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".
Projects that can be described by one or more Keywords to trigger NIP referrals are within the scope regardless of discipline.

Goals, Metrics & KPIs


Percentage of users on new XSEDE grants for non-traditional projects: key performance indicator for XSEDE
Extend use to
new communities
Number of users on new XSEDE grants for non-traditional projects700/yr

Extend use to

new communities
Percentage of users on sustained (usage at least 10% of allocation) XSEDE grants for non-traditional projects: key performance indicator for XSEDE33%/yr
Extend use to
new communities
Number of users on sustained (usage at least 10% of allocation) XSEDE grants for non-traditional projects2000/yr

Extend use to

new communities
Number of new XSEDE projects from target
communities generated by NIP
Extend use to
new communities
Number of sustained XSEDE projects from target
communities mentored by NIP
Extend use to
new communities


Percentage of new allocated users from non-
traditional disciplines of XSEDE
resources and services
35% of newly allocated users from all disciplines during the reporting year.
Percentage of sustained users from non-
traditional disciplines of XSEDE
resources and services
22% of users from all disciplines, on grants active during the reporting year that have used at least 10% of their allocation.

Team Members

Paola BuitragoPSCExpertpaola@psc.edu
Alan CraigShodorDeputy Manager; Experta-craig@illinois.edu
Amit ChourasiaSDSCExpertamit@sdsc.edu
Sudhakar PamidighantamIUExpertpamidigs@iu.edu
Paul RodriguezSDSCExpertprodriguez@sdsc.edu
Sergiu SanieleviciPSCManagersergiu@psc.edu
Marcela MadridPSCExpertmmadrid@psc.edu
Roberto GomezPSCExpertgomez@psc.edu
Davide Del VentoNCARExpertddvento@ucar.edu
Joel WellingPSCExpertwelling@psc.edu
Bryon GillPSCExpertbgill@psc.edu
Rozita LaghaeiPSCExpertrlagha@psc.edu
Julian UranPSCExpertjulian@psc.edu
Rajanie PrabhaPSCExpertrajanie@psc.edu
Kelly PierceTACCExpertkpierce@tacc.utexas.edu


Communication & Meetings

Email list: ecss-nip@xsede.org

Meeting Information


NIP Strategic Plan

NIP Data Science Learning Resources

Projects to contact

Keywords to trigger NIP referrals

SGCI Support for Front-end Gateway Development

New Staff Orientation

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) ASC180053 (PB) ASC180054 (medical imaging, ML) IRI180020 (ML) IRI180021 (robotics) SES180012 (economics, XRAC ECSS) DPP180003 (Polar research, image analysis) PHY180046 (LHC, ML) PHY180050 (cosmology, ML)  ASC180008 (DL, energy infrastructure remote sensing, XRAC rejection) IRI180022 (Robotics, ML) MSS180021 (materials, ML) BIO150074 (genomics, ecology) DEB180019 (metagenomics, transcriptomics, arctic studies) MCB180172 (genomics, ecology) DBS180011 (ML, archaeology) MCB180176 (BLAST mis-annotation) SES180011 (economics) DDM180007 (deep learning) DMS180040 (DL) SBE180006 (social network) SES180007 (Financial Market Research) IBN180001 (brain connectome) MCB180182 (medical imaging DL)

11/1/18 to 1/31/19: SES180022 (economics) CCR180059 (MPI-cuda-GIS) MCB180195 (genomics, ecology, data collection) PHY180060 (HEP, dark matter, DL/NN) IRI180028 (Jetstream, natural language processing; text mining; computational linguistics) IRI180026 (robotics) AST180069 (DL in radio astronomy) IBN180020 (echinoderm genome assembly) ECS180015 (ML, wifi sensing) CCR180066 (DL in computational chemistry) IRI180032 (ML, Cryo-EM) IBN170020 (neuroscience) ASC170054 (graph computing) MCB190016 (ML, genomics) SES190007 (statistics, mental health) MCB190018 (DL, population genetics)

