Publications

 

iHARP -> Research -> Publications
last updated 2024 December 4

iHARP Publications and accepted research papers.

 

2024

  1. Francis Ndikum Nji, Rohan Salvi, Sai Sri Ram Kuram Tirumala, Jianwu Wang, Xue Zheng. Evaluation of Traditional and Deep Clustering Algorithms for Multivariate Spatiotemporal Data. Accepted by The Seventh IEEE International Workshop on Benchmarking, Performance Tuning and Optimization for Big Data Applications (BPOD 2024) at 2024 IEEE International Conference on Big Data (IEEE Big Data 2024). [arXiv pre-print]
  2. Francis Ndikum Nji, Omar Faruque, Mostafa Cham, Vandana P Janeja, Jianwu Wang. Hybrid Ensemble Deep Graph Temporal Clustering for Spatiotemporal Data. Accepted by The Seventh IEEE International Workshop on Benchmarking, Performance Tuning and Optimization for Big Data Applications (BPOD 2024) at 2024 IEEE International Conference on Big Data (IEEE Big Data 2024)
  3. Akila Sampth., Omar Faruque, Md Azim Khan, Vandana P. Janeja, Jinawu Wang. Physics-Informed Machine Learning for Sea Ice Thickness Prediction. Proceedings Of The IEEE International Conference On Knowledge Graph (IEEE ICKG 2024).
  4. Emam Hossain, Md Osman Gani, Devon Dunmire, Aneesh Subramanian, and Hammad Younas (2024). Time Series Classification of Supraglacial Lakes Evolution over Greenland Ice Sheet. In 2024 International Conference on Machine Learning and Applications (ICMLA). IEEE. (https://arxiv.org/abs/2410.05638)
  5. Maloy Kumar Devnath, Sudip Chakraborty, and Vandana P. Janeja. 2024. Deep Learning for Antarctic Sea Ice Anomaly Detection and Prediction: A Two-Module Framework. In Proceedings of the 1st ACM SIGSPATIAL International Workshop on Geospatial Anomaly Detection, October 29, 2024. ACM, Atlanta GA USA, 90–93. https://doi.org/10.1145/3681765.3698457
  6. Maloy Kumar Devnath, Sudip Chakraborty, and Vandana P. Janeja. 2024. CMAD: Advancing Understanding of Geospatial Clusters of Anomalous Melt Events in Sea Ice Extent. In The 32nd ACM International Conference on Advances in Geographic Information Systems (SIGSPATIAL ’24), October 29-November 1, 2024, Atlanta, GA, USA. ACM, Atlanta, Georgia, USA, https://doi.org/10.1145/3678717.3691280
  7. Subhankar Ghosh, Arun Sharma, Jayant Gupta, Aneesh Subramanian, and Shashi Shekhar. 2024. Towards Kriging-informed Conditional Diffusion for Regional Sea-Level Data Downscaling: A Summary of Results. In Proceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems, October 29, 2024. ACM, Atlanta GA USA, 372–383. https://doi.org/10.1145/3678717.3691304
  8. Francis Ndikum Nji, Omar Faruque, Mostafa Cham, Janeja Vandana, and Jianwu Wang. 2024. Hybrid Ensemble Deep Graph Temporal Clustering for Spatiotemporal Data. https://doi.org/10.48550/ARXIV.2409.12590
  9. Subhankar Ghosh, Arun Sharma, Jayant Gupta, and Shashi Shekhar. 2024. Towards Statistically Significant Taxonomy Aware Co-Location Pattern Detection (Short Paper). LIPIcs, Volume 315, COSIT 2024 315, (2024), 25:1-25:11. https://doi.org/10.4230/LIPICS.COSIT.2024.25 *
  10. Gong Cheng, Mathieu Morlighem, and Sade Francis. 2024. Forward and Inverse Modeling of Ice Sheet Flow Using Physics‐Informed Neural Networks: Application to Helheim Glacier, Greenland. Journal of Geophysical Research: Machine Learning and Computation 1, 3 (September 2024), e2024JH000169. https://doi.org/10.1029/2024JH000169
  11. Sahara Ali, Omar Faruque, and Jianwu Wang. 2024. Estimating Direct and Indirect Causal Effects of Spatiotemporal Interventions in Presence of Spatial Interference. In Machine Learning and Knowledge Discovery in Databases. Research Track, Albert Bifet, Jesse Davis, Tomas Krilavičius, Meelis Kull, Eirini Ntoutsi and Indrė Žliobaitė (eds.). Springer Nature Switzerland, Cham, 213–230. https://doi.org/10.1007/978-3-031-70352-2_13
  12. Sahara Ali, Uzma Hasan, Xingyan Li, Omar Faruque, Akila Sampath, Yiyi Huang, Md Osman Gani, and Jianwu Wang. 2024. Causality for Earth Science — A Review on Time-series and Spatiotemporal Causality Methods. https://doi.org/10.48550/arXiv.2404.05746
