ANRF MISSION AI for Science and Engineering (AI-SE)

Introduction:
Anusandhan National Research Foundation (ANRF) is mandated to spearhead a new era of directed Research & Innovation in the country, translating ideas into tangible national and societal outcomes. Under its Mission for Advancement in High-Impact Areas (MAHA) program, ANRF promotes mission-mode, solution-oriented research. The newest flagship initiative under ANRF MAHA is Artificial Intelligence for Science & Engineering (AI-SE), launched in collaboration with the Ministry of Electronics and Information Technology (MeitY), Scientific Departments (DRDO, MoES, DBT, MNRE), non- government partners (Gates Foundation and Google).

Vision:

To embed AI as a core enabler of India's scientific and engineering ecosystem by advancing foundational AI methods, domain-specific models, and national-scale infrastructure for accelerated discovery and innovation.
AI_SE

Objectives:
  • Advance next-generation AI methods that directly model science and engineering, including neural operators, physics-informed learning, molecular and biological foundation models, and domain-specific models, AI agents, agentic harness, design of programmable labs, loop of science.
  • Accelerate AI-driven discovery in strategic areas such as Climate Science, Advanced Materials, Biomanufacturing, and data-rich fields like microscopy, spectroscopy, medical imaging, astrophysics, and high-energy physics.
  • Build an open, interoperable AI ecosystem of scientific models, datasets, tools, and infrastructure to embed and share scientific insights across domains. This includes AI Agent Harnesses, Code Generation for Scientific/HPC Optimized Codes, scalable AI frameworks, scientific workloads and orchestration capabilities for transformative applications in science and engineering.
  • Catalyse cross-disciplinary collaboration to integrate AI research with domain expertise, advance the science of AI (including generative AI and domain adaptation), and strengthen India's scientific and technological self-reliance.
  • Creation of a coherent set of open-source, open- weight models, AI Agent Harnesses & Frameworks, foundation models and datasets for science and engineering.


Significance of the Mission:
This Mission positions AI as an integral component of the scientific and engineering enterprise where scientific principles, engineering designs, data, and models are directly embedded in AI systems, thereby advancing both the frontiers of science/engineering and the science of AI to accelerate discovery, innovation, and national technological self-reliance. Proposals which are primarily in Science and Engineering but do not have a strong AI component will be de-prioritized.

Scope of the Mission:
The Mission adopts an interlinked support architecture through various domain specific programs.

The Mission will drive cutting-edge AI research, backing academia and research institutions to develop fundamental building blocks in science and engineering. This includes exploring novel architectures like domain-centric neural operators, sophisticated large-scale models tailored for specific knowledge domains in science and engineering, and AI-powered experimental platforms and digital twins.

The projects identified under the programs will be open for funding support by ANRF and/or partner scientific departments such as Ministry of Earth Sciences (MoES), Department of Biotechnology (DBT) and Defence Research & Development Organization (DRDO) and Ministry of New and Renewable Energy (MNRE) , based on the areas of interest. More entities including non-governmental organizations will be added to the mission as program partners, in future.

Projections for the programs include scalable GPU clusters supported by MeitY, a federated data backbone built on FAIR (Findable, Accessible, Interoperable, and Reusable) principles, and an open-source ecosystem of models, tools, and autonomous laboratories for machine-speed validation. These elements converge in the Open IndiaAI Stack, a composable catalogue of models, datasets, and workflows that function like snap-together "LEGO blocks. These LEGO blocks can be composed into domain specific AI agents via automated AI techniques. The outputs of supported projects must be deposited and shared openly in these repositories such as AI Kosh, Hugging Face and open-model repositories.


Proposals are invited under the following Categories:

Category A: Open calls in the following Areas with emphasis on reimagining these areas.

