From awd at cs.cmu.edu  Tue Jul 11 13:37:23 2023
From: awd at cs.cmu.edu (Artur Dubrawski)
Date: Tue, 11 Jul 2023 13:37:23 -0400
Subject: TOMORROW: Thesis Defense - July 12, 2023 - Sebastian Caldas -
 Collaborative learning by leveraging siloed data
In-Reply-To: <CAJvAoyuMSYsy3U4Md6QKc+DVL=R_HHQZ95TD_9jDuc5pt1hnBg@mail.gmail.com>
References: <55ab2165-1689-4881-38d4-7420a04f00e0@andrew.cmu.edu>
 <CAJvAoyuMSYsy3U4Md6QKc+DVL=R_HHQZ95TD_9jDuc5pt1hnBg@mail.gmail.com>
Message-ID: <CAJvAoys58B9kB3g4aowKgc6fHAd=xd8WSqQWkZfJhoUiQANFXA@mail.gmail.com>

On Tue, Jun 27, 2023 at 6:16?PM Artur Dubrawski <awd at cs.cmu.edu> wrote:

> This will be fun!
>
> Please mark your calendars and join to cheer for Sebastian while enjoying
> a presentation of exceptional quality.
>
> Cheers
> Artur
>
> ---------- Forwarded message ---------
> From: Diane Stidle <stidle at andrew.cmu.edu>
> Date: Tue, Jun 27, 2023 at 4:24?PM
> Subject: Thesis Defense - July 12, 2023 - Sebastian Caldas - Collaborative
> learning by leveraging siloed data
> To: ml-seminar at cs.cmu.edu <ML-SEMINAR at cs.cmu.edu>, <cler at pitt.edu>, <
> martin.jaggi at epfl.ch>
>
>
> *Thesis Defense*
>
> Date: July 12, 2023
> Time: 4:00pm (EDT)
> Place: GHC 8102 & Remote
> PhD Candidate: Sebastian Caldas
>
> *Title: **Collaborative learning by leveraging siloed data*
> Abstract:
> Regulations can often limit stakeholders? modeling capabilities by
> preventing data sharing. For example, in order to protect patient privacy,
> clinical centers may be unable to share their data and thus lack
> representative records to learn about a rare condition. To address this
> challenge, previous work in machine learning has shown that these
> stakeholders benefit from training models in a collaborative fashion,
> improving their predictive performance. However, as we start training these
> collaborative models in real-world settings, and in order to be truly
> useful, they need to provide utility along dimensions beyond predictive
> performance. In this thesis, we propose methods and algorithms to improve
> collaborative models that leverage siloed data along three dimensions. In
> the first part, we propose methods to reduce the communication footprint of
> models learned by mobile devices cooperating over edge networks, allowing
> for higher capacity models to be trained. Then, in the second part, we
> introduce an algorithm that provides explanations about predictions of
> models trained across clinical centers, thus improving their clinical
> utility. Finally, in the third part, we address the need to encode expert
> supervision into collaborative models trained using on-device data,
> increasing the class of problems we can tackle in these scenarios.
>
> *Thesis Committee:*
> Artur Dubrawski (Chair)
> Virginia Smith
> Gilles Clermont (University of Pittsburgh) cler at pitt.edu
> Martin Jaggi (EPFL) martin.jaggi at epfl.ch
>
> *Link to the draft document: *
> https://drive.google.com/file/d/1xTPUERARdnQnMSNCnu2VXrWk1YFKQOqp/view?usp=sharing
>
>
> *Zoom meeting link:*
> https://cmu.zoom.us/j/92902855666?pwd=a3l4V3ppQlp1K252K2doSjNTRlhPdz09
> <https://www.google.com/url?q=https://cmu.zoom.us/j/92902855666?pwd%3Da3l4V3ppQlp1K252K2doSjNTRlhPdz09&sa=D&source=calendar&ust=1688311717182551&usg=AOvVaw0fNQndryXEeSLoOO-ZhNfp>
>
> --
> Diane Stidle
> PhD Program Manager
> Machine Learning Department
> Carnegie Mellon Universitystidle at andrew.cmu.edu
>
>
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From awd at cs.cmu.edu  Tue Jul 18 06:09:04 2023
From: awd at cs.cmu.edu (Artur Dubrawski)
Date: Tue, 18 Jul 2023 06:09:04 -0400
Subject: Fwd: [CfP] ML4H 2023 Call for Participation - Machine Learning for
 Health Symposium
In-Reply-To: <117265028240952320.0.v2@titan.email>
References: <117265028240952320.0.v2@titan.email>
Message-ID: <CAJvAoyux3WqxuWCO_WxGUzBYSO=KCbqhcOrHabHLJRfsVqW8Fw@mail.gmail.com>

