Francis Nji successfully defends his PhD Proposal Congratulatoins Francis!
Francis Nji, iHARP Research Assistant successfully defended his PhD Proposal on Monday, January 27, 2025. Join iHARP in congratulating Francis on his successful PhD Proposal defense!

Title
Accurate Clustering of Multi-dimensional Multivariate Spatiotemporal data

Committee
Abstract
The growing availability of multivariate spatiotemporal data, which includes datasets containing both spatial and temporal dimensions across multiple variables, presents significant opportunities for extracting insights into complex environmental systems, societal trends, and dynamic processes in fields such as environmental monitoring, urban planning, traffic management, transportation, social media analysis, epidemiology, climatology, crime analysis and disaster management where understanding the interactions between spatial locations and their evolution over time is crucial for decision-making. Proper analysis of these datasets enable researchers to understand interactions and patterns that evolve over time and space, facilitating advancements in predictive modeling, causal analysis, and decision-making for addressing global challenges like climate change, resource management, and public health crises. One of such analytical approaches to extract meaningful insights from this data is clustering. Clustering is the process of grouping data with similar spatial attributes, temporal attributes, or both, from which many significant events and regular phenomena can be discovered. However, clustering this data is highly challenging due to the complexities involved in accounting for both spatial autocorrelation and temporal dependencies, as well as the high dimensionality of multivariate data. To tackle these challenges, this dissertation presents three innovative approaches aimed at accurately partitioning complex multivariate spatiotemporal data such that similar points are grouped together and dissimilar points are segregated. Each proposed model is designed to capture the nuanced spatial and temporal relationships inherent in the data, while enhancing clustering performance and stability. By leveraging advanced traditional and deep learning techniques, the proposed models provide robust solutions for managing the complexities of spatiotemporal datasets, resulting in more accurate, stable and interpretable clustering outcomes.

The first proposed model, Hybrid Ensemble Deep Graph Temporal Clustering (HEDGTC), integrates homogeneous and heterogeneous ensemble clustering techniques in an attempt to harness their individual strengths while mitigating their weaknesses. HEDGTC further employs a dual-consensus approach to address noise and misclassification that might result from base clusters. To obtain the desired clusters, HEDGTC employs a deep graph attention autoencoder network which simultaneously updates the clustering loss and reconstruction loss to improve the clustering results in terms of performance and stability. When compared with existing state-of-the-art ensemble models, HEDGTC outperforms with significant margins proving capable to capture implicit temporal patterns and provides consistent results when tested on real-world multivariate spatiotemporal datasets. Although HEDGTC outperforms existing ensemble algorithms, it has its limitations. Real-world multivariate spatiotemporal data is truly complex and can be characterized by non-linearity: variables may exhibit nonlinear interdependencies, localized patterns: clusters may form in specific regions of space, time, or feature combinations, irrelevant dimensions: datasets often contain redundant information, or irrelevant variables and overlapping clusters: a single data point can belong to different clusters. In such cases, HEDGTC might have a hard time to deal with this dependencies therefore the need to develop advanced algorithms that, unlike HEDGTC which rely on global features to perform clustering, will include local feature subspaces and the capability to capture underlying structures in data with both spatial and temporal dimensions.

To address the limitations of HEDGTC, we propose a novel Attention-Guided Deep Temporal Subspace Clustering (A-DATSC) for multivariate spatiotemporal data. A-DATSC incorporates a deep subspace clustering generator and a quality-verifying discriminator that work in tandem. Inspired by the recent success of the U-Net architecture, the generator combines CNN-RNN-attention mechanisms in an autoencoder to capture spatial, temporal and salient representations respectively present in multivariate spatiotemporal data. The autoencoder is equipped with a fully connected GNN-based self-expressive network that extracts the weights of the latent features into a coefficient matrix and a clustering layer that performs clustering through the optimization of the reconstruction loss, self-expressive loss and clustering loss in a iterative manner. The discriminator evaluates current clustering performance by inspecting whether the re-sampled data from estimated subspaces have consistent subspace properties, and supervises the generator to progressively improve subspace clustering. Experimental results on three real-world multivariate spatiotemporal data demonstrate the advantages of A-DATSC over shallow and few deep subspace clustering models.