  13. Aneesh Subramanian, Devon Dunmire, Emam Hossain, Md Osman Gani, Alison Banwell, and Brendan Myers. 2024. The fate of Greenland Ice Sheet supraglacial lakes in a warm and cool year. https://doi.org/10.5194/egusphere-egu24-20925
  14. Gong Cheng, Mathieu Morlighem, and Sade Francis. 2024. A Unified Framework for Forward and Inverse Modeling of Ice Sheet Flow using Physics Informed Neural Networks. https://doi.org/10.5194/egusphere-egu24-2495
  15. Tolulope Ale, Vandana P. Janeja, and Nicole-Jeanne Schlegel. 2024. Harnessing Feature Clustering For Enhanced Anomaly Detection With Variational Autoencoder And Dynamic Threshold. In IGARSS 2024 – 2024 IEEE International Geoscience and Remote Sensing Symposium, July 07, 2024. IEEE, Athens, Greece, 8692–8696. https://doi.org/10.1109/IGARSS53475.2024.10640794
  16. Bayu Adhi Tama, Vandana Janeja, and Sanjay Purushotham. “Assessing Annotation Accuracy in Ice Sheet Using Quantitative Metrics,” 2024. In 2024 IEEE International Geoscience and Remote Sensing Symposium in Athens, Greece, FRPB.PA.46. [Poster]
  17. Maruthi P. Chellatore and Sharad Sharma. “Mobile Application for Identifying Anomalous Behavior and Conducting Time Series Analysis Using Heterogeneous Data.” In 26th International Conference on Human-Computer Interaction (HCI International 2024), June 29 – July 4, 2024, Washington, DC. HCI International. https://doi.org/10.1007/978-3-031-60458-4_12
  18. Sharad Sharma, Sri Chandra Dronavalli, Maruthi P. Chellatore, and Rishitha Pesaladinne. “Interactive Visualizations for Crime Data Analysis by Mixed Reality.” In 26th International Conference on Human-Computer Interaction (HCI International 2024), June 29 – July 4, 2024, Washington, DC. HCI International. https://doi.org/10.1007/978-3-031-61047-9_19
  19. Bayu Adhi Tama, Sanjay Purushotham, and Vandana Janeja. “A Pilot Study on the Challenges in Ice Layer Annotations,” 2024. In 13th International Conference on Climate Informatics in London, UK. https://doi.org/10.5281/ZENODO.11078788
  20. Saydeh N. Karabatis and Vandana P. Janeja. 2024. Narrative to Trajectory (N2T+): Extracting Routes of Life or Death from Human Trafficking Text Corpora. https://doi.org/10.48550/ARXIV.2405.06129
  21. Yuchuan Huang and Mohamed F. Mokbel. 2024. Sparcle: Boosting the Accuracy of Data Cleaning Systems through Spatial Awareness. Proc. VLDB Endow. 17, 9 (May 2024), 2349–2362. https://doi.org/10.14778/3665844.3665862
  22. Ziqi Yin, Adam R Herrington, Rajashree Datta, Aneesh C. Subramanian, Jan Thérèse Maria Lenaerts, and Andrew Gettelman. 2024. Improved Understanding of Multicentury Greenland Ice Sheet Response to Strong Warming in the Coupled CESM2‐CISM2 with Regional Grid Refinement. https://doi.org/10.22541/au.170967825.56554188/v1
  23. Gong Cheng, Mathieu Morlighem, and Sade Francis. 2024. A unified framework for forward and inverse modeling of ice sheet flow using physics-informed neural networks. https://doi.org/10.22541/essoar.170965007.78479393/v1
  24. Devon Dunmire, Nander Wever, Alison F. Banwell, and Jan T. M. Lenaerts. 2024. Antarctic-wide ice-shelf firn emulation reveals robust future firn air depletion signal for the Antarctic Peninsula. Commun Earth Environ 5, 1 (February 2024), 100. https://doi.org/10.1038/s43247-024-01255-4
  25. Sahara Ali, Omar Faruque, Yiyi Huang, Md Osman Gani, Aneesh Subramanian, Nicole-Jeanne Schlegel, and Jianwu Wang. “Estimating Causal Effects of Greenland Blocking on Arctic Sea Ice Melt Using Deep Learning Technique,” 2023. In American Meteorological Society’s 23rd Conference on Artificial Intelligence for Environmental Science 2024. Poster at AMS, 668. [Conference Paper/Poster]
  26. Tolulope Ale, Nicole-Jeanne Schlegel, Vandana Janeja. “Enhanced Multivariate Anomaly Detection and Feature Attribution in Climate Data.” 2024. In the 30th SIGKDD Conference on Knowledge Discovery and Data Mining – Applied Data Science Track. KDD 2024 – A.D.S.
  27. Sharad Sharma and Sri Chandra Dronavalli. “Data Analysis and Visualization of Crime Data.” Electronic Imaging 36, no. 1 (January 21, 2024): 364-1-364–66. https://doi.org/10.2352/EI.2024.36.1.VDA-364.