Program I: AI for Science and Science of AI (ANRF, MeitY and Gates Foundation)

  1. Hybrid AI-HPC Approaches for Scientific Discovery
  2. Reimagining Design and Simulation through AI
  3. AI for Next-Generation Batteries and Sustainable Energy Storage
  4. AI for Scientific characterization (including medical imaging, microscopy, spectroscopy and multimodal data analysis)
  5. AI for Computational Chemistry
  6. AI for Astrophysics, Cosmology, Nuclear and High Energy Physics
  7. AI-guided Molecular Design or Quantum phenomena
  8. AI for Mathematics and Mathematical Reasoning
  9. AI for reimagining & transforming core scientific disciplines

Program II: AI for Engineering with emphasis on Engineering Design and Accelerated Materials Development (ANRF, MeitY and DRDO)

  1. Accelerating Materials Discovery and Optimization with AI
  2. Novel Materials design through AI for defence applications
  3. Digital Twins for naval systems like AIP, advanced propellers, unmanned underwater systems
  4. Real-time fluid dynamics modelling
  5. AI-enabled design and maintenance of maritime systems
  6. AI for semiconductor & circuit design.
  7. AI for any core engineering area
  8. AI for Advance Engineering Design & Manufacturing (AI-CAD, AI-CAM)
  9. AI for robotics, drones, edge & embedded system applications
  10. AI for electricity grid

Program III: AI for Earth, Atmosphere, Ocean Sciences (ANRF, MeitY, MoES and MNRE)

  1. AI emulators for physics parameterization and earth system models
  2. Multimodal rainfall nowcasting
  3. Climate modelling and environmental forecasting
  4. AI for Earth Science and Geotechnical applications including accelerated subsurface and subsea exploration of geothermal, oil & gas resources etc
  5. Applications including coupled modelling and extreme event risk forecasting for disaster management, pollution, renewable energy and agriculture.
  6. AI for critical minerals and energy exploration

Program IV: AI for Bio and Life Sciences (ANRF, MeitY, DBT, Google and Gates Foundation)

  1. Biomanufacturing
  2. AI-assisted strain selection and yield optimization
  3. Enzyme design and biocatalysis
  4. AI for Drug Discovery, Cell & Gene Therapies
  5. AI for Computational Biology
  6. AI for Protein and mRNA biologics
  7. AI for Therapeutics and Vaccines
  8. AI for Multi OMICS in Plant and Animal Sciences

Category B

Category B: Proposals are invited against the following challenge statements.

The detailed statements are provided in the Annexure.

  1. AI for Maternal, Newborn and Child Health
  2. AI-ready Datasets and Biobanks for Women's and Paediatric Health
  3. AI for Infectious-Disease Screening, Diagnostics and Surveillance
  4. AI for Drug Discovery and Development: Therapeutics, Biologics and Vaccines
  5. Independent Assessment and Benchmarking of AI Systems for Performance, Cost, Efficiency and Scalability
  6. AI-Based Forecasting for Renewable Energy Generation and Grid Integration
  7. Open-stack AI for Robotics: Manipulation, Safe Learning and Teleoperation
  8. Accelerating the Loop of Science: Programmable Laboratories and AI-Driven Experimental Workflows
  9. AI for Semiconductor Science and Technology: Foundational Problems from Materials to Circuits
  10. AI for Semiconductor Design: Foundational Models and Neuro-Symbolic Frameworks for SoC Assembly and Verification
  11. Development of AI-Enabled, Cost-Effective Technologies for Transforming Inland Aquaculture Productivity for Small-Scale Producers
  12. Development of AI-Driven Solutions for Accelerated Crop Breeding