In recent years, research on clustering analysis has largely focused on improving accuracy and efficiency, often at the cost of interpretability. Geospatial clustering of multivariate spatiotemporal data plays a critical role in analyzing complex spatial patterns for applications such as urban planning, mobility analysis, and climate monitoring. However, the interpretability of clustering results remains a significant challenge due to the "black-box" nature of clustering algorithms and the inherent complexity of multivariate spatiotemporal data. Ensuring interpretability is essential for fostering trust, meeting ethical standards, and complying with regulatory requirements, as clustering-derived decisions must be transparent and justifiable. To address these challenges, we propose a novel end-to-end Interpretable Causal Clustering (ICC) model for high dimensional multivariate spatiotemporal data. ICC employs a causal-discovery feature engineering pre-clustering and a causal inference in-clustering phase. Pre-clustering is achieved through an ensemble of causal discovery methods to prioritize causally significant features, enhanced by spatial modeling and sparsity regularization to focus on relevant features. In-clustering is achieved through a U-Net Autoencoder architecture with stacked GATv2 layers for capturing spatial dependencies and ConvLSTM for temporal modeling. ICC integrates a Probabilistic Discriminative Model (PDM) at the latent encoding layer to further enhance the encoding of causally significant features, ensuring that the latent representations respect causal constraints. ICC incorporates Dynamic Bayesian Networks as a causal inference technique to ensure that the clustering process respects causal dependencies. To improve clustering results, ICC introduces a causal regularization loss term that penalizes clusters that violate causal constraints. To further enhance interpretability, ICC introduces Counterfactual reasoning that seeks to validate clusters for causal consistency and maps them onto geospatial and temporal causal graphs. This further tests the validity of the clusters if they reflect true causal relationships. ICC mitigates confounding effects by explicitly modeling confounders which reduces noise and spurious correlations. Experimental results demonstrate that ICC significantly enhances interpretability and accuracy in geospatial clustering, offering actionable insights into the dynamics of multivariate spatiotemporal climate data. We plan to evaluate our approach on a suite of synthetic and real world clustering problems, and compare across state of the art interpretable and non-interpretable clustering algorithms.
]]> Francis Nji, iHARP Research Assistant successfully defended his PhD Proposal on Monday, January 27, 2025. Join iHARP in congratulating Francis on his successful PhD Proposal defense! Title... https://iharp.umbc.edu/ https://dev.my.umbc.edu/api/v0/pixel/news/146810/guest@my.umbc.edu/658f7d619d7f2761606c7135b99f5e63/api/pixel iharp iHARP https://dev.my.umbc.edu/groups/iharp https://assets2-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xsmall.png?1663786838 https://assets4-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/original.png?1663786838 https://assets4-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xxlarge.png?1663786838 https://assets2-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xlarge.png?1663786838 https://assets3-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/large.png?1663786838 https://assets1-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/medium.png?1663786838 https://assets4-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/small.png?1663786838 https://assets2-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xsmall.png?1663786838 https://assets3-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xxsmall.png?1663786838 iHARP https://assets1-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/810/941037366577c44e59f969c6eacb2a76/xxlarge.jpg?1738090897 https://assets2-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/810/941037366577c44e59f969c6eacb2a76/xlarge.jpg?1738090897 https://assets3-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/810/941037366577c44e59f969c6eacb2a76/large.jpg?1738090897 https://assets2-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/810/941037366577c44e59f969c6eacb2a76/medium.jpg?1738090897 https://assets4-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/810/941037366577c44e59f969c6eacb2a76/small.jpg?1738090897 https://assets2-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/810/941037366577c44e59f969c6eacb2a76/xsmall.jpg?1738090897 https://assets2-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/810/941037366577c44e59f969c6eacb2a76/xxsmall.jpg?1738090897 1 0 true Tue, 28 Jan 2025 14:01:56 -0500 Full-Circle Climate Communication Workshop

Thank you to those who attended and participated in the first Full-Circle Climate Communication Workshop held at UMBC between January 13 to 17, 2025. The workshop successfully brought together over 50 people from a wide range of disciplines and with varied expertise to consider how best to communicate issues regarding climate resilience. 


During the workshop, participants were challenged to strategize and develop new and innovative ways to communicate in a transdisciplinary team. Each team consisted of a variety of experts from a wide range of fields that included but were not limited to Public Policy, Data Science, Artificial Intelligence, Data Visualization, Visual Arts, Performance Arts, Geography, Storytelling, Media Communication, and Behavioral Sciences. 


We truly thank everyone who made the workshop a success. 


Full-Circle Climate Workshop Committee:  Dr. Lee Boot, Dr. Anita Komlodi, Dr. Eric Stokan, Dr. Rebecca Williams, Dr. Josephine Namayanja, Nikki Monczewski


Those who helped support, and we could not have done it without them, include: Jasmin Diaz, Xiaofei Xie, and Hemanth Chelluri, as well as graduate student volunteers from iHARP.


This workshop was organized by the NSF HDR Institute for Harnessing Data and Model Revolution in the Polar Regions (iHARP) in collaboration with the Imaging Research Center (IRC), and the Center for Social Science Scholarship (CS3)., .  


If you are interested in joining, participating, or speaking at the next Full-Circle Communication Workshop, please click here to join our mailing list. 