2023

  1. Louis Lapp, Sahara Ali, and Jianwu Wang. 2023. Integrating Fourier Transform and Residual Learning for Arctic Sea Ice Forecasting. In 2023 International Conference on Machine Learning and Applications (ICMLA), December 15, 2023. IEEE, Jacksonville, FL, USA, 1753–1758. https://doi.org/10.1109/ICMLA58977.2023.00266
  2. Sahara Ali, Omar Faruque, Yiyi Huang, Md. Osman Gani, Aneesh Subramanian, Nicole-Jeanne Schlegel, and Jianwu Wang. 2023. Quantifying Causes of Arctic Amplification via Deep Learning Based Time-Series Causal Inference. In 2023 International Conference on Machine Learning and Applications (ICMLA), December 15, 2023. IEEE, Jacksonville, FL, USA, 689–696. https://doi.org/10.1109/ICMLA58977.2023.00101
  3. Sharad Sharma, Sri Chandra Dronavalli, Maruthi P. Chellatore, and Rishitha Pesaladinne. “Situational Awareness and Feature Extraction for Indoor Building Navigation Using Mixed Reality.” In IEEE International Conference on Computational Science and Computational Intelligence, December 13-15, 2023, Las Vegas, Nevada. IEEE-CSCI-RTSC. Vol. 2023.
  4. Sharad Sharma, Rishitha Pesaladinne, and Sri Chandra Dronavalli. “Crime Data Visualization Using Virtual Reality and Augmented Reality.” In the IEEE International Conference on Computational Science and Computational Intelligence, December 13-15, 2023, Las Vegas, Nevada. IEEE-CSCI-RTSC. Vol. 2023.
  5. Naomi Tack, Nicholas Holschuh, Sharad Sharma, Rebecca Williams, and Don Engel. 2023. “Initial Development of a WebXR Platform for Ice Penetrating Radar Data, to Improve Our Understanding of Polar Ice Sheets,” December 2023. Poster at the AGU23 meeting, IN43B-0627[Poster]
  6. Christopher Shuman and Mark A. Fahnestock. “Last of the Big Thwaites Bergs – Iceberg B22A Modulates Fast Ice and Ice Front Stability, as It Departs the Amundsen Sea Embayment (2017-2023),” December 2023. Poster at the AGU23 meeting, C21D-1264. [Poster]
  7. Sudip Chakraborty, Chhaya Kulkarni, Atefeh Jebeli, Jianwu Wang, and Vandana Janeja. “Extreme Slash and Burn Practices over the Amazon Rainforest in 2019 Wreaked Havoc on Sea Ice Extent Over the Antarctic,” December 2023. Poster at the AGU23 meeting, C51D-0975[Poster]
  8. Tolulope Ale and Vandana Janeja. 2023. Multi-domain Anomalous Relationships in Heterogeneous Temporal Data. In Review. https://doi.org/10.21203/rs.3.rs-3705904/v1
  9. Atefeh Jebeli, Bayu Adhi Tama, Sanjay Purushotham, and Vandana P. Janeja. 2023. Tracing Englacial Layers in Radargram via Semi-supervised Method: A Preliminary Result. AAAI-SS 2, (2023), 85–88. https://doi.org/10.1609/aaaiss.v2i1.27653 [Symposium Paper]
  10. Nidhin Harilal, Bri-Mathias Hodge, Aneesh Subramanian, and Claire Monteleoni. 2023. STint: Self-supervised Temporal Interpolation for Geospatial Data. (2023). https://doi.org/10.48550/ARXIV.2309.00059 [pre-print]
  11. Katherine Yi, Angelina Dewar, Tartela Tabassum, Jason Lu, Ray Chen, Homayra Alam, Omar Faruque, Sikan Li, Mathieu Morlighem, and Jianwu Wang. “Evaluating Machine Learning and Statistical Models for Greenland Subglacial Bed Topography.” In 2023 International Conference on Machine Learning and Applications (ICMLA), 659–66. Jacksonville, FL, USA: IEEE, 2023. https://doi.org/10.1109/ICMLA58977.2023.00097[Conference Paper]
  12. Sharad Sharma and Rishitha Reddy Pesaladinne. “Spatial Analysis and Visual Communication of Emergency Information through Augmented Reality.” Journal of Imaging Science and Technology 67, no. 6 (November 1, 2023): 1–9. https://doi.org/10.2352/J.ImagingSci.Technol.2023.67.6.060401.
  13. Emam Hossain, Sahara Ali, Yiyi Huang, Nicole J Shchlegel, Jianwu Wang, Aneesh C. Subramanian, & Md Osman Gani. “Incorporating Causality with Deep Learning in Predicting Short-term and Seasonal Sea Ice”. Abstract in 23rd Conference on Artificial Intelligence for Environmental Science, 104th AMS Annual Meeting, 2024, November 2023. [Abstract]
  14. Subhankar Ghosh, Jayant Gupta, Arun Sharma, Shuai An, and Shashi Shekhar. 2023. Reducing False Discoveries in Statistically-Significant Regional-Colocation Mining: A Summary of Results. In 12th International Conference on Geographic Information Science (GIScience 2023) (Leibniz International Proceedings in Informatics (LIPIcs)), 2023. Schloss Dagstuhl – Leibniz-Zentrum für Informatik, Dagstuhl, Germany, 3:1-3:18. https://doi.org/10.4230/LIPIcs.GIScience.2023.3
