features on a Hierarchical Spatial Grid, In: Proceedings of IJGKG 2021.

28.ACM K-CAP 2021 Ling Cai, Krzysztof Janowicz, Bo Yan, Rui Zhu, Gengchen Mai. Time in a Box: Advancing Knowledge Graph Completion with Temporal Scopes, In: Proceedings of ACM K-CAP 2021, Dec. 02 - 03, 2021, Virtual Conference. [arxiv paper] * Best Student Paper

27.K-CAP 2021 Rui Zhu, Ling Cai, Gengchen Mai, Cogan Shimizu, Colby K. Fisher, Krzysztof Janowicz, Anna Lopez-Carr, Andrew Schroeder, Mark Schildhauer, Yuanyuan Tian, Shirly Stephen, Zilong Liu. Providing Humanitarian Relief Support through Knowledge Graphs, In: Proceedings of ACM K-CAP 2021, Dec. 02 - 03, 2021, Virtual Conference.

26.AGILE 2021 Gengchen Mai, Krzysztof Janowicz, Rui Zhu, Ling Cai and Ni Lao. Geographic Question Answering: Challenges, Uniqueness, Classification, and Future Directions, In: Proceedings of AGILE 2021, Jun. 08 - 11, 2021, Virtual Conference. [DOI] [arxiv paper]

25.AGILE 2021 Meilin Shi, Krzysztof Janowicz, Ling Cai, Gengchen Mai, Rui Zhu. A Socially Aware Huff Model for Destination Choice in Nature-based Tourism, In: Proceedings of AGILE 2021, Jun. 08 - 11, 2021, Virtual Conference. [DOI] * Best Full Paper Nominatee

2020

24.TGIS 2020 Gengchen Mai, Krzysztof Janowicz, Ling Cai, Rui Zhu, Blake Regalia, Bo Yan, Meilin Shi, Ni Lao. SE-KGE: A Location-Aware Knowledge Graph Embedding Model for Geographic Question Answering and Spatial Semantic Lifting. Transactions in GIS, 24.3 (2020): 623-655. DOI:10.1111/tgis.12629 [arxiv paper] [code] [video] [slides] * Top Cited Papers in TGIS 2020-2021

23.TGIS 2020 Ling Cai, Krzysztof Janowicz, Gengchen Mai, Bo Yan, Rui Zhu. Traffic Transformer: Capturing the Continuity and Periodicity of Time Series for Traffic Forecasting. Transactions in GIS, 24.3 (2020): 736-755. DOI:10.1111/tgis.12644 * Top Cited Papers in TGIS 2020-2021

22.ICLR 2020 Gengchen Mai, Krzysztof Janowicz, Bo Yan, Rui Zhu, Ling Cai, Ni Lao. Multi-Scale Representation Learning for Spatial Feature Distributions using Grid Cells, In: Proceedings of ICLR 2020, Apr. 26 - 30, 2020, Addis Ababa, ETHIOPIA . [OpenReview paper] [arxiv paper] [code] [video] [slides] * Spotlight Paper (Acceptance Rate 6%, 156 out of 2594 submissions)

21.AGILE 2020 Gengchen Mai, Krzysztof Janowicz, Sathya Prasad, Meilin Shi, Ling Cai, Rui Zhu, Blake Regalia, Ni Lao. Semantically-Enriched Search Engine for Geoportals: A Case Study with ArcGIS Online, In: Proceedings of AGILE 2020, , Jun. 16 - 19, 2020, Chania, Crete, Greece. [DOI] [arxiv paper] [code]

2019

20.TGIS 2019 Gengchen Mai, Krzysztof Janowicz, Bo Yan, Simon Scheider. Deeply Integrating Linked Data with Geographic Information Systems. Transactions in GIS, 23(2019), 579-600. DOI:10.1111/tgis.12538 [code] [demo video]

19.TGIS 2019 Bo Yan, Krzysztof Janowicz, Gengchen Mai, Rui Zhu. A Spatially-Explicit Reinforcement Learning Model for Geographic Knowledge Graph Summarization. Transactions in GIS, 23(2019), 620-640. DOI:10.1111/tgis.12547

18.TGIS 2019 Rui Zhu, Krzysztof Janowicz, Gengchen Mai. Making Direction a First-Class Citizen of Tobler's First Law of Geography. Transactions in GIS, 23(2019), 398-416. DOI:10.1111/tgis.12550

17.K-CAP 2019 Gengchen Mai, Krzysztof Janowicz, Bo Yan, Rui Zhu, Ling Cai, Ni Lao. Contextual Graph Attention for Answering Logical Queries over Incomplete Knowledge Graphs, In: Proceedings of ACM K-CAP 2019, Nov. 19 - 21, 2019, Marina del Rey, CA, USA. [arxiv]

16.K-CAP 2019 Ling Cai, Bo Yan, Gengchen Mai, Krzysztof Janowicz, Rui Zhu. TransGCN: A Translation-Based Graph Convolutional Network Model for Link Prediction, In: Proceedings of ACM K-CAP 2019, Nov. 19 - 21, 2019, Marina del Rey, CA, USA. [arxiv] * 1st Best Full Paper Award

15.AGILE 2019 Gengchen Mai, Bo Yan, Krzysztof Janowicz, Rui Zhu. Relaxing Unanswerable Geographic Questions Using A Spatially Explicit Knowledge Graph Embedding Model, In: Proceedings of AGILE 2019, June 17 - 20, 2019, Limassol, Cyprus. * 1st Best Full Paper Award

2018

14.SWJ 2018 Krzysztof Janowicz, Pascal Hitzler, Blake Regalia, Gengchen Mai, Stephanie Delbecque, Maarten Frohlich, Patrick Martinent, Trevor Lazarus. On the Prospects of Blockchain and Distributed Ledger Technologies for Open Science and Academic Publishing [Editorial]. Semantic Web Journal, 9.5 (2018): 545-555.