]]> Thank you to those who attended and participated in the first Full-Circle Climate Communication Workshop held at UMBC between January 13 to 17, 2025. The workshop successfully brought together... http://iharp.umbc.edu https://dev.my.umbc.edu/api/v0/pixel/news/146779/guest@my.umbc.edu/3d6a283bbeef030e2cf5d3bc64fefa48/api/pixel iharp iHARP https://dev.my.umbc.edu/groups/iharp https://assets2-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xsmall.png?1663786838 https://assets4-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/original.png?1663786838 https://assets4-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xxlarge.png?1663786838 https://assets2-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xlarge.png?1663786838 https://assets3-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/large.png?1663786838 https://assets1-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/medium.png?1663786838 https://assets4-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/small.png?1663786838 https://assets2-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xsmall.png?1663786838 https://assets3-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xxsmall.png?1663786838 iHARP https://assets4-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/779/080fe7d99bc690b2743704e32b044c05/xxlarge.jpg?1738013200 https://assets3-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/779/080fe7d99bc690b2743704e32b044c05/xlarge.jpg?1738013200 https://assets3-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/779/080fe7d99bc690b2743704e32b044c05/large.jpg?1738013200 https://assets2-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/779/080fe7d99bc690b2743704e32b044c05/medium.jpg?1738013200 https://assets1-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/779/080fe7d99bc690b2743704e32b044c05/small.jpg?1738013200 https://assets4-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/779/080fe7d99bc690b2743704e32b044c05/xsmall.jpg?1738013200 https://assets4-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/779/080fe7d99bc690b2743704e32b044c05/xxsmall.jpg?1738013200 0 0 true Mon, 27 Jan 2025 16:28:48 -0500 Rohan Putatunda successfully defends his PhD Proposal Congratulatoins Rohan!
Rohan Putatunda, iHARP Research Assistant successfully defended his PhD Proposal on Monday, January 27, 2025. Join iHARP in congratulating Rohan on his successful PhD Proposal defense!

Title
Deep Learning for Ice Calving Front Analysis: Advancing Understanding through AI-Driven Techniques

Committee
Abstract
Ice calving, the process where large ice masses detach from a glacier’s terminus, is a significant driver of ice mass loss and contributes to global sea-level rise. In ice calving, ice calving fronts refer to the terminus regions where these events occur, often producing icebergs as large as Manhattan, which eventually fragment into smaller pieces, or "chicklets." These chicklets, influenced by environmental forces such as ocean currents and winds, follow complex trajectories that can disrupt maritime routes. Although traditional methods for monitoring ice-calving fronts rely heavily on manual reviews of time series satellite imagery, they are time-intensive, prone to human error, and lack scalability. Recent advances in deep learning have introduced automation in segmenting ice-calving fronts, but critical challenges such as predicting future calving front positions and forecasting chicklet trajectories remain underexplored. This thesis addresses three fundamental challenges in understanding and predicting ice-calving processes. First, it tackles the challenge of accurate segmentation of ice calving fronts, characterized by sparse pixel representation, through SEATTNET, a novel hybrid attention model that combines squeeze-and-excitation (SE) blocks with spatial attention gates to enhance feature representation and segmentation accuracy. Second, it explores forecasting future ice-calving front position, where the absence of explicit spatiotemporal data and the nonlinear nature of latitude-longitude temporal sequences present significant challenges. To address these, a georeferenced dataset derived from segmentation masks is utilized alongside the GlaSpectra model, which employs spectral convolution layers along with FFT and IFFT to capture global and local spatial relationships, enabling precise trajectory forecasting. Finally, this thesis also proposes to tackle the challenge of predicting the movement of calved ice fragments, known as icebergs or "chicklets," whose trajectories are highly unpredictable due to the influence of ocean currents, winds, and other environmental factors. To address this, we used spatiotemporal data of iceberg movement over time and applied ConvLSTM layers to capture both the spatial patterns and temporal dynamics. To make predictions more accurate, we developed a custom drift loss function that focuses on two key aspects: how the size and shape of the chicklets change over time and how their movement patterns evolve. The loss function incorporates the principle that the larger the volume of the ice mass, the slower its movement pattern is likely to be, ensuring that the model captures this critical physical relationship. This approach enables our proposed deep learning based model to not only predict the trajectory of the icebergs but also understand the relationship between their motion and their changing dimensions. By addressing these complexities, this research not only advances the use of AI in glaciology, offering practical, and scalable, tools for studying and predicting ice calving and its after-effect of ice chicklets behavior, but also has potential applications in studying landslide movements, and coastal erosion movement.