    [Conference Paper]
  15. Subhankar Ghosh, Shuai An, Arun Sharma, Jayant Gupta, Shashi Shekhar, and Aneesh Subramanian. 2023. Reducing Uncertainty in Sea-level Rise Prediction: A Spatial-Variability-Aware Approach. In I-GUIDE Forum 2023: Harnessing the Geospatial Data Revolution for Sustainability Solutions, 2023. Purdue University Library Publishing. https://doi.org/10.5703/1288284317665
  16. Prathamesh Walkikar, Lei Shi, Bayu Adhi Tama, and Vandana P. Janeja. 2023. Discovery of multi-domain spatiotemporal associations. Geoinformatica (October 2023). DOI:https://doi.org/10.1007/s10707-023-00506-4 [Journal]
  17. Uzma Hasan, Emam Hossain, and Md Osman Gani. “A Survey on Causal Discovery Methods for I.I.D. and Time Series Data,” 2023. https://doi.org/10.48550/ARXIV.2303.15027[Journal]
  18. Sudip Chakraborty, Chhaya Kulkarni, Atefeh Jabeli, Akila Sampath, Gehan Boteju, Jianwu Wang, and Vandana Janeja. 2023. Understanding the Role of 2019 Amazon Wildfires on Antarctic Ice Sheet Melting Using Data Science Approaches. Accepted 2023 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining Workshop: Fragile Earth: AI for Climate Sustainability – from Wildfire Disaster Management to Public Health and Beyond, 2023 [Conference/Workshop Paper]
  19. Subhankar Ghosh, Jayant Gupta, Arun Sharma, Shuai An, and Shashi Shekhar. 2023. Reducing False Discoveries in Statistically-Significant Regional-Colocation Mining: A Summary of Results. In 12th International Conference on Geographic Information Science (GIScience 2023) (Leibniz International Proceedings in Informatics (LIPIcs)), Schloss Dagstuhl – Leibniz-Zentrum für Informatik, Dagstuhl, Germany, 3:1-3:18. DOI: https://doi.org/10.4230/LIPIcs.GIScience.2023.3 [Conference Paper]
  20. Naomi Tack, Rebecca Williams, Nicholas Holschuh, Sharad Sharma, and Don Engel. 2023. Visualizing the Greenland Ice Sheet in VR using Immersive Fence Diagrams. In Practice and Experience in Advanced Research Computing, ACM, Portland OR USA, 429–432. DOI: https://doi.org/10.1145/3569951.3603635 [Conference Paper]
  21. Naomi Tack, Bayu Adhi Tama, Atefeh Jebeli, Vandana P. Janeja, Don Engel, and Rebecca Williams. 2023. Metrics for the Quality and Consistency of Ice Layer Annotations. In IGARSS 2023 – 2023 IEEE International Geoscience and Remote Sensing Symposium, July 16, 2023, Pasadena, CA, USA. IEEE, Pasadena, CA, USA, 4935–4938. https://doi.org/10.1109/IGARSS52108.2023.10283420 [Symposium Paper]
  22. Chhaya Kulkarni, Vandana Janeja, and Nicole-Jeanne Schlegel. 2023. Multi-Contextual Learning: Analyzing Melt Over the Greenland Ice Sheet. In IGARSS 2023 – 2023 IEEE International Geoscience and Remote Sensing Symposium, July 16, 2023, Pasadena, CA, USA. IEEE, Pasadena, CA, USA, 6736–6739. https://doi.org/10.1109/IGARSS52108.2023.10281954 [Symposium Paper]
  23. Naomi Tack, Nicholas Holschuh, Sharad Sharma, Rebecca Williams, and Don Engel. 2023. Development and Initial Testing of XR-Based Fence Diagrams for Polar Science. In IGARSS 2023 – 2023 IEEE International Geoscience and Remote Sensing Symposium, July 16, 2023, Pasadena, CA, USA. IEEE, Pasadena, CA, USA, 1541–1544. https://doi.org/10.1109/IGARSS52108.2023.10281776 [Symposium Paper]
  24. Atefeh Jebeli, Bayu Adhi Tama, Vandana P Janeja, Nicholas Holschuh, Claire Jensen, Mathieu Morlighem, Joseph A Macgregor, and Mark A Fahnestock. 2023. TSSA: TWO-STEP SEMI-SUPERVISED ANNOTATION FOR RADARGRAMS ON THE GREENLAND ICE SHEET. (2023). DOI:https://doi.org/10.13140/RG.2.2.23219.20007 [Symposium Paper]
  25. Sharad Sharma. 2023. Mobile Augmented Reality System for Emergency Response. In 2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA), IEEE, Orlando, FL, USA, 402–406. DOI:https://doi.org/10.1109/SERA57763.2023.10197820 [Conference Paper]
  26. Muhammad Hasan Ferdous, Uzma Hasan, and Md Osman Gani. 2023. eCDANs: Efficient Temporal Causal Discovery from Autocorrelated and Non-stationary Data (Student Abstract). (2023). DOI:https://doi.org/10.48550/ARXIV.2303.02833 [Abstract]
  27. Sharad Sharma and Don Engel. 2023. Mobile augmented reality system for object detection, alert, and safety. ei 35, 12 (January 2023), 218-1-218–5. https://doi.org/10.2352/EI.2023.35.12.ERVR-218