For everyone's awareness, this is a worthwhile venue that is the
continuation of what we used to call internally "Ina's Workshop" - a highly
successful event originally embedded in the NeurIPS program and started by
our former phd student Madalina Fiterau - more recent organizers of which
made a decision a couple of years ago - rather suboptimal in my mind - to
decapsulate from NeurIPS.  They still colocate with NeurIPS but also need
to compete now for attention with one or two similar workshops that have
been started within NeurIPS in the vacuum created.

Anyhow, please consider it as a possible venue for your new papers touching
the intersection of AI/ML and healthcare. They consider both well
established work and work-in-progress. Submissions are due in early
September.

Cheers,
Artur

---------- Forwarded message ---------
From: ML4H <info at ml4h.cc>
Date: Tue, Jul 18, 2023, 4:37 AM
Subject: [CfP] ML4H 2023 Call for Participation - Machine Learning for
Health Symposium
To: awd at andrew.cmu.edu <awd at andrew.cmu.edu>


Hi Dr. Artur Dubrawski,

I hope you're doing well and having a great summer! We were wondering if
you can share the following Call for Participation (CfP) to your group and
other interested researchers at your institution.

Thank you,
Van Truong, Vishwali Mhasawade, Payal Chandak
Communications Chairs, ML4H 2023


------------------------ Call for Participation Below ----------------------

The 2023 Machine Learning for Health Symposium (ML4H) invites submissions
describing innovative research that lies in the broad purview of Machine
Learning for Health. Authors are invited to submit work on relevant
problems in a variety of health-related disciplines, including healthcare,
biomedicine, and public health. For full details, refer to the online Call
for Participation:
https://ml4health.github.io/2023/call_for_participation.html

This year, ML4H 2023 will accept submissions for two distinct tracks: the
Proceedings track for formal archival publications and the non-archival
Findings track. Submissions are due on September 7th, 11:59 PM AoE in the
form of anonymized PDF files. All submissions for ML4H 2023 will be managed
through the OpenReview system (
https://openreview.net/group?id=ML4H/2023/Symposium).

Similar to last year, we have a full author response period and reviewer
discussion period to ensure proper feedback on the work. ML4H 2023 will
feature two thematic sessions: Global Health + Equity and Generative AI for
Health. While we especially encourage submissions relevant to this year?s
themes, any submission that falls under the purview of machine learning for
health is welcome. Submissions will be considered for awards, including
Best Proceedings Paper, Best Findings Paper, Best Thematic Paper, and Best
Newcomer Paper.

In response to the growing ML4H community, ML4H has transitioned into a
standalone symposium rather than a NeurIPS-affiliated workshop. This event
represents a continuation of prior ML4H workshops/symposiums (2016
<https://nips.cc/Conferences/2016/Schedule?showEvent=6209>, 2017
<https://ml4health.github.io/2017/>, 2018
<https://ml4health.github.io/2018/>, 2019
<https://ml4health.github.io/2019/>, 2020
<https://ml4health.github.io/2020/>, 2021
<https://ml4health.github.io/2021/>, 2022
<https://ml4health.github.io/2022/>). This year, ML4H will remain
co-located with NeurIPS, taking place in New Orleans, USA, on Sunday, Dec
10, 2023.

Important Dates

Aug 1: Submission site opens

Sep 7 AoE: Submission deadline

Oct 13: Author response period starts

Oct 18: Author response period ends

Nov 1: Decisions released

Nov 15: Camera-ready deadline

Dec 10: In-person event

Mentorship Opportunities

This year, we are offering three mentorship programs at ML4H: Submission
Mentorship, Reviewer Mentorship, and Career Mentorship. Please consider
signing-up as a mentor or mentee!