]]> Rohan Putatunda, iHARP Research Assistant successfully defended his PhD Proposal on Monday, January 27, 2025. Join iHARP in congratulating Rohan on his successful PhD Proposal defense! Title... https://iharp.umbc.edu/ https://dev.my.umbc.edu/api/v0/pixel/news/146771/guest@my.umbc.edu/ea91dba92e64ebdeacf93faacb9caa6f/api/pixel iharp iHARP https://dev.my.umbc.edu/groups/iharp https://assets2-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xsmall.png?1663786838 https://assets4-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/original.png?1663786838 https://assets4-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xxlarge.png?1663786838 https://assets2-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xlarge.png?1663786838 https://assets3-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/large.png?1663786838 https://assets1-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/medium.png?1663786838 https://assets4-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/small.png?1663786838 https://assets2-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xsmall.png?1663786838 https://assets3-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xxsmall.png?1663786838 iHARP https://assets4-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/771/715219208ee56f56eec1aa3aa1cd705d/xxlarge.jpg?1738010952 https://assets2-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/771/715219208ee56f56eec1aa3aa1cd705d/xlarge.jpg?1738010952 https://assets1-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/771/715219208ee56f56eec1aa3aa1cd705d/large.jpg?1738010952 https://assets3-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/771/715219208ee56f56eec1aa3aa1cd705d/medium.jpg?1738010952 https://assets4-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/771/715219208ee56f56eec1aa3aa1cd705d/small.jpg?1738010952 https://assets4-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/771/715219208ee56f56eec1aa3aa1cd705d/xsmall.jpg?1738010952 https://assets4-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/771/715219208ee56f56eec1aa3aa1cd705d/xxsmall.jpg?1738010952 0 0 true Mon, 27 Jan 2025 15:50:11 -0500 Akila Sampath successfully defends her PhD Proposal Congratulatoins Akila!
Akila Sampath, iHARP Research Assistant, successfully defended her PhD Proposal on Wednesday, December 4, 2024. Join iHARP in congratulating Akila on her successful PhD proposal defense.

Title
Leveraging Physical Principles in Deep Learning to Study Arctic Sea Ice

Committee
Abstract
The Arctic region is undergoing rapid environmental changes, with sea ice loss being a prominent indicator. Accurate prediction of sea ice thickness and extent is crucial for understanding climate change impacts and informing policy decisions. Traditional climate models often struggle to capture the complex interactions between atmospheric, oceanic, and sea ice processes. In recent years, machine learning has emerged as a powerful tool for analyzing large datasets and making accurate predictions. However, machine learning models, while capable of capturing complex patterns, can sometimes produce unrealistic or physically implausible results. To address this limitation, we propose a novel approach that combines the power of machine learning with the rigor of physical principles. By integrating physics-informed techniques into machine learning models, we aim to develop more accurate and reliable predictions of sea ice conditions.

Physics-Informed Machine Learning (PIML) is a novel approach that blends traditional scientific models with the pattern-recognition capabilities of machine learning to improve predictions of sea ice thickness. By leveraging both data-driven and physics-based knowledge, PIML offers more accurate and reliable predictions, even in data-scarce environments. This approach is particularly well-suited for studying complex systems like the Arctic sea ice. Our research introduces Physics-Encoded Neural Networks (PeNNs) to predict snow density. PeNNs embed physical laws directly into the neural network architecture, enabling the estimation of hidden physical properties from observable data. This makes PeNNs highly effective for tracking snow and ice conditions with precision. Additionally, we developed a physics-guided model (PGM) to investigate the causal link between sea ice loss and increased turbulence in the Beaufort Gyre through wind current. By incorporating physical constraints, the PGM ensures that predictions align with known scientific principles, aiding in the understanding of these causal relationships. Our proposed models offer a more comprehensive approach to studying Arctic sea ice. By integrating physics into machine learning, we aim to create tools that are both accurate and interpretable. This research provides valuable insights into Arctic climate change and demonstrates how physics can enhance the capabilities of machine learning models, leading to a deeper understanding of the impacts of sea ice loss.