2/1/19 to 4/30/19:  ASC180051 (Berkeley Container Library) IRI190006 (DL, Robotics) MSS180028 (ML, complex systems) SES190009 (economics) EAR190010 (DL, Geophysics) CDA190001 (DL, pathology) ASC190013 (DL tool development) DEB190002 (ornithology, citizen science) DBS190002 (metagenomics, paleoanthropology) CCR190008 (deep neural networks research) ASC190014 (neural networks, photo DB management)  MCB190021 (genomics, AI) SES190003 (XRAC, federal reserve) CHE190022 (optical microscopy, DL) DMS190010 (seismology, DL) ASC190018 (cancer imaging, DL) MCB180081 (genomics) CCR190014 (gene expression, PA Cure, Large Memory) ASC190019 (plant classification, CNN) ASC190020 (3D Scanning and Augmentation, DL) BCS190005 (DL for biomedical imaging) SES190014 (decision science, data privacy) ATM190007 (ML, rainfall distribution) DBS190003 (ML, visual recognition) ASC190027 (Neural Architecture Search, NLP)

5/1/19 to 7/30/19: AST190024 (cosmology, DL)  ECS190007 (NLP, infrastructure management) DBS180014 (NLP, machine comprehension) DMS190019 (AI drug repurposing) MCB190067 (ML, gene expression) MCB190065 (ML, gene expression) BIR190003 (ML controlled medical imaging) CDA190007 (agent based simulation, public health) MCB190075 (DL, proteomics) IBN190007 (brain imaging) OCE190009 (data science in satellite observations) ASC190034 (3D image reconstruction, physics based ML) EID180001 (Deep Learning in Geosystems) IRI190011 (speech recognition) MCB190093 (genomics reference trees)  MCB190094 (CRISPR, ML) MIP190004 (circuit design, ML) IRI190013 (ML research) IBN180019 (XRAC, RNA sequencing, statistical methods) MCB190114 (SGCI, ML, GAMESS, RNA) PHY190036 (ML, Higgs) ASC190042 (ML, epigenetics) CCR190034 (genetic programming) 

8/1/19 to 10/30/19: MCB190119 (gene expression, ML) MCB190120 (protein structure, ML) IRI190014 (NLP, ML) CTS190052 (MD, DFT, ML) CCR190032 (ML, DARPA Hackathon) MCB190126 (predict cancer biomarkers) MSS190019 (dynamic control of unmanned vehicles, AI) SES190017 (Financial Big Data and Machine Learning) AST190040 (astronomy, ML) ATM190020 (lightning strike data) IBN190012 (auditory and visual category learning) IRI190015 (DL theory) ASC190046 (ML, Nanomaterials) EAR190025 (GeoAI) DMS190025 (Meteorological data assimilation) CCR190047 (ML, stem cell microscopy) CCR190050 (ML, metagenomics) CCR190051 (ML, image compression) IRI190017 (CNN, statistics, sepsis prediction) DDM190001 (ML, IC diagnostics) DMR190092 (computer vision DL, additive manufacturing) SBE190004 (human decision making) PHY190040 (ML theory) DMS190028 (Formal Abstracts in Mathematics) CCR190053 (NN, microcontroller units) MCB190144 (Protein Design using CNN) CCR190054 (AI for Image and Signal Processing) IBN190013 (NN, electron microscopy) CCR190056 (V100-accelerated DNA sequence alignment)  CCR190057 (deep learning, fMRI) DPP190001 (AI, Polar Science, XRAC, continues startup DPP180003)