The Author Mentorship Program pairs less experienced authors with senior
researchers to provide feedback on their paper submission, with the overall
goal of improving submission quality and fostering future collaboration.

Program details: https://ml4health.github.io/2023/author_mentorship.html

Mentee sign-up: https://forms.gle/RzR9yntvUjpV5Hgc7

Mentor sign-up: https://forms.gle/fh8j1Eq875H53jHD8

Deadline: Rolling


The Reviewer Mentorship Program aims to train junior reviewers, foster new
connections and relationships in the ML4H community, and ultimately improve
the quality of the review process. More details will be made available at:
https://ml4health.github.io/2023/reviewer_mentorship.html.


The Career Mentorship Program focuses advice on career-related topics, from
developing a research plan to work-life balance. More details will be made
available at: https://ml4health.github.io/2023/career_mentorship.html


Contact Us
Please direct questions to: info at ml4h.cc and follow us on Twitter at
@symposiumml4h <https://twitter.com/symposiumml4h>.
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From predragp at andrew.cmu.edu  Wed Jul 26 14:20:04 2023
From: predragp at andrew.cmu.edu (Predrag Punosevac)
Date: Wed, 26 Jul 2023 14:20:04 -0400
Subject: The Auton Lab Zenbleed response
Message-ID: <CAEFFt-HJoKOnvY+iB5eB6iiMdb_bSU9JcNF7y5WuDfP6JKCUSg@mail.gmail.com>

Dear Autonians,

Some of you might have heard of the latest security nightmare called
Zenbleed which affects AMD products discovered by the Google security team.
Those of you who are curious might read more about it here


https://lock.cmpxchg8b.com/zenbleed.html


Currently all Auton Lab parameter firewalls and network related servers run
OpenBSD on the Intel hardware and are not affected with these bugs.
OpenBSD does not use the AVX instructions to the same extent that Linux and
Microsoft do, so this is not as important. However, attacks built upon
primitives are getting better and they will soon pose major security
threats. Consequently, I patched today's OpenBSD machines and updated
bootblocks accordingly. This action did require reboot.


Most other OSs, unlike OpenBSD, are relying on vendor support. They are
still affected. After denying the problem AMD will release microcode for
their top of the line products soon but consumer grade CPUs will have to
wait until Thanksgiving :-)


What does all of the above mean in practical terms? If you are security
conscient you should not be using AMD based products for online banking or
have your computer connected to the internet while trying to see encrypted
files. Our top of the line GPU nodes utilize the latest and the greatest
AMD products (just like many other HPC intensive shops). They are all
affected by these series of bugs. As long as you are not doing online
banking on GPU[24-27] you will be OK.


Most Kind Regards,

Predrag Punosevac
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From awd at cs.cmu.edu  Wed Jul 26 21:01:42 2023
From: awd at cs.cmu.edu (Artur Dubrawski)
Date: Wed, 26 Jul 2023 21:01:42 -0400
Subject: Second AAAI Fall Symposium on Survival Prediction
In-Reply-To: <CAKH1gVpt_f=AFxNOP4sp0-2zjGEjD_vtjs5fR2TOpDjhyJnhFw@mail.gmail.com>
References: <CAKH1gVpt_f=AFxNOP4sp0-2zjGEjD_vtjs5fR2TOpDjhyJnhFw@mail.gmail.com>
Message-ID: <CAJvAoysjTrb2XZt0LkCSmDW5sv0Se7YqMwpLFBnKbCn0-Gq1pA@mail.gmail.com>

Team,

Our own Dr. Chirag Nagpal is coorganizing this AAAI Symposium. Looks to be
a prime event and a good venue to submit work related to survival analysis,
estimation of remaining useful life, and similar topics.