At the top pictured is Akila Sampath,
Middle Row, left to right:  Dr. Jianwu Wang,  Dr. Vandana Janeja, Dr.Nicole Schlegel.
Bottom Row, left to right: Dr. Donald.k.Perovich, Dr. James Foulds,  Dr. Dr. Houbing Song
]]> Akila Sampath, iHARP Research Assistant, successfully defended her PhD Proposal on Wednesday, December 4, 2024. Join iHARP in congratulating Akila on her successful PhD proposal defense.... https://iharp.umbc.edu/ https://dev.my.umbc.edu/api/v0/pixel/news/146207/guest@my.umbc.edu/04ceb04ee2d9332211c1dd32bcf1f959/api/pixel iharp iHARP https://dev.my.umbc.edu/groups/iharp https://assets2-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xsmall.png?1663786838 https://assets4-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/original.png?1663786838 https://assets4-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xxlarge.png?1663786838 https://assets2-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xlarge.png?1663786838 https://assets3-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/large.png?1663786838 https://assets1-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/medium.png?1663786838 https://assets4-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/small.png?1663786838 https://assets2-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xsmall.png?1663786838 https://assets3-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xxsmall.png?1663786838 iHARP https://assets4-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/207/26c06c4c7b3cea4b2523d05bdb967e05/xxlarge.jpg?1733864981 https://assets3-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/207/26c06c4c7b3cea4b2523d05bdb967e05/xlarge.jpg?1733864981 https://assets3-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/207/26c06c4c7b3cea4b2523d05bdb967e05/large.jpg?1733864981 https://assets1-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/207/26c06c4c7b3cea4b2523d05bdb967e05/medium.jpg?1733864981 https://assets3-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/207/26c06c4c7b3cea4b2523d05bdb967e05/small.jpg?1733864981 https://assets3-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/207/26c06c4c7b3cea4b2523d05bdb967e05/xsmall.jpg?1733864981 https://assets4-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/207/26c06c4c7b3cea4b2523d05bdb967e05/xxsmall.jpg?1733864981 0 0 true Tue, 10 Dec 2024 16:09:48 -0500 iHARP Hackathon Kickoff Event Success

Kicking off the NSF HDR Machine Learning Challenge to Identify Anomalies in Challenges of Societal Importance, iHARP hosted a Hackathon at UMBC on November 22, 2024. Participants of the kickoff Hackathon had the opportunity to engage with three different data sets curated by three different NSF HDR Institutes. Challenge winners will get to showcase their work at a co-located workshop at the AAAI Conference in March 2025.


Thank you to everyone who attended and participated in the Hackathon Kickoff Event and a special thanks to all those who provided support and guidance to participants throughout the event!

]]> Kicking off the NSF HDR Machine Learning Challenge to Identify Anomalies in Challenges of Societal Importance, iHARP hosted a Hackathon at UMBC on November 22, 2024. Participants of the kickoff... http://iharp.umbc.edu https://dev.my.umbc.edu/api/v0/pixel/news/146005/guest@my.umbc.edu/f102aced3f665b9031e7b485c1325fa7/api/pixel iharp iHARP https://dev.my.umbc.edu/groups/iharp https://assets2-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xsmall.png?1663786838 https://assets4-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/original.png?1663786838 https://assets4-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xxlarge.png?1663786838 https://assets2-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xlarge.png?1663786838 https://assets3-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/large.png?1663786838 https://assets1-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/medium.png?1663786838 https://assets4-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/small.png?1663786838 https://assets2-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xsmall.png?1663786838 https://assets3-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xxsmall.png?1663786838 iHARP https://assets1-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/005/c3939fbc1f7e884a7a6d49dc3d027956/xxlarge.jpg?1733169226 https://assets1-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/005/c3939fbc1f7e884a7a6d49dc3d027956/xlarge.jpg?1733169226 https://assets2-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/005/c3939fbc1f7e884a7a6d49dc3d027956/large.jpg?1733169226 https://assets4-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/005/c3939fbc1f7e884a7a6d49dc3d027956/medium.jpg?1733169226 https://assets2-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/005/c3939fbc1f7e884a7a6d49dc3d027956/small.jpg?1733169226 https://assets4-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/005/c3939fbc1f7e884a7a6d49dc3d027956/xsmall.jpg?1733169226 https://assets2-dev.my.umbc.edu/system/shared/thumbnails/news/000/146/005/c3939fbc1f7e884a7a6d49dc3d027956/xxsmall.jpg?1733169226 0 0 true Mon, 02 Dec 2024 14:55:10 -0500 UMBC Doctoral Candidacy Ceremony: iHARP Research Assistants Moving Forward as PhD Candidates Congratulations Tolulope Ale and Maloy Kumar Devanth

Tolulope Ale and Maloy Kumar Devanth have been officially admitted to the Candidacy . On November 1, 2024, Tolulope Ale had the opportunity to participate in the time honored tradition of the UMBC Candidacy Ceremony marking a crucial milestone in the PhD journey. While unable to attend the ceremony, Maloy Kumar Devanth was out of town presenting his PhD research at the SIGSPATIAL 2024.


Please join us in congratulating Tolulope and Maloy on achieving this monumental milestone!