13.TGIS 2018 Gengchen Mai, Krzysztof Janowicz, Yingjie Hu, Song Gao. ADCN: An Anisotropic Density-Based Clustering Algorithm for Discovering Spatial Point Patterns with Noise. Transactions in GIS, 22(2018), 348-369. DOI:10.1111/tgis.12313 [code] * Top 10% Most Downloaded Papers in TGIS (01/2018-12/2019)

12.EKAW 2018 Gengchen Mai, Krzysztof Janowicz, Bo Yan. Support and Centrality: Learning Weights for Translation-based Knowledge Graph Embedding Models, In: Proceedings of EKAW 2018, Nov. 12 - 16, 2018, Nancy, France.

11.ISWC 2018 Krzysztof Janowicz, Bo Yan, Blake Regalia, Rui Zhu, Gengchen Mai. Debiasing Knowledge Graphs: Why Female Presidents are not like Female Popes [Vision Paper], In: Proceedings of ISWC 2018, Oct. 8 - 12, 2018, Monterey, CA, USA.

10.GIScience 2018 Bo Yan, Krzysztof Janowicz, Gengchen Mai, Rui Zhu. xNet+SC: Classifying Places Based on Images by Incorporating Spatial Contexts, In: Proceedings of the 10th International Conference on Geographic Information Science (GIScience 2018), August 28 - 31, 2018, Melbourne, Australia.

9.AGILE 2018 Gengchen Mai, Krzysztof Janowicz, Sathya Prasad, Bo Yan. Visualizing The Semantic Similarity of Geographic Features [Short Paper], In: Proceedings of 21st Conference on Geo-information science (AGILE 2018), June 12 - 15, 2018, Lund, Sweden.

8.ESWC 2018 Blake Regalia, Krzysztof Janowicz, Gengchen Mai, Dalia Varanka, E Lynn Usery. GNIS-LD: Serving and Visualizing the Geographic Names Information System Gazetteer As Linked Data, In: Proceedings of ESWC 2018, June 3 - 7, 2018, Heraklion, Crete, Greece.

2017

7.SIGSPATIAL 2017 Bo Yan, Krzysztof Janowicz, Gengchen Mai, Song Gao. From ITDL to Place2Vec -- Reasoning About Place Type Similarity and Relatedness by Learning Embeddings From Augmented Spatial Contexts, In: Proceedings of the 25th International Conference on Advances in Ge-ographic Information Systems (ACM SIGSPATIAL 2017), November 7 - 10, 2017, Redondo Beach, California, USA.

2016

6.SIGSPATIAL 2016 Gengchen Mai, Krzysztof Janowicz, Yingjie Hu, Song Gao. ADCN: An Anisotropic Density-Based Clustering Algorithm [Short paper], In: Proceedings of the 24th International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2016), October 31 - November 3, 2016, San Francisco Bay Area, California, USA.

5.GIScience 2016 Song Gao, Rui Zhu, Gengchen Mai. Identifying Local Spatiotemporal Autocorrelation Patterns of Taxi Pick-ups and Drop-offs [Short paper], In: Proceedings of the 9th International Conference on Geographic Information Science (GIScience 2016), September 27 - 30, 2016, Montreal, Canada.

4.GIScience 2016 Krzysztof Janowicz, Yingjie Hu, Grant McKenzie, Song Gao, Blake Regalia, Gengchen Mai, Rui Zhu, Benjamin Adams, Kerry Taylor. Moon Landing or Safari? A Study of Systematic Errors and their Causes in Geographic Linked Data, In: Proceedings of the 9th International Conference on Geographic Information Science (GIScience 2016), September 27 - 30, 2016, Montreal, Canada.

2015

3.JAG 2015 Rui Xiao, Shiliang Su, Gengchen Mai, Zhonghao Zhang, Chenxue Yang. Quantifying determinants of cash crop expansion and their relative effects using logistic regression modeling and variance partitioning. International Journal of Applied Earth Observation and Geoinformation 34 (2015) 258–263.

2014

2.EcoInd 2014 Shiliang Su, Yaping Wang, Fanghan Luo, Gengchen Mai, Jian Pu. Peri-urban vegetated landscape pattern changes in relation to socioeconomic development. Ecological Indicators 46 (2014) 477–486.

1.AgiSys 2014 Shiliang Su, Yi’na Hu, Fanghan Luo, Gengchen Mai, Yaping Wang. Farmland fragmentation due to anthropogenic activity in rapidly developing region. Agricultural Systems 131 (2014) 87–93.

Peer-Reviewed CS/GIScience Workshop Paper:

11.Yucheng Shi, Hehuan Ma, Wenliang Zhong, Qiaoyu Tan, Gengchen Mai, Xiang Li, Tianming Liu, and Junzhou Huang. ChatGraph: Interpretable Text Classification by Converting ChatGPT Knowledge to Graphs, In: International Workshop on Learning with Knowledge Graphs at ICDM 2023, December 1-4, 2023, Shanghai, China.

10.Jielu Zhang, Lan Mu, Donglan Zhang, Zhuo Chen, Zhongliang Zhou, Gengchen Mai. Identifying and Intervening in Key Predictors of Out-of-Hospital Cardiac Arrest Survival Outcome Using Explainable Artificial Intelligence, In: ICML 2023 IMLH Workshop, Jul 23 - 29, 2023, Honolulu, Hawaii, USA.

9.Rui Zhu, Krzysztof Janowicz, Gautam Thakur, Xiaogang Ma, Ellie Young, Gengchen Mai. Report of The 1st ACM SIGSPATIAL International Workshop on Geospatial Knowledge Graphs (GeoKG’2022), In: SIGSPATIAL Special, Nov. 1 - 4, 2022, Seattle, Washington, USA.

8.Bruno Martins, Dalton Lunga, Song Gao, Shawn Newsam, Lexie Yang, Xueqing Deng, Gengchen Mai. Report of the 5th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery (GeoAI 2022), In: SIGSPATIAL Special, Nov. 1 - 4, 2022, Seattle, Washington, USA.

