Congratulations to Bayu Tama, PhD
Top 2% Scientist who's work is cited
Congratulations to Bayu Adhi Tama, Ph.D.
for being among the top 2% of scientist in the world who's work is
continually cited. We are excited and honored to have Bayu apart of the
iHARP Community!
]]>
Congratulations to Bayu Adhi Tama, Ph.D. for being among the top 2% of scientist in the world who's work is continually cited. We are excited and honored to have Bayu apart of the iHARP...
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Mon, 21 Nov 2022 10:24:19 -0500
Mon, 21 Nov 2022 11:19:58 -0500
Monitoring Ice Sheets with UAV-borne Ice-penetrating Radar..
Stanford HAI Event - Wedensday, October 26
Full Title:
Monitoring Ice Sheets with UAV-borne Ice-penetrating Radar Systems and Physics-informed Machine Learning
Date: Wednesday, October 26
Time: 10:00 a.m.
-
11:00 a.m.
PDT
Abstract:
The Antarctic Ice Sheet will play a growing role in sea level rise over
the next century, but models of sea level contributions from the vast
ice sheet carry far larger uncertainty estimates than other major
contributing sources. A number of factors contribute to this
uncertainty, all of which can be traced back to a sparsity of data. The
Antarctic Ice Sheet is nearly 50% larger than the United States in area
and holds ice equivalent to over 60 meters of global sea level rise.
Satellite observations have turned the surfaces of Earth’s ice sheets
into data-rich environments, yet the subsurface environments remain
sparsely observed.
Multiple potential positive-feedback processes have been proposed that
could dramatically alter our predictions of the future of the ice sheet.
These hypotheses are difficult to test because the processes would
likely not have occurred in the relatively short direct span of direct
observations available to us, but, in many cases, we also lack the
observational infrastructure to identify these processes beginning
today. Even well-established processes still carry large uncertainties
in how they will impact the ice sheet due to the poor spatial and
temporal resolution of data available.
Our group explores this problem from two fronts: using robotics to
enable more widespread data collection and leveraging data-based
approaches to maximize the value of data collected. Uncrewed aerial
vehicles (UAVs) carrying ice-penetrating radar instruments hold the
potential to dramatically expand sub-surface data collection by reducing
the cost, logistical complexity, and safety risks associated with
current approaches. At the same time, the scale of the problem is so
vast that it is critical to consider how we can optimize the deployment
of resources to maximize the value of the collected data. This requires a
move towards data-driven approaches to understanding the behavior of
the ice sheet
About
"The University of Pennsylvania Graduate School of Education is thrilled
to host an entirely virtual NASA Space Apps Challenge local event this
fall. We will virtually convene creative thinkers and problem-solvers
from here in Philadelphia and across the globe to explore complex,
significant, and compelling problems."
What to Expect
Throughout
your NASA International Space Apps Challenge experience with Penn GSE,
you'll have the opportunity to learn directly from members of the Penn
community about core ideas and strategies related to collaborative
problem-solving, team effectiveness, authentic learning, and
project-based learning.
To Join
]]>
Event Website: https://2022.spaceappschallenge.org/locations/philadelphia-penn-gse/welcome About "The University of Pennsylvania Graduate School of Education is thrilled to host an...
https://2022.spaceappschallenge.org/locations/philadelphia-penn-gse/event
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Thu, 29 Sep 2022 08:13:06 -0400
UMBC & Unviersity of West Indies Five Island Campus
Climate Chanllegen 2nd Place!
A team representing the University of the West Indies Five Islands Campus and the University of Maryland, Baltimore County, USA captured the second place. The application assessed tourism sustainability in the Eastern Caribbean from Polar Region Ice Melting to Sea Level Change to Rainfall.
]]>
A team representing the University of the West Indies Five Islands Campus and the University of Maryland, Baltimore County, USA captured the second place. The application assessed tourism...
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Tue, 20 Sep 2022 17:26:05 -0400
Tue, 20 Sep 2022 17:26:12 -0400
ISGEO & iHARP Present ISEGEO-22 Workshop
Workshop on Model-Based Reasoning
ISGEO-22: August 15 - 19, 2022
THANK YOU to everyone who made this event a huge success!
Final Presentation Video:
To watch the final presentions of projects that were created and worked on during the workshop, please use this link to navigate to the video:
Overview:
IS-GEO and iHARP are pleased to announce a virtual workshop on
Model-based Reasoning. Invited expert, Dr. Deana Pennington from the
University of Texas at El Paso (UTEP) brings prior expertise in
evaluating social learning and model-based reasoning together with clear
guidance for successful transdisciplinary team building.
Model-based reasoning uses mental models, simulation models, and
everything in between to understand how researchers can collaboratively
integrate their subject matter expertise of problems and generate
combined knowledge from their different perspectives.
To learn more about the ISGEO-22 Workshop, please use this link to navigate to the ISEGEO-22 Github page:
https://is-geo.github.io/ISGEO-22/
Please keep an out for followup workshops and other related events!
Dr. Vandana Janeja, Director of iHARP and Chair of Information systems, and et al. presented at the 2022 CRA Conference.
