Environmental Genomics
Computational interpretation of real-world genomic sequence data for environmental biotechnology contexts.
Biotechnology - Bioinformatics - AI for Sustainable Life Sciences
Biotechnology student exploring bioinformatics, environmental genomics, and AI-powered sustainable systems.
KIIT biotechnology dual-degree student working across genomic data, AI/IoT sustainability, and student research leadership.
KIIT University
B.Tech & M.Tech Dual Degree in Biotechnology
CGPA 9.02
Till Semester 5, 2025-26
Research Trainee
Environmental Biotechnology Lab
Patent Contributor
IoT + AI/ML vertical farming system
Founder & President
BIOGENIX - AI & Biotechnology Club
Genomic Data Science
Johns Hopkins University specialisation
Profile
I am interested in biotechnology that does not stay limited to the laboratory. My focus is on how biological systems, computational methods, and intelligent technologies can work together to solve real-world problems in health, environment, and sustainability.
Computational interpretation of real-world genomic sequence data for environmental biotechnology contexts.
Molecular biology and laboratory-method foundations across PCR, electrophoresis, cloning, SDS-PAGE, chromatography, and spectroscopy.
IoT and AI/ML concept integration for vertical farming, sensor automation, and soil health optimization.
Research & Projects
Each card is written in a problem, role, methods, and outcome structure so professors and recruiters can scan quickly without losing depth.
ATG CCA TTA
GCT AAG TCC
TTA CGA GGT
AAC TGG CTA
Undergraduate Research Trainee | Aug 2025 - Present
Contributing to environmental genomics research through data analysis, Python scripting, computational modelling, and interpretation of real-world genomic sequence data.
Context
Environmental biotechnology increasingly depends on the ability to interpret genomic sequence data from complex biological and ecological systems.
Methods
Outcome: Ongoing research exposure at the intersection of environmental biotechnology and bioinformatics.
Student contributor and patent co-author | Sep 2024 - Aug 2025
Worked on a multidisciplinary system integrating sensors, automation, and AI/ML concepts for sustainable vertical farming and soil health optimization.
Context
Modern agriculture needs intelligent, resource-efficient systems for environmental monitoring, automation, and sustainable food production.
Methods
Outcome: Named co-author on Indian Ideation Patent No. 202431099109, issued Dec 27, 2024.
Training participant | Jun 2025
Received practical training in Cryo-EM workflows for macromolecular structural biology.
Context
Structural biology relies on careful sample preparation, vitrification, imaging, and analysis to study macromolecules at high resolution.
Methods
Outcome: Built exposure to advanced research instrumentation and structural biology applications.
Skills
The portfolio groups skills by evidence and context, making the interdisciplinary profile easier to trust.
Intermediate
Research trainee role and Johns Hopkins Genomic Data Science Specialisation
Intermediate
Academic training, lab exposure, and structural biology workshop exposure
Applied exposure
Vertical farming project and patent contribution
Strong
Founder and President of BIOGENIX, presentations, and technical sessions
Leadership
BIOGENIX was created to encourage biotechnology students to explore how AI, computational methods, and laboratory biology can work together. The goal is to build a student-led space where curiosity, technical learning, and interdisciplinary collaboration can grow beyond the classroom.
Proof
Indian Ideation Patent
ID: 202431099109
Patent contribution related to IoT and AI/ML-enabled sustainable vertical farming systems.
The Johns Hopkins University
ID: P4OW4XP6ZOLD
Six-course specialisation on analysing and interpreting data from next-generation sequencing experiments.
Moderna
ID: KV2AU9UU07TQ
Explored molecular principles of mRNA therapeutics and their role in infectious diseases.
Contact