  • Proposals must be collaborative, demonstrating strong expertise in both core Sciences or Engineering and AI, and must involve multi-investigator or multi-institutional consortia. Minimum one Startup/MSME/Industries/ Global Capability Centre (GCC), international entity, hospital or non-profit organization/ Translational partner is mandatory for the proposal.
  • Proposals relying solely on pre-2020 "black box" machine learning approaches (e.g., basic machine learning and regression models, shallow neural networks, or standard convolutional/recurrent neural networks (CNN)/(RNN) pipelines) will not be prioritized for support. Proposals are expected to use modern AI methods (post-2020) that reflect the state of the art in scientific applications, transfer learning or emergent properties etc. Fine tuning of open source state of art foundation models is also encouraged using specialized data sets.
  • Research grants of up to Rs 30 Crore for a period of 3 years may be awarded, inclusive of GPU usage costs. In rarer cases, upto Rs 50 Crore will also be considered, commensurate with the projected deliverables and impact of the proposal.
  • The budgetary provision for GPU usage must not exceed 70% of the total project cost.
  • GPU usage will be supported only through MeitY's GPU-as-a-Service; purchase of GPUs or other HPC equipment will not be funded.
  • Funding will cover Research Personnel (JRFs, SRFs, RAs/National Post Doctoral Fellows (NPDFs), Project Scientists etc.), AI/cloud compute hours, software tools, datasets, and experimental rigs. Additional allowable costs include travel, contingency, and institutional overheads as per ANRF norms.
  • The number of research personnel, as well as the provisions for consumables, travel, and contingency, should be realistic, reasonable, and adequately justified with detailed rationale. Unrealistic or excessive budgetary provisions will not be supported.
  • Co-funding or cost-sharing from other non-governmental sources (Industry, CSR, philanthropy, or other sources) is encouraged in the proposal. However, the ANRF IP policy and the ANRF open License policy will be applicable in all cases and no licence fee is payable under the ANRF Open License. Evaluation will be based upon technical merit only. Any top-up funding received after approval of the project from any source must be declared to ANRF.
  • Funding may also cover on-demand HPC services through National Supercomputing Mission, to support experimental validation and hybrid science-in-the-loop approaches.
  • Proposals with high capital cost requirements will not be supported. PIs should not propose high-capital cost (more than 1 Cr) in the proposal. However, this condition is not applicable to the two specific challenges—Programmable Laboratories and Robotics.
  • Duration of the projects shall not exceed 3 years.
  • Collaboration: Startup/MSME/Industries/ Global Capability Centre (GCC), international entity, hospital or non-profit organization/ Translational partner are invited to participate in the mission as a collaborating partner with academic institutions/ R&D labs and can aim to leverage open-source outputs of the mission to drive their innovation. No financial support will be provided for industry/MSME/startups/GCC/ international entity by ANRF in this mission.
  • Minimum one Startup/MSME/Industries/ Global Capability Centre (GCC), international entity, hospital or non-profit organization/ Translational partner is mandatory for the proposal. They can be a partner with financial contribution or without financial contribution but the role and contribution of the Startup/MSME/Industries should be defined in the proposal.

a. A researcher who has an sanctioned project as a PI in the previous call of MAHA AI for Science and Engineering mission is eligible to apply in this call.

  • Project proposals are invited in consortium mode with atleast two funding eligible institutes, bringing together multiple Principal Investigators (PIs) and institutions/laboratories from academia, research organizations, industry, and startups. At least one CO-PI from a different eligible institution should be involved in the proposal. An Honorary PI does not count towards the minimum. In addition, every proposal must include at least one translational partner.

b. Every PI and CO-PI should have a clear role, contribution, budget allocation & deliverables.

c. Each proposal must be submitted by a lead institution and will be headed by a PI.

d. The PI should be from an academic institution or a National Research Laboratory or from a Private research labs having a valid DSIR - SIRO recognition, and must hold a regular position in the institution.

e. Applicants (PI/Co-PI) must be Indian citizens or OCI holders.

f. Applicants (PI/Co-PI) must have a Ph.D. in Science, Mathematics, Engineering, or relevant Social sciences (for PI in quantitative social sciences) or M.D./M.S./M.D.S./M.V.Sc. degree holders.