Cheers,
Artur

On Wed, Jul 26, 2023, 6:11 PM Chirag Nagpal <chiragn at cs.cmu.edu> wrote:

> Might be of interest to PMx Research...
> -----------------
> Second Symposium on Survival Prediction: Algorithms, Challenges and
> Applications (SPACA)
>
> Part of the AAAI Fall Symposium Series:
> https://aaai.org/conference/fall-symposia/aaai-2023-fall-symposium-series/
> *Description of symposium*
>
> Survival analysis attempts to estimate the time until a specified event
> (eg, death of a patient) occurs, or some related survival measures, and is
> widely applicable for survival prediction and risk factor analysis. A key
> challenge in learning effective survival models is that this time-to-event
> data is subject to ?censoring?? so that the time to event is only known up
> to a bound for such instances. We seek contributions from researchers from
> diverse fields including machine learning, healthcare, medicine, finance
> and engineering. We anticipate this will foster interdisciplinary
> collaborations and will catalyze the development of the next generation of
> the survival prediction algorithms.
>
> Symposium URL: https://sites.google.com/view/spaca-2023/home
>
> Submission URL: https://easychair.org/conferences/?conf=fss230 ? select
> the Second Symposium on Survival Prediction: Algorithms, Challenges and
> Applications (SPACA) track
>
> Submission Template:
> https://www.aaai.org/Publications/Templates/AuthorKit23.zip
>
> *Topics*
>
> This symposium will focus on the following themes, covering four aspects
> of survival prediction tasks. Examples of topics of interest in each theme
> are provided.
>
>
>    -
>
>    Novel algorithms
>    -
>
>       Deep learning algorithms
>       -
>
>       Learning from multimodal data
>       -
>
>    Evaluation metrics
>    -
>
>       Calibration and discrimination
>       -
>
>       Model comparison strategies
>       -
>
>    Foundational issues
>    -
>
>       Identifying causal effects
>       -
>
>       Competing risks; dependent censoring
>       -
>
>       Uncertainty quantification
>       -
>
>    Applications
>    -
>
>       Medicine and health care
>       -
>
>       Manufacturing and engineering
>       -
>
>       Finance and economics
>       -
>
>       Law enforcement
>       -
>
>       ?
>
>
> *Important dates*
>
> All deadlines are at 11:59 pm Eastern Daylight Time.
>
>
>    -
>
>    Paper submission deadline: Friday, 11 August 2023
>    -
>
>    Acceptance notification: Friday, 1 September 2023
>    -
>
>    Camera-ready paper deadline: Friday, 15 September 2023
>    -
>
>    Registration deadline: Friday, 29 September 2023
>    -
>
>    Symposium dates: Wednesday - Friday, 25 - 27 October 2023
>
>
> *Format of symposium*
>
> The symposium will feature invited talks, paper and poster presentations,
> followed by discussion group sessions to explore open challenges and future
> directions in development of algorithms for survival prediction and their
> real-world adoption in various application domains. We anticipate this
> symposium will be in-person.
>
> *Submission requirements*
>
> Interested participants should submit either extended abstracts for the
> poster sessions (4 pages maximum) or full papers (6 pages maximum,
> excluding references) for position, review and work-in-progress pieces. We
> will also consider papers that include results that have already been
> published (with appropriate acknowledgement). Format papers using the AAAI
> proceedings template:
> https://www.aaai.org/Publications/Templates/AuthorKit23.zip
>
> Submissions should be formatted according to the AAAI template and submitted
> through the AAAI Fall Symposium Series EasyChair site at
> https://easychair.org/conferences/?conf=fss230 ? select the Second
> Symposium on Survival Prediction: Algorithms, Challenges and Applications
> (SPACA) track. Authors of accepted papers may choose to have their paper
> included in the archival proceedings published by AAAI. This is optional ?
> accepted papers where authors do not opt in for the proceedings will be
> published only on the symposium website and will not be considered
> archival for resubmission purposes.
>
> *Symposium Organizing Committee*
>
> Prof. Kevin S. Xu (chair), Case Western Reserve University
>
> Prof. Russ Greiner, University of Alberta
>
> Prof. George H. Chen, Carnegie Mellon University
>
> Dr. Weijing Tang, Harvard University
>
> Dr. Chirag Nagpal, Google Research
>
> --
>
> *Chirag Nagpal* PhD Candidate, Auton Lab
> School of Computer Science
> Carnegie Mellon University
> cs.cmu.edu/~chiragn
>
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From awd at cs.cmu.edu  Fri Jul 28 10:25:22 2023
From: awd at cs.cmu.edu (Artur Dubrawski)
Date: Fri, 28 Jul 2023 10:25:22 -0400
Subject: Fwd: This has been brought up by CRC at our last renewal and delayed
 it...please make every effort to acknowledge them in any work we
 crank out. Our ability to continue using CRC may depend on this
In-Reply-To: <BL3PR04MB8011BDC8E279D94071089998A106A@BL3PR04MB8011.namprd04.prod.outlook.com>
References: <cm.2203026270698.ekuthkk.iuuhvhyjk.j@cmail20.com>
 <BL3PR04MB8011BDC8E279D94071089998A106A@BL3PR04MB8011.namprd04.prod.outlook.com>
Message-ID: <CAJvAoyua8pkpqmHmkk-DSQZRbNmw4tWQLAbg=0f8YY3==sc8-Q@mail.gmail.com>