7.Cogan Shimizu, Rui Zhu, Gengchen Mai, Mark Schildhauer, Krzysztof Janowicz, and Pascal Hitzler. A Pattern for Modeling Causal Relations Between Events, In: WOP 2021 @ ISWC 2021 , Oct. 24, 2021, Virtual Conference.

6.Rui Zhu, Shirly Ambrose, Lu Zhou, Cogan Shimizu, Ling Cai, Gengchen Mai, Krzysztof Janowicz, Pascal Hitzler, Mark Schildhauer. Environmental Observations in Knowledge Graphs, In: DaMaLOS 2021 @ ISWC 2021 , Oct. 24, 2021, Virtual Conference.

5.Gengchen Mai, Krzysztof Janowicz, Cheng He, Sumang Liu and Ni Lao. POIReviewQA: A Semantically Enriched POI Retrieval and Question Answering Dataset [Short Paper], In: Proceedings of GIR'18 Workshop co-located with ACM SIGSPATIAL 2018, Nov. 6 - 9, 2018, Seattle, Washington, USA. [arxiv]

4.Gengchen Mai, Krzysztof Janowicz, Bo Yan. Combining Text Embedding and Knowledge Graph Embedding Techniques for Academic Search Engines, In: Proceedings of SemDeep-4 Workshop co-located with ISWC 2018, Oct. 8 - 12, 2018, Monterey, CA, USA.

3.Gengchen Mai, Krzysztof Janowicz, Yingjie Hu, Song Gao, Rui Zhu, Bo Yan, Grant McKenzie, Anagha Uppal, and Blake Regalia. Collections of Points of Interest: How to Name Them and Why it Matters [Short Paper], In: Proceedings of Spatial big data and machine learning in GIScience Workshop at GIScience 2018, August 28 - 31, 2018, Melbourne, Australia.

2.Blake Regalia, Krzysztof Janowicz, Gengchen Mai. Phuzzy.link: A SPARQL-Powered Client-Sided Extensible Semantic Web Browser, In: Proceedings of 3rd International Workshop on Visualization and Interaction for Ontologies and Linked Data (VOILA2017) co-located with ISWC 2017, October 22, 2017, Vienna, Austria.

1.Gengchen Mai, Krzysztof Janowicz, Yingjie Hu, Grant McKenzie. A Linked Data Driven Visual Interface for the Multi-Perspective Exploration of Data Across Repositories, In: Proceedings of 2nd International Workshop on Visualization and Interaction for Ontologies and Linked Data (VOILA2016) co-located with ISWC 2016, October 17 or 18, 2016, Kobe, Japan.

Other Publication:

1.Gengchen Mai. Spatially Explicit Machine Learning Model, In: Spatial Data Science Symposium 2019, Dec. 9 - 11, 2019, Santa Barbara, CA, USA.

Patent:

3. US Patent US20220292330A1: Hongxu Ma, Gengchen Mai, Bin Ni. Generation and application of location embeddings.

2. US Patent US20220290989A1: Grigory Bronevetsky, Charlotte Leroy, Bin Ni, Hongxu Ma, Gengchen Mai. Predicting geospatial measures.

1. US Patent 16240539: Gengchen Mai, Cheng He, Sumang Liu, Ni Lao. System and method for natural language processing (nlp) based searching and question answering.

Conference Oral/Poster Presentation:

2023

58. Online Panelist Presentation (2023): CSP: Self-Supervised Contrastive Spatial Pre-Training for Geospatial-Visual Representations, In Digital Twins Webinar 5: Geospatial AI and Digital Twins in Contemporary Infrastructure , Oct 27, 2023, Online.

57. Invited Talk (2023): Foundation Models for GeoAI: Applicability, Autonomy, and Uniqueness, In UGA Franklin College Dean's Board of Advisors Meeting , Oct 16, 2023, Athens, Georgia, USA.

56. Online Keynote Speech (2023): Geographic Question Answering with Spatially Explicit Machine Learning Models, In the 1st Geographic Question Answering Workshop colocated at GIScience 2023 , Sep 12, 2023, Leeds, UK.

55. Online Oral Presentation (2023): Foundation Models for GeoAI: Applicability, Autonomy, and Uniqueness, In GeoAI Talk at Department of Geography, University at Buffalo , Sep 08, 2023, Buffalo, New York, USA.

54. Online Oral Presentation (2023): Foundation Models for GeoAI: Applicability, Autonomy, and Uniqueness, In Google X/Mineral AI Tech Talk , Sep 06, 2023, Mountain View, California, USA.

53. Online Panel Discussion (2023): Spatially Explicit Artificial Intelligence and Machine Learning Thematic Panel Session, In Spatial Data Science Symposium 2023 , Sep 06, 2023, Hybrid.

52. Poster Presentation (2023): CSP: Self-Supervised Contrastive Spatial Pre-Training for Geospatial-Visual Representations, In the Fortieth International Conference on Machine Learning (ICML 2023) , Jul 23 - 29, 2023, Honolulu, Hawaii, USA.

51. Oral Presentation (2023): Foundation Models for GeoAI: Applicability, Autonomy, and Uniqueness, In Google research AI Tech Talk , July 20, 2023, Mountain View, California, USA.

50. Online Oral Presentation (2023): On the Opportunities and Challenges of Foundation Models for GeoAI: Applicability, Autonomy, and Uniqueness, In the 2023 Symposium on Spatiotemporal Data Science at Harvard University , July 16, 2023, Cambridge, Massachusetts, USA.

49. Oral Presentation (2023): Foundation Models for GeoAI: Applicability, Autonomy, and Uniqueness, In Prof. Aditya Grover's Machine Intelligence (MINT) group, Department of Computer Science, UCLA , July 14, 2023, Los Angeles, California, USA.

