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X-ORIGINAL-URL:https://tamids.tamu.edu
X-WR-CALDESC:Events for TAMIDS
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DTSTART;TZID=America/Chicago:20260410T100000
DTEND;TZID=America/Chicago:20260410T120000
DTSTAMP:20260407T185732
CREATED:20260303T202400Z
LAST-MODIFIED:20260303T205250Z
UID:19799-1775815200-1775822400@tamids.tamu.edu
SUMMARY:Supervised Text Classification Workshop
DESCRIPTION:Participants will learn how to train models to categorize texts based on labeled examples and understand evaluation metrics. It will be one hour of theory and explanation of the concepts\, and the last hour will be hands-on practice in Python. Key topics include: Classification algorithms like Naive Bayes and Logistic Regression\, Evaluation metrics such as accuracy\, precision\, recall\, F1-score\, and confusion matrices\,  supervised learning paradigm and workflow\, applications in social science research (sentiment analysis\, content categorization\, frame detection)\, training data preparation and train-test splitting\, feature extraction with TF-IDF and bag-of-words\, and much more!
URL:https://tamids.tamu.edu/2026/02/13/text-mining-workshop-series/
CATEGORIES:TAMIDS Event,Workshop
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20260413T140000
DTEND;TZID=America/Chicago:20260413T150000
DTSTAMP:20260407T185732
CREATED:20260313T191141Z
LAST-MODIFIED:20260407T181122Z
UID:19946-1776088800-1776092400@tamids.tamu.edu
SUMMARY:Seminar Series: Dr. Leila Character
DESCRIPTION:Dr. Leila Character is an Assistant Professor in the Department of Geography at Texas A&M University and a geospatial scientist specializing in remote sensing and machine learning. Her research focuses on building computational approaches that solve complex environmental challenges by enabling large-scale mapping and object detection across terrestrial and underwater environments. She develops new methods that combine diverse types of remotely sensed data—such as hyperspectral\, multispectral\, lidar\, radar\, sonar\, and magnetometer—to automate feature extraction and create novel geospatial layers that extend far beyond what manual analysis can achieve.  \n\n\n\nDr. Character’s work centers on three themes: improving machine learning model generalizability and methodological transferability\, refining imagery preprocessing and data annotation\, and advancing data collection strategies. Her projects include many application areas\, from archaeology to defense. \n\n\n\n\nLocation: Blocker 220 and Zoom \n\n\n\nZoom ID: 974 968 84861Passcode: 923446 \n\n\n\nExploring the Deep: Machine Learning and Remote Sensing for Targeted Underwater Exploration and Mapping\n\n\n\nTraditional methods for locating and mapping underwater targets\, such as ship and aircraft wrecks\, are often expensive and inefficient. Integrating deep learning with remotely sensed data transforms this process\, allowing large seafloor areas to be searched efficiently. Although terrestrial target detection is advancing rapidly\, underwater applications remain limited due to a lack of training data. This work addresses that gap through two successful projects: shipwreck detection using publicly available multibeam sonar and aircraft wreck detection using sidescan sonar data. The methodology proved highly effective—field testing of the aircraft detection model identified three of four new aircraft targets in survey data. \n\n\n\nBuilding on this foundation\, new research focuses on fusing very high-resolution 3D bathymetric data with sidescan sonar for deep learning–based underwater target detection under diverse environmental and optical conditions. Detected targets will be ranked using a forest-based model that incorporates morphometric characteristics and compared to human review. Ultimately\, this multi-modal approach will enhance the efficiency and accuracy of underwater object detection\, enabling broader seafloor characterization and more targeted field validation while reducing operational costs and improving safety for marine exploration. \n\n\n\n\n\n\n\nSeminar Flyer413Download
URL:https://tamids.tamu.edu/event/seminar-series-dr-leila-character/
CATEGORIES:TAMIDS Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20260414T143000
DTEND;TZID=America/Chicago:20260414T153000
DTSTAMP:20260407T185732
CREATED:20260314T152934Z
LAST-MODIFIED:20260402T161008Z
UID:19928-1776177000-1776180600@tamids.tamu.edu
SUMMARY:Generative AI Foundations Workshop (Intermediate Level)
DESCRIPTION:This intermediate-level workshop will focus on practical applications\, emphasizing automation\, prompt engineering\, and how to utilize GenAI in research. It will be held virtually and hosted by TAMIDS Senior Ambassador Zavier Ndum. Register at the link below! \n\n\n\n\nRegister here.