]]> Tolulope Ale and Maloy Kumar Devanth have been officially admitted to the Candidacy . On November 1, 2024, Tolulope Ale had the opportunity to participate in the time honored tradition of the UMBC... http://iharp.umbc.edu https://dev.my.umbc.edu/api/v0/pixel/news/145952/guest@my.umbc.edu/185c4969ad5548c250770dd182d6ec85/api/pixel iharp iHARP https://dev.my.umbc.edu/groups/iharp https://assets2-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xsmall.png?1663786838 https://assets4-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/original.png?1663786838 https://assets4-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xxlarge.png?1663786838 https://assets2-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xlarge.png?1663786838 https://assets3-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/large.png?1663786838 https://assets1-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/medium.png?1663786838 https://assets4-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/small.png?1663786838 https://assets2-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xsmall.png?1663786838 https://assets3-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xxsmall.png?1663786838 iHARP https://assets1-dev.my.umbc.edu/system/shared/thumbnails/news/000/145/952/053d8a2a92bb58b04cc3ae7cc800b26a/xxlarge.jpg?1732728780 https://assets3-dev.my.umbc.edu/system/shared/thumbnails/news/000/145/952/053d8a2a92bb58b04cc3ae7cc800b26a/xlarge.jpg?1732728780 https://assets2-dev.my.umbc.edu/system/shared/thumbnails/news/000/145/952/053d8a2a92bb58b04cc3ae7cc800b26a/large.jpg?1732728780 https://assets1-dev.my.umbc.edu/system/shared/thumbnails/news/000/145/952/053d8a2a92bb58b04cc3ae7cc800b26a/medium.jpg?1732728780 https://assets2-dev.my.umbc.edu/system/shared/thumbnails/news/000/145/952/053d8a2a92bb58b04cc3ae7cc800b26a/small.jpg?1732728780 https://assets3-dev.my.umbc.edu/system/shared/thumbnails/news/000/145/952/053d8a2a92bb58b04cc3ae7cc800b26a/xsmall.jpg?1732728780 https://assets4-dev.my.umbc.edu/system/shared/thumbnails/news/000/145/952/053d8a2a92bb58b04cc3ae7cc800b26a/xxsmall.jpg?1732728780 0 0 true Wed, 27 Nov 2024 12:33:16 -0500 Wed, 27 Nov 2024 12:36:54 -0500 UMBC High Performance Computing (HPC) Boot Camp Expanding iHARP and UMCES Research Capabilities

To expand research capabilities, iHARP hosted a High Performance Computing (HPC)  Bootcamp on November 12, 2024 led by iHARP Research Assistant Sai Vikas Amaraneni with support from DoIT members Roy Prouty, Philip Henry, Beamlak Bekele, and Max Breitmeyer. 


iHARP and UMCES CGC-SCIPE researchers were introduced to UMBC’s HPC resources and gained hands-on training in the Ada High-Performance Computing (HPC) cluster. The bootcamp introduced fundamental concepts in Ada such as BASH basics, and environment setup for efficient research workflows, as well as managing jobs with SLURM. Attendees used a case study involving Patch-CNN for predicting sea ice extent in the Antarctic region (research project being presented at AGU this year), in order to understand the role of HPC in research boththrough single GPU and Multi-GPU training.


We would like to thank Sai Vikas Amaraneni and DoIT members Roy Prouty, Philip Henry, Beamlak Bekele, and Max Breitmeyer for their support and dedication to furthering research capabilities in iHARP and UMCES.


]]> To expand research capabilities, iHARP hosted a High Performance Computing (HPC)  Bootcamp on November 12, 2024 led by iHARP Research Assistant Sai Vikas Amaraneni with support from DoIT members... http://iharp.umbc.edu https://dev.my.umbc.edu/api/v0/pixel/news/145949/guest@my.umbc.edu/198ea1d1551baf9dcde721d4247b5496/api/pixel iharp iHARP https://dev.my.umbc.edu/groups/iharp https://assets2-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xsmall.png?1663786838 https://assets4-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/original.png?1663786838 https://assets4-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xxlarge.png?1663786838 https://assets2-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xlarge.png?1663786838 https://assets3-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/large.png?1663786838 https://assets1-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/medium.png?1663786838 https://assets4-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/small.png?1663786838 https://assets2-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xsmall.png?1663786838 https://assets3-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xxsmall.png?1663786838 iHARP https://assets2-dev.my.umbc.edu/system/shared/thumbnails/news/000/145/949/bd4dc194caf49f7d81c7b5af68314c49/xxlarge.jpg?1732726386 https://assets3-dev.my.umbc.edu/system/shared/thumbnails/news/000/145/949/bd4dc194caf49f7d81c7b5af68314c49/xlarge.jpg?1732726386 https://assets2-dev.my.umbc.edu/system/shared/thumbnails/news/000/145/949/bd4dc194caf49f7d81c7b5af68314c49/large.jpg?1732726386 https://assets2-dev.my.umbc.edu/system/shared/thumbnails/news/000/145/949/bd4dc194caf49f7d81c7b5af68314c49/medium.jpg?1732726386 https://assets4-dev.my.umbc.edu/system/shared/thumbnails/news/000/145/949/bd4dc194caf49f7d81c7b5af68314c49/small.jpg?1732726386 https://assets4-dev.my.umbc.edu/system/shared/thumbnails/news/000/145/949/bd4dc194caf49f7d81c7b5af68314c49/xsmall.jpg?1732726386 https://assets4-dev.my.umbc.edu/system/shared/thumbnails/news/000/145/949/bd4dc194caf49f7d81c7b5af68314c49/xxsmall.jpg?1732726386 1 0 true Wed, 27 Nov 2024 11:55:17 -0500 Maryland State Senator Sarah Elfreth Visits iHARP Interacting & learning about ground breaking research