48. Oral Presentation (2023): EVKG: An interlinked and interoperable electric vehicle knowledge graph for smart transportation system, In 2023 Esri User Conference , July 11, 2023, San Diego, CA, USA.

47. Online Oral Presentation (2023): On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligence: Applicability, Uniqueness, and Autonomy, In The Eighth LiDAR and Forest Ecology Summer School at Peking University , June 24, 2023, Beijing, China.

46. Oral Presentation (2023): Foundation Models for Geospatial and Health Tasks: Applicability, Uniqueness, and Autonomy, In Advances in Multimodal Artificial Intelligence to Enhance Environmental and Biomedical Data Integration Workshop By the National Academies of Sciences, Engineering, and Medicine , June 14 - 15, 2023, Washington DC, USA.

45. Online Oral Presentation (2023): On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligence, In the 126th Open Geospatial Consortium Member Meeting - GeoAI Domain Working Group Session , June 5 - 9, 2023, Huntsville, Alabama, USA.

44. Online Oral Talk (2023): On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligence, In GeoAI Talk at Texas A&M University , May 25, 2023, College Station, Texas.

43. Online Oral Talk (2023): On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligence, In GeoAI Talk at China University of Petroleum (East China) , May 22, 2023, Qingdao, Shandong, China.

42. Lightening Talk (2023): Spatial Social Network research in Artificial General Intelligence Era, In Georgia Tech Spatial Social Network Wqorkshop 2023 , May 18, 2023, Atlanta, GA, USA.

41. Online Oral Presentation (2023): On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligence, In CPGIS/ACM SIGSPATAIL China GeoAI Talk series , May 11, 2023, Online.

40. Online Oral Presentation and Panel Discussion (2023): On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligence, In Geography According to ChatGPT kick-off Online Webinar , May 4, 2023, Online.

39. Invited Online Oral Presentation (2023): On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligence, In Center for Spatial Information Science, The University of Tokyo , Apr. 26, 2023, Tokyo, Japan.

38. Invited Online Oral Presentation (2023): ChatGPT, Foundation Models, and Geo-Foundation Models, In Peking University ChatGPT Webinar , Apr. 17, 2023, Beijing, China.

37. Invited Oral Presentation (2023): Spatially Explicit Artificial Intelligence – Towards General-Purpose Representation Learning of Polygonal Geometries, In AAG 2023 J. Warren Nystrom Award Session , Mar. 24, 2023, Denver, CO, USA.

2022

36. Online invited talk (2022): Towards a Foundation Model for Geospatial Artificial Intelligence, In CPGIS Geographic Digital Twins and GeoAI Seminar , Dec. 21, 2022, Beijing, China.

35. Poster presentation (2022): Understanding Economic Development in Rural Africa using Satellite Imagery, Building footprints and Deep Models, In ACM SIGSPATIAL 2022 , Nov. 1 - 4, 2022, Seattle, WA, USA.

34. Oral presentation (2022): Towards a Foundation Model for Geospatial Artificial Intelligence, In ACM SIGSPATIAL 2022 , Nov. 1 - 4, 2022, Seattle, WA, USA.

33. Invited Oral presentation (2022): Towards a Foundation Model for Geospatial Artificial Intelligence, In University of Washington Geography Roundtable on the Frontiers of Geospatial Artificial Intelligence 2022 , Oct. 31, 2022, Seattle, WA, USA.

32. Invited Seminar presentation (2022): Spatially Explicit Artificial Intelligence for Environmental Data Science, In UGA Marine Science Seminar , Sep 26, 2022, Athens, Georgia, USA.

31. Online Oral presentation (2022): Spatially Explicit Artificial Intelligence, In The School of Resource and Environmental Science, Wuhan University , Sep 20, 2022, Wuhan, Hubei, China.

30. Online Oral presentation (2022): Spatially Explicit Artificial Intelligence, In the 3rd World Young Scientists Forum at the 11th global geographic information Developers Conference (WGDC 2022), July 21, 2022, Beijing.

29. Online Oral presentation (2022): Narrative Cartography with Knowledge Graphs, In Online Workshop of Design & Analytics for Urban Artificial Intelligence @ Texas A&M University, June 24, 2022, Virtual Conference.

28. Online Oral presentation (2022): Geographic Question Answering with Spatially Explicit Machine Learning Models, In AAG 2022 William L. Garrison Award Presentation Session, Feb 26, 2022, Virtual Conference.

2021

27. Online Oral presentation (2021): Geospatial Knowledge Graph and Spatially Explicit AI, In GeoKG & GeoAI 2021 @ GIScience 2021, Sep 27, 2021, Virtual Conference.

26. Online Oral presentation (2021): Location Encoding and Spatially-Explicit Machine Learning, In Nanjing Normal University Geo-Big Data & GeoAI 2021 Summer School, Aug 23, 2021, Nanjing, China.

25. Online Oral presentation (2021): Location Encoding and Spatially-Explicit Machine Learning, In China GIScience Symposium Series No. 5: GeoAI, Feb 16, 2021, Beijing, China.

2020

24. Online Oral presentation (2020): Space2Vec: Multi-Scale Representation Learning for Spatial Feature Distributions using Grid Cells, In Thinkspatial Tech Talk at UCSB Spatial Center, Dec 1, 2020, Santa Barbara, CA,USA.

23. Online Oral presentation (2020): Space2Vec: Multi-Scale Representation Learning for Spatial Feature Distributions using Grid Cells, In Google AI Tech Talk 2020, August 12, 2020, Mountain View, CA, USA.