Presentation Abstract:
Climate change has been declared as the defining crisis of our time
and concrete actions are needed now. Many communities have started major
initiatives to address climate change. For example, the Biden
administration has made it a central priority for all federal agencies
resulting in initiatives for reducing greenhouse gases (GHG) emissions
(e.g., electric vehicles), absorbing GHG (e.g., forests), increasing
resilience (sea level rise, forest fires, extreme cold/hot weather),
etc. This panel will bring together thought leaders in academia,
industry and government to explore climate-smart computing opportunities
by addressing questions such as the following:
- What is climate-smart computing? What may it help understand,
mitigate, and adapt to climate change? How may we reduce computing’s
carbon footprint?
- What are computing research success stories in this area?
- What are major computing opportunities in this area?
- How may new computing researchers get involved?
- What are key research infrastructures (e.g., datasets, cyberinfrastructure, funding)?
- Is there a need for computing research community action? If so, recommend
To view the presentation slides, please use the following link:
Uzma Hasan, a 1st Year PhD student in the IS department and iHARP graduate research assistant, has presented
her research paper titled "KCRL: A Prior Knowledge based Causal
Discovery Framework with Reinforcement Learning" at the Machine Learning
for Healthcare (MLHC) conference, Durham, NC on 5th August, 2022
To read the publication, please navigate to it by using this link:
]]>
Uzma Hasan, a 1st Year PhD student in the IS department and iHARP graduate research assistant, has presented her research paper titled "KCRL: A Prior Knowledge based Causal Discovery Framework...
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Tue, 20 Sep 2022 11:17:41 -0400
Benchmarking Probabilisitc Machine Learning Models for....
iHARP Funded Research
Benchmarking Probabilistic Machine Learning Models for
Arctic Sea Ice.
Authored by:
Sahara Ali,
Seraj al Mahmud Mostafa, Xingyan Li, Sara Khanjani, Jianwu Wang, James Foulds,
Vandana Janeja.
iHARP members,
and others, recently had their paper accepted by IEEE as a part of the 2022 International
Geoscience and Remote Sensing Symposium (IGARSS). Their work explores the use of
AI in tackling climate change by utilizing machine learning. The paper will
become publicly available on July 1, 2023.
A sneak preview
of the paper can be found by following this link:
https://drive.google.com/file/d/1oXotdE8TDDAu0jzs0VrEb6R5pr4xE8yt/view
Join us in congratulating the authors on their hard work and getting their paper accepted by IGARSS.
]]>
Benchmarking Probabilistic Machine Learning Models for Arctic Sea Ice. Authored by: Sahara Ali, Seraj al Mahmud Mostafa, Xingyan Li, Sara Khanjani, Jianwu Wang, James Foulds, Vandana Janeja....
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Mon, 19 Sep 2022 13:59:39 -0400
Earth Science Information Partners (ESIP) Fellowship
Application Deadline: Ocober 7, 2022
Earth Science Information Partners (ESIP)
is a collaboration based platform sponsored by NASA, NOAA and USGS. It
is a community of partner organizations and volunteers who work together
to meet environmental data challenges and look for opportunities to
expand, improve, and innovate across Earth science disciplines.
Every year ESIP awards 8 Community Fellowships
to graduate students majoring in Earth, Environmental and/or Computer
sciences. This fellowship provides early career researchers a chance to
work closely with professionals in an interdisciplinary, cross-sector
group by working with one of the ESIP Collaboration Areas. Community
Fellows become engaged in ESIP collaboration areas as rapporteurs,
documenting group activities on monthly telecons and at ESIP’s bi-annual
meetings.
The deadline to apply for the upcoming cycle is October 7th, 2022.
Sahara Ali, PhD Student and fellow, is available to answer any questions or concerns of students who are interested in the fellowship. To contact Sahara, please email her at sali9@umbc.edu
More details on the fellowship can be found here.
]]>
Earth Science Information Partners (ESIP) is a collaboration based platform sponsored by NASA, NOAA and USGS. It is a community of partner organizations and volunteers who work together to meet...
https://www.esipfed.org/get-involved/student-opportunities
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Tue, 13 Sep 2022 12:47:30 -0400
Tue, 13 Sep 2022 12:47:57 -0400
iHARP featured in UMBC News Article
Data Science Meeting Climate Science to Lead Changes
Some of the UMBC iHARP team. (Marlayna Demond '11/UMBC)
Snippet of the UMBC Article:
Tens of millions of people live in areas that are at risk for
flooding due to climate change, sea level rise, and melting of glaciers.
UMBC’s Vandana Janeja is leading a team of researchers
using data science, machine learning, artificial intelligence (AI), and
polar science to analyze enormous volumes of climate data, and Arctic
and Antarctic observations in ways that could help populations prepare
for and respond to these risks.
]]>
Some of the UMBC iHARP team. (Marlayna Demond '11/UMBC) Snippet of the UMBC Article: Tens of millions of people live in areas that are at risk for flooding due to climate change, sea...
https://umbc.edu/stories/umbc-to-lead-climate-focused-nsf-data-science-institute/
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iHARP
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iHARP
2
0
true
Fri, 02 Sep 2022 12:21:38 -0400
Tue, 20 Sep 2022 10:49:13 -0400