URL:https://tamids.tamu.edu/event/generatve-ai-foundations-for-beginners/
CATEGORIES:Ambassador Event,TAMIDS Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20260417T083000
DTEND;TZID=America/Chicago:20260417T170000
DTSTAMP:20260407T185732
CREATED:20260317T170935Z
LAST-MODIFIED:20260406T193606Z
UID:19826-1776414600-1776445200@tamids.tamu.edu
SUMMARY:Texas Digital Twin Symposium
DESCRIPTION:Overview\n\n\n\nThe Texas Digital Twin Symposium brings together researchers\, students\, and industry partners from across Texas to advance the growing digital twin research ecosystem\, with a strong focus on data science–enabled methods and real-world applications. The event is designed to spark new cross-disciplinary collaborations spanning engineering\, statistics\, computer science\, and applied mathematics. Through technical sessions\, posters\, and breakout discussions\, participants explore emerging challenges and opportunities in digital twin technologies and highlight innovative student work. This event will be held in the Joe C. Richardson Petroleum Engineering Building in Room 910. \n\n\n\n\n\n\n\nPresenters\n\n\n\n\nSatish Bukkapatnam\, Texas A&M Department of Industrial & Systems Engineering\n\n\n\nIan Fialho\, Executive Senior Director\, Boeing\n\n\n\nMichael Grieves\, Executive Director\, Digital Twin Institute\n\n\n\nOmar Ghattas\, Director\, University of Texas Oden Institute\n\n\n\nDev Niyogi\, Professor\, University of Texas at Austin\n\n\n\nLisha White\, Mechanical Engineer\, NIST\n\n\n\nRuda Zhang\, Assistant Professor\, University of Houston Cullen College of Engineering\n\n\n\n\n\n\n\n\nPoster Session\n\n\n\nWe welcome posters that highlight innovations for digital twin systems with a data science component\, including theory\, methods\, and applications. \n\n\n\n\nPoster Submission Form\n\n\n\n\nPoster Abstract Deadline: March 30 \n\n\n\n\n\n\n\nRegistration\n\n\n\nThe symposium is open to all students\, researchers\, and faculty at Texas A&M University. There is a limit of 80 participants. Once we reach capacity\, new registrations will be added to the waiting list. If you cannot attend in person\, please contact TAMIDS@tamu.edu so we can notify waitlisted attendees.  \n\n\n\n\nRegistration Form\n\n\n\n\nRegistration Deadline: April 8 \n\n\n\n\n\n\n\nCommittee\n\n\n\n\nRui Tuo [Conference Chair]\, Associate Professor\, Industrial & Systems Engineering\n\n\n\nDouglas Allaire\, Associate Professor\, Mechanical Engineering\n\n\n\nAshrant Aryal\, Assistant Professor\, Construction Science\n\n\n\nRaktim Bhattacharya\, Professor\, Aerospace Engineering\n\n\n\nDrew Casey\, Associate Director\, Texas A&M Institute of Data Science\n\n\n\nRudy Geelen\, Assistant Professor\, Aerospace Engineering\n\n\n\nEduardo Gildin\, Associate Department Head of Graduate Studies\, Petroleum Engineering\n\n\n\nJian Tao\, Assistant Professor\, Visual Computing & Computational Media\n\n\n\n\nIf you have any questions about this event\, please contact TAMIDS@tamu.edu.  \n\n\n\n\n\n\n\nSupported by\n\n\n\n\nTexas A&M Institute of Data Science\n\n\n\nTexas A&M Energy Institute
URL:https://tamids.tamu.edu/event/texas-digital-twin-symposium/
CATEGORIES:TAMIDS Event,Workshop
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20260424T100000
DTEND;TZID=America/Chicago:20260424T120000
DTSTAMP:20260407T185732
CREATED:20260324T192800Z
LAST-MODIFIED:20260402T160659Z
UID:19801-1777024800-1777032000@tamids.tamu.edu
SUMMARY:Topic Modeling & Discovery Workshop
DESCRIPTION:Participants will learn how to identify latent themes in large text collections using unsupervised machine learning and how to interpret and validate these findings. It will be one hour of theory and explanation of the concepts\, and the last hour will be hands-on practice in Python. Key topics include: Unsupervised learning\, topic modeling concepts\, Latent Dirichlet Allocation (LDA) intuition and implementation\, choosing the number of topics (K)\, using coherence metrics and interpretability\, systematic topic interpretation for words\, documents\, and labels\, evaluating topic quality and distinctiveness with Document-level and corpus-level topic analysis recall\, F1-score\, and confusion matrices\, and much more!
URL:https://tamids.tamu.edu/2026/02/13/text-mining-workshop-series/
CATEGORIES:TAMIDS Event,Workshop
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