22. Online Video presentation (2020): SE‐KGE : A location‐aware Knowledge Graph Embedding model for Geographic Question Answering and Spatial Semantic Lifting, In Esri UC 2020, July 13 - 16, 2020, San Diego, CA, USA. [video]

21. Online Video presentation (2020): Multi-Scale Representation Learning for Spatial Feature Distributions using Grid Cells, In ICLR 2020, Apr. 26 - 30, 2020, Addis Ababa, ETHIOPIA. [video]

20. Oral presentation (2020): Knowledge Graphs and Spatiotemporal Data, In NSF OKN VoCamp 2020, Jan. 27 - 28, 2019, Santa Barbara, CA, USA.

2019

19. Oral presentation (2019): Knowledge Graphs and Spatiotemporal Data, In Spatial Data Science Symposium 2019, Dec. 9 - 11, 2019, Santa Barbara, CA, USA.

18. Oral presentation (2019): Contextual Graph Attention for Answering Logical Queries over Incomplete Knowledge Graphs, In ACM K-CAP 2019, Nov. 19 - 21, 2019, Marina del Rey, CA, USA.

17. Oral presentation (2019): A Spatially Explicit Machine Learning Model for Map Generalization, In Apple Map Leadership Presentation, August 15, 2019, Sunnyvale, CA, USA.

16. Poster presentation (2019): A Spatially Explicit Machine Learning Model for Map Generalization, In Apple Intern Machine Learning Symposium 2019, August 1, 2019, Cupertino, CA, USA.

15. Oral presentation (2019): Deeply Integrating Linked Data with Geographic Information Systems, In Esri UC 2019, July 8 - 13, 2019, San Diego, CA, USA.

14. Oral presentation (2019): Relaxing Unanswerable Geographic Questions Using A Spatially Explicit Knowledge Graph Embedding Model, In Spatial Discovery III, May 1 - May 3, 2019, Santa Barbara, CA, USA.

13. Oral presentation (2019): Relaxing Unanswerable Geographic Questions Using A Spatially Explicit Knowledge Graph Embedding Model, In Annual Meeting of AAG 2019: GeoAI and Deep Learning Symposium: Geo-Text Data and Location-based Social Media, April 3 - April 7, 2019, Washington DC, USA.

12. Oral presentation (2018): Support and Centrality: Learning Weights for Translation-based Knowledge Graph Embedding Models, In EKAW 2018, Nov. 12 - 16, 2018, Nancy, France.

2018

11. Oral presentation (2018): POIReviewQA: A Semantically Enriched POI Retrieval and Question Answering Dataset, In GIR'18 Workshop co-located with ACM SIGSPATIAL 2018, Nov. 6 - 9, 2018, Seattle, Washington, USA.

10. Oral presentation (2018): Combining Text Embedding and Knowledge Graph Embedding Techniques for Academic Search Engines, In SemDeep-4 Workshop co-located with ISWC 2018, Oct. 8 - 12, 2018, Monterey, CA, USA.

9. Oral presentation (2018): xNet+SC: Classifying Places Based on Images by Incorporating Spatial Contexts, In GIScience 2018, Aug 27 - 31, 2018, Melbourne, Australia.

8. Oral presentation (2018): Collections of Points of Interest: How to Name Them and Why it Matters, In Spatial big data and machine learning in GIScience Workshop at GIScience 2018, Aug 27 - 31, 2018, Melbourne, Australia.

7. Oral presentation (2018): Visualizing The Semantic Similarity of Geographic Features, In AGILE 2018, June 12 - 15, 2018, Lund, Sweden.

6. Oral presentation (2018): Visualizing The Semantic Similarity of Geographic Features, In Annual Meeting of AAG 2018: Artificial Intelligence and Deep Learning Symposium: Geospatial Semantics and Geo-Text Data Analytics II, April 10 - April 14, 2018, New Orleans, Louisiana, USA.

2017

5. Oral presentation (2017): A Semantically Enabled Geographic Information Retrieval Framework by using Representation Learning: A Simple Case Study of DBpedia, In GIS Day@UCSB Geography, November 17, 2017, Santa Barbara, California, USA.

4. Oral presentation (2017): ADCN: An Anisotropic Density-Based Clustering Algorithm for Discovering Spatial Point Patterns with Noise, In Annual Meeting of AAG 2017: Spatiotemporal Symposium -- Big Spatiotemporal Data Discovery and Mining Session, April 5- April 9, 2017, San Francisco, California, USA.

2016

3. Poster presentation (2016): ADCN: An Anisotropic Density-Based Clustering Algorithm, In 24th International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2016) , October 31 - November 3, 2016, San Francisco Bay Area, California, USA.

2. Poster presentation (2016): A Linked Data Driven Visual Interface for the Multi-Perspective Exploration of Data Across Repositories, In 12th Reasoning Web Summer School (RW 2016) co-located with 10th International Conference on Web Reasoning and Rule Systems (RR 2016) , September 5 - 9, 2016, Aberdeen, Scotland, UK.

1. Oral presentation (2016): Tea Plantation Expansion in Hangzhou, China: Process, Related factors & Ecological Effect, In 2016 Annual Meeting of AAG: The Quest to Map Plant Species Session, March 28- April 1, 2016, San Francisco, California, USA.


Research Experience & Project

POI Retrieval and Question Answering

Machine Learning & NLP Research Intern at Saymosaic Inc.

2018/06 - 2018/09

Many services that perform information retrieval for Points of Interest (POI) utilize a Lucene-based setup with spatial filtering. While this type of system is easy to implement it does not make use of semantics but relies on direct word matches between a query and reviews leading to a loss in both precision and recall. To study the challenging task of semantically enriching POIs from unstructured data in order to support open-domain search and question answering (QA), we introduce a new dataset POIReviewQA. It consists of 20k questions (e.g.“is this restaurant dog friendly?”) for 1022 Yelp business types. For each question we sampled 10 reviews, and annotated each sentence in the reviews whether it answers the question and what the corresponding answer is. To test a system’s ability to understand the text we adopt an information retrieval evaluation by ranking all the review sentences for a question based on the likelihood that they answer this question. We build a Lucene-based baseline model, which achieves 77.0% AUC and 48.8% MAP. A sentence embedding-based model achieves 79.2% AUC and 41.8% MAP, indicating that the dataset presents a challenging problem for future research by the GIR community. The result technology can help exploit the thematic content of web documents and social media for characterisation of locations.