Maryland State Senator Elfreth visited the iHARP center at UMBC on October 22, 2024. During her visit, she engaged with researchers and learned about their groundbreaking work.


While at the center, Senator Elfreth experienced the immersive Virtual Ice Museum, created through a collaboration between iHARP and the Imaging Research Center (IRC) at UMBC. This Virtual Ice Museum allows audiences to explore climate change research in a new immersive and interactive format through virtual reality (VR).


We would like to thank the iHARP researchers who shared their work, as well as Ryan Zuber, the IRC Technical Director, for demonstrating the Virtual Ice Museum. We especially appreciate Senator Elfreth for taking the time from her busy schedule to meet with iHARP members and collaborators. ]]> Maryland State Senator Elfreth visited the iHARP center at UMBC on October 22, 2024. During her visit, she engaged with researchers and learned about their groundbreaking work. While at the... https://iharp.umbc.edu/ https://dev.my.umbc.edu/api/v0/pixel/news/145639/guest@my.umbc.edu/d14895e28a6ca4b446b21e239667ba78/api/pixel iharp iHARP https://dev.my.umbc.edu/groups/iharp https://assets2-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xsmall.png?1663786838 https://assets4-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/original.png?1663786838 https://assets4-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xxlarge.png?1663786838 https://assets2-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xlarge.png?1663786838 https://assets3-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/large.png?1663786838 https://assets1-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/medium.png?1663786838 https://assets4-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/small.png?1663786838 https://assets2-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xsmall.png?1663786838 https://assets3-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xxsmall.png?1663786838 iHARP https://assets1-dev.my.umbc.edu/system/shared/thumbnails/news/000/145/639/2720a5a68d93c81033704613e28e1a5f/xxlarge.jpg?1731610229 https://assets3-dev.my.umbc.edu/system/shared/thumbnails/news/000/145/639/2720a5a68d93c81033704613e28e1a5f/xlarge.jpg?1731610229 https://assets1-dev.my.umbc.edu/system/shared/thumbnails/news/000/145/639/2720a5a68d93c81033704613e28e1a5f/large.jpg?1731610229 https://assets4-dev.my.umbc.edu/system/shared/thumbnails/news/000/145/639/2720a5a68d93c81033704613e28e1a5f/medium.jpg?1731610229 https://assets2-dev.my.umbc.edu/system/shared/thumbnails/news/000/145/639/2720a5a68d93c81033704613e28e1a5f/small.jpg?1731610229 https://assets4-dev.my.umbc.edu/system/shared/thumbnails/news/000/145/639/2720a5a68d93c81033704613e28e1a5f/xsmall.jpg?1731610229 https://assets1-dev.my.umbc.edu/system/shared/thumbnails/news/000/145/639/2720a5a68d93c81033704613e28e1a5f/xxsmall.jpg?1731610229 0 0 true Thu, 14 Nov 2024 13:54:51 -0500 Hiring: Academic Program Specialist Apply today!

The University of Maryland, Baltimore County (UMBC) is seeking an Academic Program Specialist for the iHARP Center. Reporting to the Operations and Communications Coordinator, the incumbent will plan, develop and coordinate events and workshops, assist the Director and Executive Director in research coordination efforts across multiple grants under iHARP, as well as provide administrative support to iHARP and supplemental grants.


In this position will work closely with iHARP members across multiple institutions, UMBC campus partners as well as various stakeholders. The ideal candidate will be detail-oriented, self-motivated and work independently as well as a part of a larger team.


For best consideration, submit a cover letter, resume and contact information for three professional references, (applications will be accepted until the position is filled) to: https://listings.umbc.edu/cw/en-us/job/494758/academic-program-specialist

The Academic Program Specialist role is a full-time (40 hours),  non-exempt staff position that is grant funded.