THis is an important note for everyone working on some of our healthcare
projects with Pitt which utilize their CRC data hosting and computing
resources.
We are expected to acknowledge in our papers and presentations these two
additional sources of funding - see the specific NIH and NSF award info
below.

Cheers
Artur

---------- Forwarded message ---------
From: Clermont, Gilles <cler at pitt.edu>
Date: Fri, Jul 28, 2023 at 8:48?AM
Subject: This has been brought up by CRC at our last renewal and delayed
it...please make every effort to acknowledge them in any work we crank out.
Our ability to continue using CRC may depend on this
To: Hauskrecht, Milos <milos at pitt.edu>, Parker, Bob <rparker at pitt.edu>,
Kyle Miller <mille856 at andrew.cmu.edu>, awd at cs.cmu.edu <awd at cs.cmu.edu>,
Pinsky, Michael R <pinsky at pitt.edu>, Al-Zaiti, Salah Shafiq <SSA33 at pitt.edu>






*From:* Center for Research Computing <bgc14 at crc.pitt.edu>
*Sent:* Friday, July 28, 2023 8:03 AM
*To:* Clermont, Gilles <cler at pitt.edu>
*Subject:* CRC News July 2023



Acknowledge CRC resources, MPI error alerts, new job efficiency display ? ?
? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?
? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?
? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?
? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?
? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?
? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?
? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?

Is this email not displaying correctly? View it in your browser
<https://centerforresearchcomputing.cmail20.com/t/j-e-ekuthkk-iuuhvhyjk-r/>

[image: University of Pittsburgh]

*Pitt Research *
*Center for Research Computing *


CRC News July 2023


------------------------------

Researchers required to acknowledge NIH S10 and NSF MRI awards when using
CRC resources

CRC?s recent hardware upgrades are thanks to two very large grants from NIH
and NSF. Proper citation plays a crucial part in the University being able
to secure more grants of this nature in the future. For all publications
that use research conducted at the CRC after July 2022 please follow the
instructions below (also found on the CRC website:
https://crc.pitt.edu/about/acknowledge
<https://centerforresearchcomputing.cmail20.com/t/j-l-ekuthkk-iuuhvhyjk-j/>
).

All research products (publications, conference proceedings, and
presentations) resulting from an allocation of computing time or storage on
HTC (HTC cluster) should include the following acknowledgement:

*"This research was supported in part by the University of Pittsburgh
Center for Research Computing, RRID:SCR_022735, through the resources
provided. Specifically, this work used the HTC cluster, which is supported
by NIH award number S10OD028483."*

All research products (publications, conference proceedings, and
presentations) resulting from an allocation of computing time or storage on
H2P (SMP, MPI, and GPU clusters) should include an acknowledgement:

*"This research was supported in part by the University of Pittsburgh
Center for Research Computing, RRID:SCR_022735, through the resources
provided. Specifically, this work used the H2P cluster, which is supported
by NSF award number OAC-2117681."*

You are free to also acknowledge or thank individual members of the CRC
team.

Please remember to also list any research products (publications,
conference proceedings, and presentations) resulting from usage of CRC
resources in any allocation or renewal proposal.
------------------------------

Some MPI Cluster Users Will See Minimum Node Count Error

Users of the MPI cluster may notice the following output when attempting to
submit a job requesting less than 2 nodes:

*sbatch: error: ERROR: Minimum node count is 2!*
* sbatch: error: Batch job submission failed: Node count specification
invalid*

This is to prevent single-node jobs that should otherwise be run on the SMP
cluster from using MPI-centric hardware that were configured specifically
to support parallel jobs across multiple compute nodes.

