I am currently pursuing an MSc in Bioinformatics with a strong interest in: Computational Drug Discovery, Molecular Dynamics Simulations, Structural Bioinformatics, Systems Biology & Network Biology. My work primarily focuses on combining computational biology, molecular modelling, and data-driven analysis to understand biological systems and identify novel therapeutic insights. I enjoy developing reproducible computational workflows, bioinformatics pipelines, and research-oriented tools that bridge biological data with meaningful interpretation. I am particularly fascinated by how protein dynamics, signaling networks, and multi-omics interactions contribute to complex disorders such as neurodegenerative diseases and cancer. Outside of research and academics, I enjoy reading books, clicking photos, making videos, and learning instruments.

• Develop reproducible bioinformatics pipelines and computational workflows for analyzing sequence, structure.
• Apply molecular dynamics simulations, structural bioinformatics, and systems biology approaches to better understand disease mechanisms, protein dynamics, and therapeutic targeting.
• Contribute toward computational drug discovery and rational therapeutic design, particularly in areas related to neurodegenerative disorders and complex disease biology.
• Explore the integration of AI/ML with biological modelling and molecular simulations for predictive analysis, hypothesis generation, and data-driven discovery.
• Promote clarity, reproducibility, collaboration, and open scientific workflows through well-documented code, scalable pipelines, and research-focused development.
• Continuously grow at the intersection of computational biology, molecular simulation, and systems-level biological analysis while contributing to impactful interdisciplinary research.

• Advanced Molecular Dynamics & Enhanced Sampling Methods
• Markov State Models and conformational landscape analysis
• Gaussian Accelerated Molecular Dynamics
• Systems Biology & Network-based Disease Modelling
• Neurodegenerative Disorder Mechanisms and Protein Misfolding
• AI-driven Drug Discovery & Predictive Modelling
• High Performance Computing for biomolecular simulations

• Python (Biopython, Matplotlib)
• R (ggplot2, edgeR, DESeq2)
• Shell scripting (Bash, Linux environment)
• Miniconda

• NCBI (BLAST, GEO, SRA)
• UniProt, PDB, Pfam, PDBsum
• Ensembl Genome Browser
• ExPASy suite (ProtParam, Translate, SwissSidechain)
• STRING (protein-protein interactions)

• PyMOL, Chimera, ChimeraX
• AlphaFold DB
• Modeller
• SWISS-MODEL
• PyRobetta (Baker Lab)
• SWISS-MODEL Structure Assessment
• PROCHECK

• TensorFlow
• Keras
• PyTorch
• Scikit-learn
• Pandas
• NumPy

• Google Colab / Kaggle notebooks
• Cluster computing basics (batch job submission, Linux servers)
• Git & GitHub (version control, project hosting)

• Research collaborations
• Computational biology projects
• Bioinformatics tool development
• Structural biology & MD simulation projects
• Open-source scientific software contributions