From owner-chemistry@ccl.net Mon Apr 17 17:37:00 2017
From: "Johannes Hachmann hachmann _ buffalo.edu" <owner-chemistry-.-server.ccl.net>
To: CCL
Subject: CCL: Deadline today: Data Mining and Machine Learning in Molecular Sciences
Message-Id: <-52750-170417162133-12160-NOLTPNxHAmJVfky3lMKA9g-.-server.ccl.net>
X-Original-From: "Johannes  Hachmann" <hachmann|*|buffalo.edu>
Date: Mon, 17 Apr 2017 16:21:32 -0400


Sent to CCL by: "Johannes  Hachmann" [hachmann~~buffalo.edu]
Dear Colleagues,

This is a quick reminder that the abstract submission for our CoMSEF session on "Data Mining and Machine Learning in Molecular Sciences" at the 2017 AIChE Annual Meeting closes TONIGHT AT 11:59PM EDT. 

Kind Regards,

Johannes Hachmann (University at Buffalo - SUNY)
Andrew Ferguson (University of Illinois Urbana-Champaign)
Diwakar Shukla (University of Illinois Urbana-Champaign)

> -----Original Message-----
> From: Hachmann, Johannes
> Sent: 10 April, 2017 10:44
> To: Johannes Hachmann (hachmann : buffalo.edu) <hachmann : buffalo.edu>
> Subject: CoMSEF session on "Data Mining and Machine Learning in Molecular
> Sciences" at the 2017 AIChE Annual Meeting in Minneapolis (Oct 29 - Nov 3)
> 
> Dear Colleagues,
> 
> We are writing today to let you know that we will again be running our
> CoMSEF session on "Data Mining and Machine Learning in Molecular Sciences"
> at the 2017 AIChE Annual Meeting in Minneapolis, MN (Oct 29 - Nov 3). This
> year, the session is co-sponsored by Data and Information Systems (10E).
> 
> In the previous two years, this session has proved to be exceedingly popular
> and well attended, indicative of a critical groundswell of excitement and
> interest within the ChemE community for data-driven methods and
> applications in the physical, chemical, materials, and life sciences. We are also
> delighted to announce that this year's session will be anchored by an invited
> talk from Prof. David Sholl (Georgia Tech).
> 
> We are currently soliciting abstracts for contributed talks, and if you or your
> students/postdocs are interested in presenting in this session, we would be
> excited to receive your submission through the online application portal. The
> scope of the session is intentionally broad, concerning the generic applications
> of data mining and machine learning for property prediction, molecular
> understanding, and rational design. Details of the session and instructions for
> abstract submission are provided below. The submission deadline is Monday,
> April 17, i.e., it is rapidly coming up.
> 
> We look forward to seeing you in Minneapolis!
> 
> Kind Regards,
> 
> Johannes Hachmann (University at Buffalo - SUNY)
> Andrew Ferguson (University of Illinois Urbana-Champaign)
> Diwakar Shukla (University of Illinois Urbana-Champaign)
> 
> ---
> 
> Data Mining and Machine Learning in Molecular Sciences
> 
> https://aiche.confex.com/aiche/2017/webprogrampreliminary/Session35757.ht
> ml
> 
> Computational approaches to correlate, analyze, and understand large and
> complex data sets are playing increasingly important roles in the physical,
> chemical, and life sciences. This session solicits submissions pertaining to
> methodological advances and applications of data mining and machine learning
> methods, with particular emphasis on data-driven modeling and property
> prediction, statistical inference, big data, and informatics. Topics of interest
> include: algorithm development, inverse engineering, chemical property
> prediction, genomics/proteomics/metabolomics, (virtual) high-throughput
> screening, rational design, accelerated simulation, biomolecular folding,
> reaction networks, and quantum chemistry.
> 
> 1. Go to
> https://aiche.confex.com/aiche/2017/webprogrampreliminary/Session35757.ht
> ml.
> 2. Click on the orange "Submit an Abstract to this Session" button at the
> bottom of the page.
> 
> 
> -----------------------------------------------------------------------------------------
> Dr. Johannes Hachmann
> Assistant Professor
> University at Buffalo, The State University of New York
> Department of Chemical and Biological Engineering (CBE)
> New York State Center of Excellence in Materials Informatics (CMI)
> Computational and Data-Enabled Science and Engineering Program (CDSE)
> 612 Furnas Hall
> Buffalo, NY 14260
> www.cbe.buffalo.edu/hachmann <http://www.cbe.buffalo.edu/hachmann>
> http://hachmannlab.cbe.buffalo.edu <http://hachmannlab.cbe.buffalo.edu/>
> -----------------------------------------------------------------------------------------
>