To prevent similar undersubscription at the CPU level and for consistency
with accounting of service unit usage for MPI jobs, a warning message is
currently in place for jobs that request CPU cores less than the full
amount that the node offers (ntasks-per-node):

sbatch: WARNING: Your MPI job is not requesting the full number of cores on
its nodes: 48 cores on the mpi partition. MPI jobs will need to request the
full number of cores to be successfully submitted to SLURM after July 15,
2023. Please modify your submission script to request the full core amount
or consider submitting your job to the SMP cluster.

After July 15, MPI jobs that do not request the full node's resources will
no longer enter the queue. You will need to adjust your SLURM submission
script to request all of the cores available. At a minimum, your job
submission script will need the following SLURM directives:

*#SBATCH --nodes=2*


* #SBATCH --ntasks-per-node=48 #SBATCH --cluster=mpi #SBATCH
--partition=mpi*

If your MPI workflow is optimized for a certain number of cores, you will
need to make sure that the proper amount is being specified to your
software by input argument, configuration file parameter, etc. Please submit
a help ticket
<https://centerforresearchcomputing.cmail20.com/t/j-l-ekuthkk-iuuhvhyjk-t/>
if you need guidance in updating your job submission script.
------------------------------

Ask Nick: Can I access information on my job?s efficiency?

After CRC made a policy change on the lower limit of requested CPUs on MPI
(see details above), some users were still submitting and being allocated
multiple full nodes worth of CPUs, but only a small number were being
utilized for the duration of the job. We used a script provided in the
SLURM installation called "seff" to display this for an individual job, and
I created a wrapper around that functionality to show output more easily
for multiple jobs.

The idea is to equip users with information about just how much of their
job's resources are being used over the duration of the job, given their
submission script configuration. This output could be used by PIs to
demonstrate the efficiency of the submitted jobs when they request a yearly
allocation of service units. This functionality will be available in
mid-August.

Users will be able to specify which cluster, which user, and a date range
to look for completed jobs. The most valuable information is in the CPU
Efficiency and Memory Efficiency items. When these are high, the full
allocation of resources for the job is being used. Low values indicate that
the user is requesting more resources than necessary for their processing,
and that they should adjust their submission script. The function currently
only shows CPU output, but we hope to add efficiency for GPU usage in the
future.

In the example below of output for multiple jobs, the top line is the input
command, followed by what the user sees regarding their completed jobs.
Note that one job failed, and therefore the efficiency could not be
calculated.

*crc-effective -M mpi -u leb140 -S 06/01/23*
* Showing jobs on mpi that completed between 06/01/23 and now for leb140:*

*cluster name: mpi*










* Job ID: 1489891 Cluster: mpi User/Group: leb140/sam State: COMPLETED
(exit code 0) Nodes: 2 Cores per node: 48 CPU Utilized: 2-08:55:19 CPU
Efficiency: 99.10% of 2-09:26:24 core-walltime Job Wall-clock time:
00:35:54 Memory Utilized: 4.45 MB Memory Efficiency: 0.00% of 187.50 GB*

*cluster name: mpi*









* Job ID: 1490283 Cluster: mpi User/Group: leb140/sam State: FAILED (exit
code 1) Cores: 1 CPU Utilized: 00:00:00 CPU Efficiency: 0.00% of 00:00:00
core-walltime Job Wall-clock time: 00:00:00 Memory Utilized: 0.00 MB
(estimated maximum) Memory Efficiency: 0.00% of 1.95 GB (1.95 GB/core)*

*Nickolas Comeau is a CRC Research Computing Specialist*


------------------------------

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<https://centerforresearchcomputing.cmail20.com/t/j-l-ekuthkk-iuuhvhyjk-h/>

University of Pittsburgh
Center for Research Computing

312 Schenley Place
4420 Bayard Street
Pittsburgh, PA 15260
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From arundhat at andrew.cmu.edu  Fri Jul 28 13:00:50 2023
From: arundhat at andrew.cmu.edu (Arundhati Banerjee)
Date: Fri, 28 Jul 2023 13:00:50 -0400
Subject: Lov 10, 11, 13 scratch full
Message-ID: <BA4BB534-B464-4B50-B60B-CBD1FB4ED7A3@andrew.cmu.edu>

Hi,

The scratch directories on lov10, lov11 and lov13 are full. Please free up some space to make them usable. Thanks! 