Topic:

Question Answering, Information Retrieval, Deep Reinforcement Learning

IOS LD Connect Academic Search Engine And Reviewer Suggestion System

Graduate Student Researcher in STKO Lab, Department of Geography, UCSB

2017/03 - Present

In this work, An academic search engine has been developed on top of IOS LD Connect Knowledge Graph. Document Embedding and Knowledge Graph Embedding have been utilized to facilitate the searching for papers, authors, and reviewers. Note that this search engine has been adopted as the official academic search engine for IOS Press.

ESRI Linked Data Connecter

Graduate Student Researcher in STKO Lab, Department of Geography, UCSB

2016/10 - Present

In this work, we conceptualized and prototypically implemented a Linked Data connector framework as a set of toolboxes for Esri’s ArcGIS. We discussed from within a GIS, how to connect to Linked Data endpoints, how to use ontologies to probe data and derive appropriate GIS representations on-the-fly, how to make use of reasoning, how to derive data that is ready for spatial analysis out of RDF triples, and, most importantly, how to utilize the link structure of Linked Data to enable analysis.

Alexandria Digital Library (ADL) Gazetteer

Graduate Student Researcher in STKO Lab, Department of Geography, UCSB

2016/08 - Present

Funded by IOS Press

Alexandria Digital Library (ADL) is UC Santa Barbara Library's home for collections of digital research materials. This project aims at leveraging Semantic Web technologies, especially GeoSPARQL, to facilitate the spatial/no-spatial query of ADL Gazetteer and dynamically visualize the results. Right now, the ADL Gazetteer data has been held and managed in a modified version of Apache Marmotta triple store in which GeoSPARQL is enabled. Thanks to all the help from STKO lab members, two different interfaces have been established to facilitate users to interactively explore the geographic data in ADL Gazetteer which are list bellow:

This is a map interface to help users do spatial/no-spatial queries on ADL Gazetteer, like finding all the entities in "administrative region" class in current map layout whose label contains "paris". GeoSPARQL is used to do spatial queries. Acknowledge to Grant McKenzie and Bo Yan.

ADL Linked Data Visualizer:

UC Santa Barbara

This is a dereferencing user interface for all the entities and entity types in ADL Gazetteer. For example, UC Santa Barbara can be dereferenced by THIS IRI. Acknowledge to Blake Regalia. See more information for our Phuzzy.link paper

.

Esri Hackathon Project: Visualizing The Semantic Similarity of Geographic Features

Esri Inc., Redlands, CA, USA

2017/07/16 - 2017/07/18

In this work, a semantically enriched geospatial data visualization and searching framework and evaluated it using a subset of places from DBpedia. The resulting map, as a representation of the semantic distribution of these geographic features, is produced by using multiple techniques including paragraph vector and clustering. Next, an information retrieval (IR) model is developed based on the vector embedding of each geographic feature. The results are visualized using the semantic similarity-based map as well as a regular map. We believe such visualization can help users to understand latent relationships between geographic features that may otherwise seem unrelated.

IOS Press RelFinder

Graduate Student Researcher in STKO Lab, Department of Geography, UCSB

2016/10 - Present

In this work, we developed an Linked Data Visualization Interface for IOS Press Linked Dataset. This interface can visualize the Linked Data Cloud as a graph and users can further explore the graph content using right click menu. The Left sidebar will display the information of the current entity. The irght sidebar helps users do "Relationship Finder" style search.

URL: http://stko-testing.geog.ucsb.edu/gengchen/IOSRelFinder/

An Anisotropic Density-Based Clustering Algorithm (ADCN)

Graduate Student Researcher in STKO Lab, Department of Geography, UCSB

2015/09 - 2017/06

Density-based clustering algorithms such as DBSCAN have been widely used for spatial knowledge discovery as they offer several key advantages compared to other clustering algorithms. They can discover clusters with arbitrary shapes, are robust to noise and do not require prior knowledge (or estimation) of the number of clusters. The idea of using a scan circle centered at each point with a search radius Eps to find at least MinPts points as a criterion for deriving local density is easily understandable and sufficient for exploring isotropic spatial point patterns. However, there are many cases that cannot be adequately captured this way, particularly if they involve linear features or shapes with a continuously changing density such as a spiral. In such cases, DBSCAN tends to either create an increasing number of small clusters or add noise points into large clusters. Therefore, in this paper, we propose a novel anisotropic density-based clustering algorithm (ADCN). To motivate our work, we introduce synthetic and real-world cases that cannot be sufficiently handled by DBSCAN (and OPTICS). We then present our clustering algorithm and test it with a wide range of cases. We demonstrate that our algorithm can perform as equally well as DBSCAN in cases that do not explicitly benefit from an anisotropic perspective and that it outperforms DBSCAN in cases that do. We show that our approach has the same time complexity as DBSCAN and OPTICS, namely O(n log n) when using a spatial index and O(n 2 ) otherwise. We provide an implementation and test the runtime over multiple cases. Finally, we apply DBSCAN, OPTICS, and our ADCN to the extraction of urban Areas of interest (AOI) from geotagged photos in six cities. Visual comparison shows that, comparing to DBSCAN and OPTICS, ADCN is inclined to extract AOI with linear shapes which follow the underline road network. ADCN also turn out to connect areas when the spatial distribution of them shows similar direction.

GitHub JS Code Repository:

https://github.com/gengchenmai/adcn

GitHub Python Code Repository:

https://github.com/gissong/ADCN

GeoLink

Graduate Student Researcher in National Center for Ecological Analysis and Synthesis (NCEAS), UCSB

2016/01 - 2016/04

Funded by NSF EarthCube program

GeoLink is a building block project of EarthCube project. It aims at building up a oceanography data integration framwork for seven data repositories and a collections of Ontology Design Patterns. My contribution in this project is creating a graph visualizer to query the paths between two entities. This graph visualizer help the user to discover the data by follow-your-nose search across different data repositories.