g. PIs nearing superannuation may apply if supported by a Co-PI from the same institution with at least three (3) years of service remaining at the time of submission. Fellows under INSPIRE, Ramanujan, and Ramalingaswamy schemes may participate as Co-PIs and having atleast (3) years of fellowship remaining at the time of submission.

h. Each proposal must have a PI and may include up to a maximum of six Co-PIs. This provision is intended to support the formation of strong, interdisciplinary, and multi-institutional research teams, to achieve target outcomes.

i. It is mandatory that Co-PI names are reflected in the main page of the pre-proposal and full-proposal. In case the names does not reflect on the main page but given in the Other Technical Documents (OTD), then the proposal will not be considered.

j. The person from Industry, startups, international faculty/researcher/industry can formally be an "Honorary PI" in collaboration with a PI in India, but the role and contribution of Honorary Investigator should be defined in the proposal. An Honorary PI must be a technical person. Honorary PI may not directly use the budget and they cannot be a PI or CO-PI.

k. Under the Mission, a researcher is eligible to submit only one proposal during a given call either as a PI or as a Co-PI.


  • The lead institution will be responsible for the financial and administrative management of the project.
  • Post selection of the project, funds will be allocated to the lead institution, which will in turn be distributed to other academic/ R&D lab partners. However, distribution of funds has to be provided to ANRF for prior approval.
  • Collaboration: Startup/MSME/Industries/ Global Capability Centre (GCC), international entity, hospital or non-profit organization/ Translational partner are invited to participate in the mission as a collaborating partner with academic institutions/ R&D labs and can aim to leverage open-source outputs of the mission to drive their innovation. No financial support will be provided for industry/MSME/startups/GCC/ international entity by ANRF in this mission.

Each supported project must produce either an open-source model or an open-source dataset or its combination thereof, as its primary deliverable.Every proposal should include four mandatory dimensions:

  1. Technical Efficacy - accuracy, speed, and robustness measured on peer-reviewed benchmarks or, where those are absent, on pre-agreed data;
  2. Open-Science Contribution - code, checkpoints, and datasets released under approved licenses, together with reproducibility scripts
  3. Technology Readiness - attainment of TRL milestones aligned with the project's declared pathway to deployment.
  4. The PIs/Co-PIs must commit to releasing intermediate artifacts under approved open-source licenses.

The details of the licence can be found here.

  • Information to be provided for pre-proposal

Section A: (maximum 3 pages): State of art, Scientific merit and novelty and advancement in existing knowledge, Objectives, Methodology, Technical efficacy benchmarks including TRLs, Planned open-science contributions, Deliverables, Impacts, and milestones with a clear deployment pathway, Schematic diagram.

Section B: Budget Requirements

Part I -Proposed GPU usage requirements and envisaged costs, with technical justifications (maximum 1 page).
Principal Investigators (PIs) can calculate the usage costs through the India AI Compute portal.

Part II - Details of other costs (Non-recurring, Consumables, Travel, Contingency, Research Personnel, and Overheads) (Maximum 1 page).

  • Full proposals will be invited by ANRF, based on the evaluation of the pre-proposals.
  • The proposals will be evaluated by a domain-specific Technical Advisory Committee (TAC), and applicants may be invited for presentations or discussions as part of the selection process.

All proposals submitted under the AI-SE Mission must be entirely original in both concept and content, reflecting the applicant's own research ideas, methodologies, and planned activities. Proposals found to contain any uncredited or unattributed copied content, whether from published literature, online sources, or previously submitted work, will be summarily rejected without further review.


Proposals must be submitted through www.anrfonline.in will be evaluated under ANRF's standard procedures, aligned with the implementation strategies of this Mission. Applicants should carefully review the detailed PI guidelines on the portal to ensure full compliance with submission requirements and formats.


Eligibility

 

Q1: Who can apply as a Principal Investigator (PI)?

