CCL: Deadline today: Data Mining and Machine Learning in Molecular Sciences



 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/>;
 >
 -----------------------------------------------------------------------------------------
 >