Paper: A Linked Data Driven Visual Interface for the Multi-Perspective Exploration of Data Across Repositories

URL: http://demo.geolink.org/

Undergraduate Research & Thesis

Thesis Topic:

Tea Plantation Expansion in Southeast of China: Process, Driving Forces and Ecological Effect

The coupling mechanism of farmland’s service function and landscape fragmentation

2014/01 - 2015/07

Funded by the Fundamental Research Funds for the Central Universities (No. 2042014kf0048)

The construction of generalization classifier by using phenological index to extract the farmland information

2014/01 - 2015/12

Funded by Open Research Fund Program of Key Laboratory of Digital Mapping and Land Information Application Engineering, National Administration of Surveying, Mapping and Geoinformation (No. GCWD201404)

Recently, tea plantation expansion has become a typical land use change in the subtropical zone of China. My experiment integrated remote sensing, spatial analysis deriving from geographic information system, landscape metric analysis and spatial regression, to quantify the socioeconomic indicators of tea plantation expansion and its effects on landscape pattern, with a case of Hangzhou, China, from 2004 to 2013. Main results showed that: (1) Hangzhou has undergone great tea plantation expansion, about 54975.9 ha, from 2004 to 2013. (2) Tea plantation expansion is highly related to some physical, social, and economical factors: slope, elevation, distance to water bodies, distance to roads, distance to socioeconomic centers, public financial revenue and per capita average income of farmers. (4) Tea plantation expansion would make the landscape become fragmentized, complex and irregular. Our study contributed to understanding the socioeconomic indicators of tea plantation expansion and its effects on landscape pattern in subtropical China.

URL: This research has been presented in 2016 Annual Meeting of AAG, The Quest to Map Plant Species Session.

Sina-Blog Check-in Project

Project leader: The Extraction of Point of Interest Based on Multi-source Check-in Data

2013/05 - 2015/06

Funded by Planning Project of Innovation and Entrepreneurship Training of National Undergraduate of Wuhan University (No.1310486034)

As a project leader of this undergraduate training project, I developed a C# Application to get check-in data form Sina-blog. And then we evaluated the effect of the construction of Wuhan Subway Line 2 on the spatial distribution of Sina-Blog Check-in data.

URL: Flow Analysis and Research on Subway Based on "Sina micro-blog" Registration data

GIS & Cartography Course Project

A One month GIS & Cartography Course project

2014/12 - 2015/01

I made two maps of Hengche County by ArcGIS Deasktop. Left one shows the current land use map of Hengche County. The right one shows the Current land use stucture of Hengche County.


Research Grant

Title:

A one-year Planet license to access high-resolution remote sensing imageries

Grant:

UGA Internal Research Support Co-Funding Program

Role:

Principle Investigator

Time:

2023 - Present

Member:

Gengchen Mai (PI)

Title:

Interdisciplinary Approaches to Alzheimer’s Disease Prevention

Grant:

UGA Interdisciplinary Research Pre-Seed Program

Role:

Co-PI

Time:

2022/12 - Present

Member:

Suhang Song (PI), Zhuo Chen, Kerstin Gerst Emerson, M Mahmud Khan, Janani R Thapa, LISA M Renzi, Tianming Liu, Gengchen Mai, Jin Sun, Angela Yao, Kaixiong Ye

Grant:

UGA Geography Faculty Start-Up Grant

Role:

Principle Investigator

Time:

2022 - Present

Member:

Gengchen Mai (PI)

Title:

A Hybrid Spatially-Explicit Machine Learning Model for Species Spatio-temporal Distribution Modeling and Biodiversity Hotspot Prediction

Role:

Principle Investigator

Time:

2020/06/15 - 2020/09/25

Member:

Gengchen Mai (PI)

Title:

Deep species spatio-temporal distribution modeling for biodiversity hotspot prediction

Role:

Principle Investigator

Time:

2019/11 - 2020/11

Member:

Gengchen Mai (PI), Krzysztof Janowicz, Ni Lao, WenyunZuo, Ling Cai.


Award

2022/07/20

Top 10 WGDC 2022 Global Young Scientist Award (10 award recipients every year)

2021/02

AAG Dissertation Research Grants (10 award recipients per year)

2020/06/15 - 2020/09/27

UCSB Geography Research Stipend Award

2019/11/19 - 2019/11/21

The Jack & Laura Dangermond Travel Scholarship for ACM K-CAP 2019 (1 per year)

2019/07/08 - 2019/07/13

The Jack & Laura Dangermond Travel Scholarship for 2019 Esri UC

2019/04/02 - 2019/04/07

The Jack & Laura Dangermond Travel Scholarship for 2019 AAG Annual Meeting

2018/11/12 - 2018/11/16

The Jack & Laura Dangermond Travel Scholarship for EKAW 2018

2018/11/06 - 2018/11/09

The Jack & Laura Dangermond Travel Scholarship for ACM SIGSPATIAL 2018

2018/10/08 - 2018/10/12

NSF Student Travel Awards for ISWC 2018

2018/08/27 - 2018/08/31

ESRI GIScience 2018 Student Travel Awards

2018/08/27 - 2018/08/31

The Jack & Laura Dangermond Travel Scholarship for GIScience 2018

2018/06/12 - 2018/06/15

The Jack & Laura Dangermond Travel Scholarship for AGILE 2018

2018/04/10 - 2018/04/14

The Jack & Laura Dangermond Travel Scholarship for 2018 AAG Annual Meeting

2018/03/01 - 2018/03/02

NSF Student Fellowship for U.S. Semantic Technologies Symposium 2018 (US2TS 2018)