A1: The PI must be an Indian Citizens or OCI holder. The PI must hold a regular position in an Indian academic institution or national research laboratory, with a Ph.D. in Science, Mathematics, Engineering, Social Sciences (quantitative AI), or equivalent medical degree (M.D./M.S./M.D.S./M.V.Sc.)

 

Q2: Can a PI nearing retirement apply?

A2: Yes, but only if supported by a Co-PI from the same institution who has at least 3 years of service remaining.

 

Q3. Can startups/GCC/International entity and industry partners apply as a lead Institution or a researcher from any of them apply as a PI or Co-PI?

A3: No, startups/GCC/International entity and industry partners can not apply as lead Institution or a researcher from any of them can not apply as a PI or as Co-PI. Startups, industry, GCCs, international institutions can be a collaborators with academic or R&D institutions. They are welcome to contribute funding in-cash or in-kind resources. And the technical collaborator(s) with clear role and contributions are welcome to be listed as a Honorary PI. However, they cannot receive direct funding from ANRF but may leverage open-source outputs, and openly licensed artifacts from the mission.

 

Q4: Can a PI submit a proposal individually?

A4: No, the PI has to submit a proposal in collaboration with other Co-PIs and other Institutions. Atleast two funding eligible Institutions must be involved in a proposal. An Honorary PI does not count towards in this minimum.

 

Q5: Will international collaborators be encouraged to contribute without any financial obligations from either end?

A5: Certainly. If accomplished international researchers wish to collaborate with the PI/Co-PIs to contribute to the project, they are welcome, without any financial obligation from ANRF.

 

Q6: Is a prior clearance (Ethical, biosafety, animal, humans, etc) required at the time of submission of proposals?

A6: The clearances may be submitted after approval of the proposal for funding.

 

Q7: Who can serve as a Co-PI in a consortium proposal?

A7: Faculty/scientists from eligible institutions with relevant expertise/complementary expertise can serve as Co-PIs.

 

Q8: What is the eligibility of Co-PI?

A8: The Co-PI must hold a regular position in an Indian academic institution or national research laboratory, with a Ph.D. in Science, Mathematics, Engineering, Social Sciences (quantitative AI), or equivalent medical degrees (M.D./M.S./M.D.S./M.V.Sc.).

 

Q9: Can a PI submit more than one proposal under the same call?

A9: A researcher can not submit more than one proposal either as a PI or as a Co-PI.

 

Q10: Are ad-hoc, contractual, or temporary faculty eligible to apply?

A10: Yes, Ad-hoc, contractual or temporary faculty can apply in a project as an honorary investigator or as a collaborator not as a PI or as a Co-PI.

 

Q11: Can applicants without institutional affiliation apply?

A11: No. Applicant should be affiliated with a recognized institute/University.

 

Q12: Can multiple proposals be submitted from the same institution?

A12: Yes. Institutions can submit multiple proposals from different PIs.

 

Q13: Is there a limit on the number of Co-PIs in a consortium?

A13: Yes. Up to 6 Co-PIs are allowed.

 

Q14: Is an endorsement letter required for each PI / co-PI?

A14: Yes. There is no requirement of any documents during the pre-proposal submission stage, however institution endorsement/ certificate from the PI/Co-PI and other approval will be required during full proposal submission. The pre-proposal should be shortlisted for full proposal submission.

 

Q15: Can a PI change their host institution after submission?

A15: Not at pre-proposal stage. This is permitted only after formal approval of ANRF.

 

Q16: Can two PIs from the same institution submit separate proposals?

A16: Yes, if they are distinct and unrelated proposals.

 

Q17: Are autonomous institutes under central/state governments eligible?

A17: Yes, fully eligible.

 

Q18: Are private universities eligible to apply?

A18: Yes, if they are UGC/AICTE-recognized.

 

Q19: Are private R&D labs eligible to participate?

A19: Yes, they are eligible. They must have DSIR-SIRO recognition.

 

Q20: Are foreign nationals working in Indian institutions eligible to apply?

