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Mission Statement

Novel and Innovative Projects (NIP) accelerates research, scholarship, and education by new communities that can strongly benefit from the use of XSEDE’s ecosystem of advanced digital services. The NIP team helps to identify scientists, scholars and educators from disciplines that have not yet made significant use of advanced computing infrastructure, who are committed to projects that require XSEDE services and are in a good position to use them efficiently. NIP staff provides mentoring to these projects, helping them to obtain XSEDE allocations and to use them successfully.
The disciplines considered within the scope of NIP are defined in the child page "Scope of NIP".

Goals, Metrics & KPIs


Number of new users from non-traditional
disciplines of XSEDE resources and services
Extend use to
new communities
Number of sustained users from non-traditional
disciplines of XSEDE resources and services
500 each RP
Extend use to
new communities
Number of new XSEDE projects from target
communities generated by NIP
Extend use to
new communities
Number of successful XSEDE projects from target
communities mentored by NIP
25 each RP
Extend use to
new communities


Percentage of new allocated users from non-
traditional disciplines of XSEDE
resources and services
30% of newly allocated users from all disciplines during the reporting period.
Percentage of sustained users from non-
traditional disciplines of XSEDE
resources and services
25% of users from all disciplines, on grants active during the reporting period that have used at least 10% of their allocation.

Team Members

Alan CraigShodorDeputy Manager;
Davide Del


Communication & Meetings

Email list:

Meeting Information


NIP Strategic Plan

NIP Data Science Learning Resources

Keywords to trigger NIP referrals

SGCI Support for Front-end Gateway Development

New Staff Orientation

  • Email list: : request access by email to the NIP manager:
  • Staff account STA110013S: request access by email to the Director, ECSS-Projects: .

Projects to watch

July-August 2016 New Startups: SES160006 DEB160014 MCB160141 EAR160030

July-August Mentored Projects: CDA160006 OCE150020 DMS160012

September-October 2016 New Startups: IBN160012 ASC160052 CIE160037 MCB160154 DMS160026   NCR160004 CIE160041 ENG160032 ENG160035 DEB160017 ENG160036 DMS160028 HUA160003 CCR160028 CIE160048 BCS160005

November 2016 -January 2017 new startups: ASC160073 ECS160007 DMS160031  IBN160017 ASC160083

February - April 2017 new startups:  SES170001 CDA170001 CHE170015 DEB170003 SES170009 ASC170011 CIE170015 HUA170001 MCB170039 ASC170012 DBS170003 SBE170002 MCB170042 ASC170015 CIE170019 ASC170017 ASC170019 BIO170028 CIE170024

May - July 2017: SBE170003 DMS170010 DEB170008 BIO170035 BIO170037 CIE170028  OCE170008 DMS170012 MCB170068 DDM170001 BIO170041 MCB170071 BIO170039 SES170014 BIO170048 CCR170012 EAR170002 CIE170031 ENG170016 CCR170013 CCR170015 HUM170001 ASC170034 OCE170010 BCS170012 SES170016 DMS170015  CIE170036 MCB170094 MSS170026 BIO170064

Aug-Oct 2017: BIO170065 IRI170003 ECS170006 BIO170064 DEB170010 CDA170007 ASC170047 ASC170048 HUM170002 CDA170010 SES170019 CIE170047 BIO170082 BIO170084 SES170021 SES170020 DEB170012 MCB170134 EAR170018 CIE170007

Nov 2017 - Jan 2018: SES170022 DPP170002 CCR170031 IRI170006 ENG170034 CIE170056 SES170025 BIO170104 DEB170016 IRI170007 BIO170110  ASC170073 MCB170162  CCR160012 DEB170017 DBS170013 SES180001

February - April 2018: DMS180001 ART170002 (ECSS) IRI180001 ASC170072 (ECSS) CIE170063 ASC170074 SES180002 DMS180008 AST180011 (big data) ASC180009 DMS180011 (deep learning) CHE180011 (deep learning) BIO180015 (ML) BIO180016 ATM180004 (ML) ASC180018 (ML)  IRI180003 (ML) CTS180015 (big data) SBE180001 ENG180004 (ML)  SES180006 (BD)

May - July 2018: DDM180003 (ML) CCR180014 (AI - ECSS per PB, requesting Anirban be assigned )  EAR180005 (ECSS, SGCI?)  OCE180009 (ECSS, Lisa L.) ASC180020 (ML) CIE180020 (ML) MCB160174 ASC180021 (workflow performance prediction, ML, SDSC staff) SES180009 CCR180019 DDM180004 (DL) MCB180060  CDA160011 IRI180006 (ML) ASC180025 (BD) OCE160022 (ML, XRAC) IRI180007 (ML) IRI180010 (ML) IBN180007 MCB160026 (Bioinfo ML) MCB180069 (bioinfo) IRI180012 (robotics) MCB160083  (ML/Biophysics)  CCR180023 (graph analytics) ASC180034 (ML, genomics, ECSS=1)?? DMS180026 (genomics, statistics, ECSS=1) BCS180015 (Bioinformatics)!!  SES180013 (NBER)??

August to October 2018: DMR180085 (LS-DYNA and Tensorflow) BCS180016 (medical DL) MCB180117 CCR180030 (DB) CHE180011 (MD, DL) ECS180008 (ML) SES180014 (Econ, natural language processing, 20 TB MySQL DB?)  MCB180122 (Genomics) DDM180005 (Transportation, Gurobi)  – DMS180029 (Bayesian, brain connectome) MCB180126 (multicontrast MR and non-parametric machine learning) CDA180008 (social media patterns) HUM180001 (Historical documents, ML)  DMS180027 (public health) PHY180043 (HEP, ML)





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