2017/11/07 - 2017/11/10

The Jack & Laura Dangermond Travel Scholarship for ACM SIGSPATIAL 2017

2017/04/06

The 1st Place Best Paper Award at AAG 2017 GIS Special Group Student Paper Competition for "Beyond Coordinates: Incorporating Geographic Knowledge into Geocoding Services Using Linked Open Data" (co-author)

2017/04/05 - 2017/04/09

The Jack & Laura Dangermond Travel Scholarship for 2017 AAG Annual Meeting

2016/09/27 - 2016/09/30

The Jack & Laura Dangermond Travel Scholarship for the 9th International Conference on Geographic Information Science (GIScience 2016)

2016/09/05 - 2016/09/09

NSF Student Fellowship for 12th Reasoning Web Summer School (RW2016)

2016/09/05 - 2016/09/09

The Jack & Laura Dangermond Travel Scholarship for 12th Reasoning Web Summer School (RW2016)

2016/03/29 - 2016/04/02

The Jack & Laura Dangermond Travel Scholarship for 2016 AAG Annual Meeting

2015/09

UCSB Geography Doctoral Scholars Fellowship

2015/06

Outstanding Undergraduate of Wuhan University [武汉大学2015届优秀本科毕业生] (11 out of 8000+ undergraduate students from Wuhan University)

2013/09 - 2014/06

China National Scholarship [国家奖学金]

2013/09 - 2014/06

First-class scholarship and Merit Student of School of Resource and Environmental Sciences, Wuhan University [武大资环院一等奖学金及三好学生]

2012/09 - 2013/06

China National Scholarship [国家奖学金]

2012/09 - 2013/06

First-class scholarship and Merit Student of School of Resource and Environmental Sciences, Wuhan University [武大资环院一等奖学金及三好学生]

2011/09 - 2012/06

China National Scholarship [国家奖学金]

2011/09 - 2012/06

First-class scholarship and Merit Student of School of Resource and Environmental Sciences, Wuhan University [武大资环院一等奖学金及三好学生]


Service

Peer Reviewer for Grant

Date

Role

Funding Agency

Division


2022

Proposal Reviewer

National Science Foundation

Human-Environment and Geographical Sciences (HEGS) Program

Conferences or Workshop Committees

Date

Role

Conference


2024

Symposium Organizer:

AAG 2024 Symposium on GeoAI and Deep Learning for Geospatial Research

2023

PC Member:

NeurIPS 2023, ESWC 2023, ACM SIGSPATIAL 2023

Event Organizer:

GIS Day 2023 @ UGA

2021

Metadata Chair:

GIScience 2021

PC Member:

GIScience 2021, ESWC 2021, ISWC 2021, SDSS 2021

2020

PC Member:

ESWC 2020, ISWC 2020

Session Chair:

AAG 2020: GeoAI and Deep Learning Symposium - Geospatial Knowledge Graphs

2019

Student Organizer:

Spatial Data Science Symposium 2019

PC Member:

LDOW-LDDL 2019, ESWC 2019, ISWC 2019, ACM K-CAP 2019

Session Organizer:

AAG 2019: GeoAI and Deep Learning Symposium - Geo-Text Data and Location-based Social Media

2018

Student Organizer:

IOT 2018

2017

PC Member:

ACM K-CAP 2017

Peer Reviewer for Book

2022

Book Proposal Reviewer:

CRC Press/Taylor & Francis Group

Service:

2024/01 - 2026/01

Non-Student Board of Directors (BOD) Members of Chinese Professional in Geographic Information Systems (CPGIS

2023/08 - 2024/08

Advisory Committee member of UGA Geography

2022/09 - 2023/06

Technical Faculty Committee Member of UGA Geography

2017/09 - 2018/09

Campus Ambassador of Esri at UCSB

2016/09 - 2017/08

Program Manager of UCSB Cognitive Science

2011/09 - 2013/06

Undersecretary of Department of Life and Welfare in the Students' Union of School of Resource and Environmental Sciences, Wuhan University


Teaching

University of Georgia

Fall 2023

Role:

Instructor

Time:

2023 Fall

Institution:

University of Georgia

Teaching Assistant:

Chintan B. Maniyar

Syllabus:

Click Here

Role:

Instructor

Time:

2023 Fall

Institution:

University of Georgia

Teaching Assistant:

Hao Yang

Syllabus:

Click Here

Spring 2023

Role:

Instructor (Co-teach with Prof. Xiaobai (Angela) Yao)

Time:

2023 Spring

Institution:

University of Georgia

Website:

TBD

Role:

Instructor

Time:

2023 Spring

Institution:

University of Georgia

Teaching Assistant:

Chintan B. Maniyar

Syllabus:

Click Here

Fall 2022

Role:

Instructor

Time:

2022 Fall

Institution:

University of Georgia

Teaching Assistant:

Chintan B. Maniyar

Syllabus:

Click Here

University of California Santa Barbara

Guest Lecturers:

2020 Winter

Guest Lecturer of GEOG 176B: Lecture 9: Analysis, Buffers and Map Algebra

2019 Spring

Guest Lecturer of GEOG 176C: Geographic Question Answering

2018 Spring

Guest Lecturer of GEOG 176C: Geographic Knowledge Graph

2017 Spring

Guest Lecturer of GEOG 176C: GIS Applications: Project Proposal

2017 Winter

Guest Lecturer of GEOG 176B: Lecture 7: Conceptual Modeling and Semantics

Role:

Teaching Assistant

Time:

2016 Spring

Institution:

UC Santa Barbara, Santa Barbara, CA, USA 93106

Role:

Teaching Assistant

Time:

2016 Summer Session B

Institution:

UC Santa Barbara, Santa Barbara, CA, USA 93106

Instructor:

Brandi Gamelin



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Contact

Gengchen Mai

Address:

Room 312, Geography and Geology Building, 210 Field St

Department of Geography

University of Georgia

Athens, Georgia 30602, USA

Copyright © Gengchen Mai