]]> The University of Maryland, Baltimore County (UMBC) is seeking an Academic Program Specialist for the iHARP Center. Reporting to the Operations and Communications Coordinator, the incumbent will... http://iharp.umbc.edu https://dev.my.umbc.edu/api/v0/pixel/news/145588/guest@my.umbc.edu/533f5d6f81cb69e815bbaf566fdce86c/api/pixel iharp iHARP https://dev.my.umbc.edu/groups/iharp https://assets2-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xsmall.png?1663786838 https://assets4-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/original.png?1663786838 https://assets4-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xxlarge.png?1663786838 https://assets2-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xlarge.png?1663786838 https://assets3-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/large.png?1663786838 https://assets1-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/medium.png?1663786838 https://assets4-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/small.png?1663786838 https://assets2-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xsmall.png?1663786838 https://assets3-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xxsmall.png?1663786838 iHARP https://assets2-dev.my.umbc.edu/system/shared/thumbnails/news/000/145/588/7d040d162aac8dd5c2b097ae43039e65/xxlarge.jpg?1731509913 https://assets2-dev.my.umbc.edu/system/shared/thumbnails/news/000/145/588/7d040d162aac8dd5c2b097ae43039e65/xlarge.jpg?1731509913 https://assets2-dev.my.umbc.edu/system/shared/thumbnails/news/000/145/588/7d040d162aac8dd5c2b097ae43039e65/large.jpg?1731509913 https://assets3-dev.my.umbc.edu/system/shared/thumbnails/news/000/145/588/7d040d162aac8dd5c2b097ae43039e65/medium.jpg?1731509913 https://assets1-dev.my.umbc.edu/system/shared/thumbnails/news/000/145/588/7d040d162aac8dd5c2b097ae43039e65/small.jpg?1731509913 https://assets3-dev.my.umbc.edu/system/shared/thumbnails/news/000/145/588/7d040d162aac8dd5c2b097ae43039e65/xsmall.jpg?1731509913 https://assets3-dev.my.umbc.edu/system/shared/thumbnails/news/000/145/588/7d040d162aac8dd5c2b097ae43039e65/xxsmall.jpg?1731509913 0 0 false Wed, 13 Nov 2024 10:06:40 -0500 Dr. Bayu Adhi Tama at USM Postdoctoral Research Symposium Sharing research and expanding networks

Dr. Bayu Adhi Tama attended the 1st USM Postdoctoral Research Symposium on Friday, September 30, 2024, at the University of Maryland, College Park. Dr. Tama presented a poster based on his research project Mapping subglacial bed topography using surface observations and machine learning:

challenges and opportunities. During the symposium, he had the opportunity to network with other Maryland Postdoctoral researchers. 



]]> Dr. Bayu Adhi Tama attended the 1st USM Postdoctoral Research Symposium on Friday, September 30, 2024, at the University of Maryland, College Park. Dr. Tama presented a poster based on his... http://iharp.umbc.edu https://dev.my.umbc.edu/api/v0/pixel/news/144375/guest@my.umbc.edu/1a38800990a1188c852d4200a56dc675/api/pixel iharp iHARP https://dev.my.umbc.edu/groups/iharp https://assets2-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xsmall.png?1663786838 https://assets4-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/original.png?1663786838 https://assets4-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xxlarge.png?1663786838 https://assets2-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xlarge.png?1663786838 https://assets3-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/large.png?1663786838 https://assets1-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/medium.png?1663786838 https://assets4-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/small.png?1663786838 https://assets2-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xsmall.png?1663786838 https://assets3-dev.my.umbc.edu/system/shared/avatars/groups/000/002/011/5a4b2df3e2c5e51353edce5eaef18479/xxsmall.png?1663786838 iHARP https://assets1-dev.my.umbc.edu/system/shared/thumbnails/news/000/144/375/023040934abf55f62ac1e9bf7c34f4cf/xxlarge.jpg?1727805439 https://assets4-dev.my.umbc.edu/system/shared/thumbnails/news/000/144/375/023040934abf55f62ac1e9bf7c34f4cf/xlarge.jpg?1727805439 https://assets1-dev.my.umbc.edu/system/shared/thumbnails/news/000/144/375/023040934abf55f62ac1e9bf7c34f4cf/large.jpg?1727805439 https://assets3-dev.my.umbc.edu/system/shared/thumbnails/news/000/144/375/023040934abf55f62ac1e9bf7c34f4cf/medium.jpg?1727805439 https://assets2-dev.my.umbc.edu/system/shared/thumbnails/news/000/144/375/023040934abf55f62ac1e9bf7c34f4cf/small.jpg?1727805439 https://assets2-dev.my.umbc.edu/system/shared/thumbnails/news/000/144/375/023040934abf55f62ac1e9bf7c34f4cf/xsmall.jpg?1727805439 https://assets2-dev.my.umbc.edu/system/shared/thumbnails/news/000/144/375/023040934abf55f62ac1e9bf7c34f4cf/xxsmall.jpg?1727805439 0 0 true Tue, 01 Oct 2024 13:57:39 -0400