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Ethical and Effective Use of Generative AI in Research

Transform Research Workflows with Responsible and Effective Generative AI

★ 4.1 (31 ratings)1–3 Jun 20265.30 PM IST60-90 minutesCertificate
The live sessions are over · get the full recording

About This Course

This 3-day workshop is designed to help researchers, PhD scholars, faculty members, academicians, and professionals understand how Generative AI can be used responsibly and effectively in academic and scientific research. The program introduces learners to the practical applications of AI in literature review, research ideation, academic writing, data analysis, peer review, and research productivity.

The workshop also focuses on ethical concerns such as bias, hallucinations, academic integrity, responsible AI usage, and reproducible workflows. Through hands-on activities using Generative AI tools, Python, Scite.ai, and Jupyter Notebooks, participants will learn how to integrate AI into research workflows while maintaining quality, transparency, and ethical standards.

Aim

To equip researchers and academic professionals with practical knowledge and hands-on skills to use Generative AI ethically, effectively, and responsibly across different stages of the research lifecycle.

Workshop Objectives

  • Understand Generative AI applications in academic research.
  • Use AI tools for literature review and research ideation.
  • Identify bias, hallucinations, and ethical risks in AI outputs.
  • Apply AI for manuscript structuring and academic writing.
  • Perform basic research data analysis using Python.
  • Explore AI-assisted peer review and publication quality checks.
  • Build reproducible research workflows using Jupyter Notebooks.
Next: Day-by-day →

Workshop Structure

Workshop Structure

📅 Day 1: Introduction to Generative AI in Academic Research

  • Overview of Generative AI and its applications in research
  • Ethical implications of AI in research, including bias and hallucinations
  • Role of AI in automating literature reviews and research ideation
  • Challenges in AI reliability and maintaining academic integrity
  • Responsible AI usage to ensure research quality and fairness

🛠️ Hands-on:
Hands-on 1: Literature Review Automation using OpenAI GPT Models / Generative AI Tools
Hands-on 2: Bias Detection and Responsible AI Evaluation

🧰 Tools Covered: OpenAI API / Generative AI Tools

📅 Day 2: AI-Assisted Academic Writing and Research Data Analysis

  • AI for structuring and drafting academic papers
  • Improving writing quality with AI-driven grammar and coherence checks
  • Data analysis and pattern detection using AI tools
  • Visualizing research data through AI-driven techniques
  • Summarizing large datasets for key insights using AI

🛠️ Hands-on:
Hands-on 1: Manuscript Structuring with OpenAI GPT Models / Generative AI Tools
Hands-on 2: Data Analysis with Python

🧰 Tools Covered: OpenAI GPT Models / Generative AI Tools, Python, Pandas, Matplotlib

📅 Day 3: AI in Peer Review, Research Integrity, and Productivity

  • AI’s role in automating peer review and manuscript quality checks
  • Identifying predatory publishing using AI tools
  • Boosting productivity by automating research tasks
  • Building reproducible workflows in research with AI
  • Future trends of AI in collaborative research and ethics

🛠️ Hands-on:
Hands-on 1: Peer Review Automation using Scite.ai
Hands-on 2: Reproducible Workflows with Jupyter Notebooks

🧰 Tools Covered: Scite.ai, Jupyter Notebooks

Who Should Enrol?

  • Undergraduate and Postgraduate Students
  • PhD Scholars and Research Scholars
  • Faculty Members and Academicians
  • Researchers and Scientists
  • Healthcare and Industry Professionals
  • Data Science and AI Enthusiasts
  • Professionals involved in academic writing and publication
  • Anyone interested in the ethical and effective use of Generative AI in research
Next: Dates →

Important Dates

Registration Ends

June 1, 2026
IST 4.30 pm

Workshop Dates

June 1, 2026 – June 3, 2026
IST 5.30 PM

Workshop Outcomes

  • Apply AI-assisted techniques for manuscript structuring and academic writing.
  • Identify bias, hallucinations, and ethical risks in AI-generated outputs.
  • Perform basic research data analysis and visualization using Python.
  • Explore AI-supported peer review and manuscript quality checking.
  • Build reproducible research workflows using Jupyter Notebooks.
  • Use Generative AI responsibly while maintaining academic integrity and research quality.
Next: Mentor →

Meet Your Mentor(s)

Mentor Photo

Prof. Mohit Tiwari

Assistant Professor

more


Next: Fees →

Recording fee

Participants in India

₹2,499

Participants outside India

$50

  • All session recordings
  • Study material
  • Certificate after completion
  • 1-year access

Get the recording

The live sessions of this workshop are over, so the live fees no longer apply. The recordings are being uploaded. They appear in your dashboard as soon as they are ready, and we will e-mail you then.

Next: FAQ →

Frequently asked questions

Will I get the recording?

Yes. Paid participants get the session recordings and study material in their NanoSchool dashboard (My registrations → Recorded Lectures / Study Material).

What if I miss a live session?

Watch the recording in your dashboard and send your questions to the mentor through the support desk.

Do I get a certificate?

Yes, an e-certificate of participation after the workshop, with a QR code anyone can verify and an "Add to LinkedIn" button.

Which fee category applies to me?

Choose the category that matches your current role: Student, Ph.D. Scholar / Researcher, Academician / Faculty or Industry Professional.

How can I pay?

By card, UPI or PayPal on the payment page; international bank transfer is also available there.

What is the refund policy?

See our Returns, Refunds & Cancellation policy: Returns, Refunds & Cancellation policy

Need Help?

We’re here for you!


(+91) 120-4781-217
 WhatsApp +91 99581 61117

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