2022

  1. Subhankar Ghosh, Jayant Gupta, Arun Sharma, Shuai An, and Shashi Shekhar. 2022. Towards geographically robust statistically significant regional colocation pattern detection. In Proceedings of the 5th ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, ACM, Seattle Washington, 11–20. DOI:https://doi.org/10.1145/3557989.3566158 [Conference/Workshop Paper]
  2. Sahara Ali, Seraj A.M. Mostafa, Xingyan Li, Sara Khanjani, Jianwu Wang, James Foulds, and Vandana Janeja. 2022. Benchmarking Probabilistic Machine Learning Models for Arctic Sea Ice Forecasting. In IGARSS 2022 – 2022 IEEE International Geoscience and Remote Sensing Symposium, IEEE, Kuala Lumpur, Malaysia, 4654–4657. DOI:https://doi.org/10.1109/IGARSS46834.2022.9883505 [Symposium Paper]
  3. Sahara Ali and Jianwu Wang. 2022. MT-IceNet – A Spatial and Multi-Temporal Deep Learning Model for Arctic Sea Ice Forecasting. In 2022 IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT), IEEE, Vancouver, WA, USA, 1–10. DOI:https://doi.org/10.1109/BDCAT56447.2022.00009 [Best Paper Award] [Conference Paper]
  4. Uzma Hasan and Md Osman Gani. 2022. KCRL: A Prior Knowledge Based Causal Discovery Framework with Reinforcement Learning. In Machine Learning in Health Care. Retrieved from https://api.semanticscholar.org/CorpusID:256943569 [Conference Paper]
  5. Xingyan Li, Jian Li, Zachary Williams, Xin Huang, Mark Carroll, and Jianwu Wang. 2022. Enhanced Deep Learning Super-Resolution for Bathymetry Data. In 2022 IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT), IEEE, Vancouver, WA, USA, 49–57. DOI:https://doi.org/10.1109/BDCAT56447.2022.00014 [Conference Paper]