AI-Genomics National Workshop 2026 - Reimagining Biology through AI and Big Data

AI-Genomics Workshop 2026 
Reimagining Biology through AI and Big Data

A national-level AI-Genomics workshop designed for the next generation of biologists, researchers, and data-driven professionals.

Learn AI fits into genomics, and what skills employers actually want?

JOIN US LIVE ON 24th JAN 2026 | 10:00 am IST

In 2026, genomics without AI is incomplete, and AI without biology is meaningless.

The AI‑Genomics Workshop 2026 is a high‑impact national‑level training designed to help students, researchers, and professionals understand how artificial intelligence is actually transforming genomics beyond buzzwords and hype.

This workshop bridges biology, big data, and AI, showing how real genomics datasets are analyzed, where AI truly adds value, where it fails, and what skills matter most for careers in 2026.

WORKSHOP DETAILS:

• Date: 24th January 2026
• Time: 10:00 AM – 3:30 PM (IST)
• Mode: Online | Live Interactive Session
• Recording access will be given for 5 Days.
• Get Workshop Completion certificate (Soft Copy)

Who Should Attend?

• Life Science & Biotechnology students
• Bioinformatics & Computational Biology learners
• Genomics & NGS professionals
• Data scientists interested in biology
• Researchers transitioning to AI‑driven biology
• Anyone curious about AI + Genomics careers

What You Will Learn?

By the end of this workshop, participants will:

• Understand why genomics is a big‑data problem, not just biology
• See real NGS datasets and understand their structure
• Learn where AI works in genomics and where it does not
• Experience AI‑assisted variant prioritization & expression analysis
• Explore AI‑driven discovery use cases in disease & drug development
• Gain a clear 6‑month skill roadmap for AI‑Genomics careers

Workshop Agenda & Modules

10:00 – 10:10 AM | Opening & Context Setting

Host Welcome & Overview

• Why genomics alone is no longer enough in 2026
• Why AI without a biological context fails
• What participants will actually be able to do by the end
• Session roadmap: Data → AI → Applications → Careers
• Speaker introductions

Host: Mrs. Urmimala

Module I | 10:00 – 11:15 AM

Genomics at Scale: From Sequencers to Big Data

Core Concepts

• Evolution of genomics: Microarrays → NGS → Single‑cell → Spatial Omics
• Why genomics is fundamentally a big‑data challenge

Types of Genomics Data

• Whole Genome & Exome Sequencing
• RNA‑Seq & Single‑cell RNA‑Seq
• Epigenomics: ATAC‑seq, ChIP‑seq

Data Reality Check

• Dominant file formats: FASTQ, BAM, VCF
• Why traditional statistics fail at scale
• Challenges: data size, noise, interpretation

Live Walk‑through

• Exploring a real NGS dataset
• Understanding raw sequencing data
• Basic QC visualization (before AI is applied)

Guest Speaker: Subhashree Devasenapathy

Module II | 11:15 AM – 12:30 PM

Where AI Actually Fits in Genomics

• ML vs Deep Learning vs Classical Bioinformatics
• Real AI use‑cases in genomics

Key Applications

• Variant calling & prioritization
• Gene expression prediction
• Disease risk prediction
• Functional annotation of unknown variants

Interactive Comparison

• Same dataset analyzed:

  • With classical bioinformatics

  • With ML‑based approaches

• Participants identify differences

Live Demo / Guided Walkthrough

• AI‑assisted variant prioritization or
• ML‑based gene expression clustering

Faculty: Dr. Nilofer

🍽️ 12:30 – 1:00 PM | Lunch Break

Module III | 1:00 – 2:00 PM

Reimagining Biology: AI‑Driven Discovery

High‑Impact Use Cases

• Disease genomics & precision medicine
• Genomics‑led drug discovery
• Multi‑omics + AI integration

Case Studies

• AI in rare disease diagnosis
• AI‑driven target identification
• Integrating genomics + clinical data
• Population genomics & personalized medicine

Limitations of AI in Biology

• Where AI fails in genomics
• Bias, overfitting & annotation errors
• Why biological expertise remains critical

Do‑Along Guided Activity

• Input genomics data
• Apply an ML model
• Interpret biological meaning (No heavy coding—focus on logic & interpretation)

Faculty: Dr. Elamathi

Module IV | 2:00 – 3:00 PM

Careers in AI‑Genomics: Skills That Actually Get You Hired

Career Roles

• AI‑Genomics Specialist
• Bioinformatics Analyst
• Genomics Data Scientist

Skill Stack Breakdown

• Must‑have biology knowledge
• Must‑have computational skills
• Optional but powerful AI skills
• Tools vs concepts (what not to obsess over)
• Projects vs certificates — the hard truth

6‑Month Action Roadmap

• What students should do in the next 6 months
• How researchers can stay relevant by 2026

Faculty: Dr. Bhupender

Module V | 3:00 – 3:30 PM

Live Q&A Session

• Career transition doubts
• Skill roadmap clarification
• Research & industry questions

Moderated by: Mrs. Urmimala

Panel: All Speakers

Faculty & Speakers

• Mrs. Urmimala – Host & Moderator
• Subhashree Devasenapathy – Genomics Data & NGS Expert
• Dr. Nilofer – AI & Machine Learning in Genomics
• Dr. Elamathi – AI‑Driven Biological Discovery
• Dr. Bhupender – AI‑Genomics Careers & Skill Strategy

Certification - All participants will receive a Certificate of Participation upon successful attendance.

Why This Workshop Is Different?

• No hype real genomics data & real AI use‑cases
• Focus on thinking, interpretation, and decision‑making
• Career‑oriented, industry‑relevant guidance
• Ideal for both students and working professionals

REGISTER NOW

Seats are limited to ensure interaction and quality learning.

👉 Secure your spot for the AI‑Genomics Workshop 2026 and future‑proof your biology career.