-Arundhati

From awd at cs.cmu.edu  Sun Jul 30 04:46:43 2023
From: awd at cs.cmu.edu (Artur Dubrawski)
Date: Sun, 30 Jul 2023 04:46:43 -0400
Subject: =?UTF-8?Q?Fwd=3A_Join_Us_on_August_4_for_RISS=E2=80=99s_Final_Events=21?=
In-Reply-To: <CAMkDbDXPjEfWspYD8KaeYmCEyqmG08bLs9OVoTcDPgJ8wS2QEQ@mail.gmail.com>
References: <CAMkDbDXPjEfWspYD8KaeYmCEyqmG08bLs9OVoTcDPgJ8wS2QEQ@mail.gmail.com>
Message-ID: <CAJvAoyt3xwh-A3Bo8B9F-SynmUWbSsrfzN23bDuzWk0NA_H5Bg@mail.gmail.com>

This year, we have quite a handful of RISS interns who are working on
really interesting projects. Please mark your calendars and attend their
final showcase next Friday.

Cheers,
Artur

---------- Forwarded message ---------
From: Rachel Burcin <rburcin at andrew.cmu.edu>
Date: Wed, Jul 26, 2023, 10:28 AM
Subject: Join Us on August 4 for RISS?s Final Events!
To:
Cc: Rachel Burcin <rburcin at andrew.cmu.edu>, . RISS Info <
riss-info at andrew.cmu.edu>, John Dolan <jdolan at andrew.cmu.edu>


Greetings, RISS Friends

Thank you for another fantastic summer of the Robotics Institute Summer
Scholar (RISS) Program. Every summer, we like to close by showcasing our
students' hard work, celebrating their achievements, and thanking the
faculty, team members, and sponsors who make the program possible.  Come
celebrate!  Please share this email with your entire lab.

This summer, we have two different events. We sincerely hope you can join
us in these celebrations:

RISS Final Showcase | Friday, August 4 | 1 - 2:30 PM | 6th Floor of GHC (across
rooms 6115, 6121, the Collaborative Commons, and the patio)

Our 47 scholars will be presenting their final research posters at this
event. Snacks and drinks will be provided; mill around, eat, and learn
about the amazing work our students have been doing this summer. We?re
proud to showcase their hard work! This is also a great opportunity to get
photos with your scholars, the team, and the sponsors.

RISS Closing Certificate Ceremony | Friday, August 4 | 3 - 4 PM | Rashid
Auditorium (GHC 4401)

We will be offering final remarks, extending our gratitude, and
distributing students? certificates at this closing ceremony. This event is
specifically for the RISS community: RISS faculty, RISS mentors, RISS team
members, RISS scholars, and the scholars? family, friends, and mentors.
This is also a great opportunity to get photos with your scholars, the
team, and the sponsors.

We look forward to seeing you at these final events!

Thank you for your ongoing support,

John, Rachel, & Maria
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From ngisolfi at cs.cmu.edu  Mon Jul 31 09:50:09 2023
From: ngisolfi at cs.cmu.edu (Nicholas Gisolfi)
Date: Mon, 31 Jul 2023 09:50:09 -0400
Subject: Auton Lab 30th Anniversary Celebration
Message-ID: <CANmms2RFJqtY9Qq09Z19Fqf1892AHw2wcYdg_0uFKLhANN5f5w@mail.gmail.com>

Hi Everyone,

On the weekend of September 8-10, the Auton Lab will be celebrating its
30th Anniversary.The event will feature a weekend of activities.

- Friday will include talks focused on AI, along with panel discussions.
- Saturday will be an all-day picnic providing ample time to catch up with
friends.
- Sunday will include a send-off brunch for all of our out-of-town visitors.

If you would like to attend the event, please RSVP
<http://autonlab.org/30th-Anniversary/>.  We look forward to seeing you
there!

- Nick and Jessie, on behalf of the organizing committee
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