A20: Yes, if they hold full-time appointments and residence permits.

 

Q21: Is it mandatory to have an AI researcher along with domain experts?

A21: Yes. It is mandatory to include an AI researcher in the team. Without AI researcher, proposal will not be considered. AI Researcher means a person with demonstrated expertise in core or applied AI and data sciences, with proven experience in developing, implementing or deploying AI/ML models, algorithms, tools and methodologies for scientific and engineering applications. He/She Should have experience and contributions in modern post-2020 AI models, tools and harnesses etc.

 

Q22: What is the meaning of Consortia?

A 22: A consortia comprising a PI and Co-PIs from at least two different funding eligible institutions. An Honorary PI does not count towards this minimum. In addition minimum one Startup/MSME/Industries/ Global Capability Centre (GCC), international entity, hospital or non-profit organization/ Translational partner is mandatory for the proposal. All members of the consortia must have clarity of roles and contributions in the proposal.

 

Q 23: Is co-funding or cost-sharing from other non-governmental sources (Industry, CSR, philanthropy, or other sources) or top up post sanction is mandatory?

A23: No, Co-funding or cost-sharing from other non-governmental sources (Industry, CSR, philanthropy, or other sources) or top up post sanction is not mandatory but encouraged in the proposal. Any such funding received after award must be declared to ANRF. The ANRF IP policy and the ANRF open license will be applicable in all cases and no licence fee is payable under the ANRF Open License.

 

Q24: Is a translational partner mandatory in the proposal?

A24: Yes, Minimum one Startup/MSME/Industries/ Global Capability Centre (GCC), international entity, hospital or non-profit organization/ Translational partner is mandatory for the proposal. They can be a partner with financial contribution or without financial contribution but the role and contributions of the partner towards translation or commercialisation must be clearly stated in the proposal.

 

Q25: Should translational partner be required to make a financial contribution to the proposed project?

A25: No, translational partner does not require to make a financial contribution to the proposed project but role and contribution of translational partner should be mentioned in the proposal.

 

Q26: Whether a foreign company or a Global Capability Center can be a collaborator in a proposal?

A26: Yes, a foreign company or a Global Capability Center can be a collaborator in a proposal.

 

Proposal Submission Process

 

Q27: Is the call structured as pre-proposal followed by full proposal?

A27: Yes, it is a two-stage process. First pre- proposals will be evaluated and only shortlisted pre-proposal will be invited for full proposal submission.

 

Q28: What are the mandatory documents required at the pre-proposal stage?

A28: Other Technical Details (OTD) as per format only.

 

Q29: Is a detailed budget required in the pre-proposal?

A29: No. Only a high-level budget summary is needed as per the OTD format during preproposal submission. However, detailed budget with breakdown to each participating institution should be proposed at full proposal submission.

 

Q30: Can applicants edit or revise the proposal after submission?

A30: No. Once submitted, it cannot be edited.

 

Q31: Is it mandatory to submit a pre-proposal by two or more institutions?

A31: Yes, through the consortium model.

 

Q32: Can the PI add or replace Co-PIs after submission?

A32: No, PI can not add or replace Co-PI after proposal submission.

 

Q33: Can a new Co-PI be added in the full proposal submission?

A33: Yes, a new Co-PI may be added in the full proposal submission only if TPC recommends it during pre-proposal evaluation.

 

Q34: Is it mandatory to submit a Gantt chart at the pre-proposal stage?

A34: Not mandatory but recommended.

 

Q35: Is a Letter of Intent (LoI) required from translational partners?

A35: Yes, at the time of submission of full proposal.

 

Q36: Can international collaborators be included?

A36: Yes. They can participate as a collaborators or as an Honorary investigators. An Honorary PI cannot be a PI or Co-PI and receives no direct funding from ANRF; however, the proposal does not entail any funding to international collaborators.

 

Q37: Can a proposal be withdrawn after submission?