11/1/19 to 1/31/20:  ECS190014 (wireless communication, NN) SBE190006 (network science) DEB190019 (Phylogeny and Biogeography) IRI190019 (music information retrieval) CCR190059 (Graph Neural Networks) MCB190171 (DL, chromatin organization) AST190059 (cosmology, ML) CDA190013 (DL, neuropathology) CTS190070 (CFD DNS, DL) DMR190116 (DFT force field development, DL) CTS190072 (microfluidics, DL) CCR190064 (mathematics)  CCR190027 (quantum computing) DMS190037 (observational study design) CCR180060 (Reinforcement Learning for Self Driving Cars) MSS190026 (DL, dislocation dynamics) DMS190040 (uncertainty quantification) IBN190018 (DL, optogenetic studies) IRI190021 (exobiology, DL) OCE190015 (coastal engineering and management) PHY190053 (quantum computing) IBN190019 (physio-psychology of vision) MCB190184 (DL, Genomics) DMS190041 (mathematics) IRI190023 (ML, ICU risk prediction) SBE190008 (economics, AirBnB) ASC190069   CCR190067 (Turing-completeness of DL) IBN190022 (ML, neuroscience) CCR190069 (Image Translation, Sonography, NN) BIR190005 (NIH Biomedical Data Science Codeathon) IRI200001 (robotics, computer vision) DMS200001 (seismology, Bayesian MC, NN) DMS200003 (oceanography, functional data analysis) IBN200002 (cardiac arrest, ML) IRI200002 (breast cancer, ML) IRI200003 (biomedical computer vision deep-learning) CCR200001 (Entity Linking for Tweets) AST200009 (GPU-accelerated search for distant Solar System objects) DMR200017 (Machine Learning Accelerated Quantum Monte Carlo Method for Fermions) IRI200004 (Meta-Reinforcement Learning) MCB200022 (genomics, rapid evolution) CTS200013 (MD, GA, DL) 

 2/1/20 to 4/30/20: DMS200006 (HIV genomics, ML) IRI200006 (medical robotics, computer vision) ASC200007 (ML on clinical images) MCB200027 (NIH transcriptomic data) DEB200004 (multisource data, Bayesian, holocene species range expansion) IBN200005 (processing ultra-high-resolution diffusion MRI data of terabytes size, ECSS) CTS200016 (Ocean Wave Forecast with Data Assimilation) ASC200005 (Big Data Management and Analysis Course at Cornell) IBN200007(genetic variation, gene expression and neuroimaging phenotypes to inform the etiology of psychopathology) SES200004 (Cooperative Patent Classification using AI) ASC200010 (Diabetic Retinopathy using deep learning) SES200006 (Language in Finance, DL) IBN200009 (Data-driven modeling and simulation of individual variability and adolescent development of the human connectome) DMR200021 (Materials Micro-Structure Image Analysis) DMR200022 (materials, DL) CHE200021 (Quantum Computational Simulations for Computational Chemistry) DMR200023 (Crystal synthesis prediction via deep learning) ASC200014 (Covid-19 epidemiology, ECSS) CCR200011 (Personalized Human Activity Recognition using CNNs) DEB200008 (ecology, genomics, ML) MCB200074 (evolutionary genomics, statistics) IRI200009 (Common sense and language for computer vision tasks) EAR200003 (Deep Transfer Learning to Model the Biogeosphere) DEB200005 (Biology-guided neural networks for discovering phenotypic traits) IBN200011 (Deep learning for real-time cognitive state classification using EEG, fNIRS and BSN data) OCE200008 (ocean science, data visualization, oral history; ECSS) DEB200012 (phylogenetics, biomechanics, macroevolution) DMR200041 (machine learning potential for 2D materials) SBE180007 (Fake News Shelf life; ECSS)  SES200010 (ML, corporate bankruptcies) 

 5/1/20 to 7/31/20: EID200001 (Stormwater Infrastructure Climate Resilience Assessment)  EAR200008 (DL dynamic scaling of growing interfaces)  IRI200018 (DL, breast cancer therapy) IBN200014 (Image analysis of the role of perineuronal nets in long-term memory consolidation) CCR200004 (Compressing and Accelerating Transformers-based Large-Scale Language Representations) ECS200008 (Post Quantum Public-Key Cryptography) ASC200032 (Reducing Memory Footprint for Extreme-Scale Deep Learning) PHY200019 (ML, particle physics) CCR200029 (Earth Science, Deep Learning, Spatial Structured Models) CCR200032 (Biological inspired Neuronal Network simulator) SES200012 (Empirical Examination of Corporate Rebranding and Trademarks) CCR200033 (Development of an Exemplar Suite for Verifiably Correct HPC Programs) IRI200020 (deep learning classifiers of malware variants) DBS200005 (AI tools for studying infant brain development) CCR200037 (Runtime Data Management on Heterogeneous Main Memory Systems for Deep Learning)