A37: Yes, with a written request through the online portal.

 

Q38: Is it mandatory for all consortium partners to register on the portal?

A38: Yes. All participating institutions must register on the ANRF portal.

 

Q39: Can a PI change the thematic vertical after submission?

A39: No. It can not be changed.

 

Q40: Is plagiarism checked during proposal evaluation?

A40: Yes. A high similarity index may lead to rejection.

 

Themes & Scope (Research Areas)

 

Q41: What thematic verticals are included under AI-SE?

A41: The AI-SE Mission covers four programme areas: (i) AI for Science and Science of AI; (ii) AI for Engineering, with emphasis on Engineering Design and Accelerated Materials Development; (iii) AI for Earth, Atmosphere and Ocean Sciences; and (iv) AI for Bio and Life Sciences. Proposals are invited through two approaches: Category A open calls and Category B defined challenge statements.

 

Funding & Budget

 

Q42: Who will fund the projects under the AI-SE Mission?

A42: The primary funding for projects under the AI-SE Mission will be provided by ANRF. MeitY will partner in the program by providing GPU resources through its India AI Mission. Additionally, partner departments such as MoES, DBT, MNRE and DRDO will support or co-fund projects alongside ANRF within their respective verticals, in coordination with MeitY.

 

Q43: What is the maximum funding available?

A43:

  • Up to Rs 30 Crore for 3 years.
  • In exceptional cases, up to Rs 50 Crore may be awarded.

 

Q44: What costs are covered under the grant?

A44: The funding covers:

  • Research personnel (JRFs, SRFs, RAs, NPDFs, Project Scientists)
  • GPU/cloud compute hours (via MeitY's GPU-as-a-service)
  • Software tools, datasets, experimental rigs
  • Consumables, travel, contingency, and institutional overheads (As per ANRF norms)

 

Q45: Can I purchase GPUs with project funding?

A45: No. GPU usage will only be supported through MeitY's GPU-as-a-service. Direct purchases of GPUs or HPC systems are not allowed.

 

Q46: Is there a cap on GPU usage costs?

A46: Yes. GPU usage cannot exceed 70% of the total project budget.

 

Q47: Are high-capital projects (like new HPC clusters) supported?

A47: No. Proposals with heavy capital expenditure will not be supported. The proposed budget under capital budget should not more than 1 Cr. However, this condition is not applicable to the two specific challenges - Programmable Laboratories and Robotics.

 

Q48: How can I calculate the GPU usage charges?

A48: The GPU usage charges can be calculated through the India AI mission's AI Compute portal (Link: https://compute.indiaai.gov.in/indiaaipricecalculator).

 

Q49: Can manpower be hired under the project?

A49: Yes. as per ANRF norms. The role of each manpower should be justified in detail.

 

Q50: Is data procurement allowed?

A50: Yes, with clear justification.

 

Q51: Are travel expenses supported?

A51: Yes, for project-related travel. Travel cost must not be proposed more than 5 lakhs for each participating institute.

 

Q52: Are international visits allowed?

A52: Yes, as per ANRF norms.

 

Q53: Is contingency allowed?

A53: Yes, as per ANRF norms. Contingency cost must not be proposed more than 5 lakhs for each participating institute.

 

Q54: Are overhead charges applicable?

A54: Yes, as per ANRF norms.

 

Q55: Is a financial contribution from the translational partner required?

A55: No. A financial contribution is not mandatory. A contribution, financial or non-financial, is encouraged, and the role and contributions of the partner must be clearly defined in the proposal.

 

Q56: Are consultancy or honorarium charges allowed?

A56: No, consultancy or honorarium charges are not allowed

 

Industry & Startup Participation

 

Q57: Is an industry partner mandatory?

A57: Minimum one Startup/MSME/Industries/ Global Capability Centre (GCC), international entity, hospital or non-profit organization/ Translational partner is mandatory for the proposal. All members of the consortium must have clarity of roles and contributions in the proposal.

 

Q58: What types of industries are eligible?

A58: Startups, MSMEs, large firms, and domain-relevant companies.

 

Q59: Can startups join a consortium?

A59: Yes. Startups can participate as collaborators/ Honorary investigators. A technical person from a participating startup may be listed as an Honorary PI, who cannot be a PI or Co-PI and receives no direct funding from ANRF.

 

Q60: Can startups apply directly as PI?

A60: No. Only faculty/ scientists from academia/ research labs can apply as PI/ Co-PI.

 

Q61: Are industry partners eligible for funding?

A61: No, The program does not entail funding to Industry Partners/Startups.

 

Q62: What documents are needed from the translational partner?

A62: LoI/Support Letter/MoU at the time of submission of full proposal.

 

Q63: Can multiple industry partners be included?

A63: Yes

 

Q64: Can foreign industry join consortia?

A64 Yes, as collaborators/ Honorary investigators. A technical person from such an entity may be listed as an Honorary PI.

 

Q65: Can industry provide datasets or infrastructure?

A65: Yes, this is encouraged.

 

Q66: Is it mandatory to have an AI person along with domain person in the proposal?

A66: Yes, this is an AI mission, therefore, an AI person is mandatory with domain researchers in the pre-proposal. Without AI person, the proposal will be rejected.


Proposals & Deliverables

 

Q67: What must each funded project deliver?

A67: Each project is expected to deliver:

  • An open-source model, dataset, or both
  • Technical benchmarks (accuracy, speed, robustness)
  • Open-science contributions (code, checkpoints, reproducibility scripts)
  • Clear Technology Readiness (TRL) milestones, if any.
  • Contributions to Track II (benchmarks or open-source models)

 

Q68: Are proposals based on older machine learning methods admissible?

A68: No. Proposals relying only on pre-2020 "black box" ML approaches (basic regression, shallow neural networks, CNN/RNN pipelines) will not be prioritized. Applicants must use modern, state-of-the-art AI methods (post-2020), such as foundation models, transfer learning, domain adaptation, or physics-informed learning.

 

Q69: Are projects on AI for engineering processes admissible?

A69: Yes. The goal of the project is open AI models for key chip design processes, or associated creation of open data sets, i.e. it is formulated as a direct modelling of engineering, then it could be admissible. Please note that several aspects of engineering: mass flow, heat flow, fluid flows, or P&ID diagrams for chemical processes etc could be directly modelled in AI in different ways, and ultimately leading to open digital twins. While we have given several examples, our intent is not to be restrictive. However we expect applicants to justify what open AI model (that directly models science or an engineering process) or open data set is being created in the proposed application.

 

Q70: What is the format for a pre-proposal?

A70:

  • Section A: State of art, Advancement from existing knowledge, Objectives, methodology, benchmarks, planned open-science contributions, deliverables, Impact and milestones with a clear deployment pathway (maximum 3 pages).
  • Section B: Budget (separate budgets for (a) GPU usage and (b) other costs) (maximum 2 pages)

 

Q71: When to submit a full proposal?

A71: A full proposal should be submitted only if your pre-proposal is selected. Pre-proposals will undergo a preliminary screening to assess their alignment with the mission's scope and objectives, as well as their technical merit and potential impact. Only those pre-proposals that pass this evaluation will be invited to submit a full proposal.


Policies & Compliance

 

Q72: Under what license must outputs be released?

A72: All outputs must be released under the ANRF Open License (adapted from MIT), ensuring open access, ethical use, and global interoperability.

 

Q73: Does ANRF have a Conflict of Interest (CoI) policy?

A73: Yes, ANRF strictly follows the CoI policy.

 

Q74: Can the PI add or replace co-PI at the time of full proposal submission?

A74: No, the PI cannot add or replace co-PI at the time of proposal submission unless advised by the selection committee.