About Me

Overview

Welcome! I am Dr. Paul, an Assistant Professor focused on understanding and combating breast cancer through an integrated approach that bridges experimental biology and data science. My research leverages insights gained from both the laboratory bench and computational analysis to explore the complexities of cancer mechanisms.

Foundation in Medical Science & Early Clinical Impact

My scientific journey began not in computation, but firmly rooted in the practicalities of medical science with a Bachelor of Science in Medical Laboratory Technology from the esteemed Christian Medical College (CMC), Vellore. My internship there (1998-1999) provided broad exposure across all diagnostic departments. This foundational training was immediately put into practice during my role as a Medical Laboratory Technologist & Junior Tutor at CSI Kalyani Multispeciality Hospital, Chennai (1999-2002). In this role, I not only gained proficiency across all clinical lab sections but also took on significant leadership responsibilities. I spearheaded initiatives that revolutionized the clinical laboratory, standardizing procedures, introducing a novel SOP for neonatal bilirubin estimation still in use today, achieving top scores in external quality assurance, and ultimately transforming a significant monthly loss into substantial profit – demonstrating a deep understanding of clinical operations and quality management. This period also involved mentoring diploma students, igniting my passion for teaching.

Building Biological Expertise

Seeking to delve deeper into the molecular underpinnings of health and disease, I pursued a Master of Science in Biotechnology at Muthayammal College of Arts and Science. This phase further honed my knowledge of molecular biology, genetics, and biological research techniques, culminating in a dissertation project carried out at the Tropical Botanic Garden and Research Institute (TBGRI), Palode, where I gained further experience in dedicated biological research environments.

Integrating Computational Power

Recognizing the transformative potential of computational methods to analyze the increasingly complex and large-scale data generated in modern biology, I embarked on a PhD in Computational Biology at VIT University, Vellore. This doctoral work was not a departure from my biomedical foundation, but a deliberate integration – equipping me with the quantitative, programming, and analytical skills necessary to extract deeper meaning from biological data. It allowed me to start building the bridge between experimental observation and computational modeling.

The Computational Toolkit: Continuous Skill Development

To effectively operate at the intersection of biology and data science, I believe in continuous learning and have actively cultivated a robust computational skillset. This includes formal training like a Diploma in Computer Applications and extensive self-directed learning and certifications in key areas such as:

• Programming & Development: R, Python, .Net, Visual Basic, JavaScript, Google Go, Google Apps Script, FoxPro

• Data Science & Machine Learning: Machine Learning principles, Google Data Analytics, Statistics with R, Kaggle

• Tools & Platforms: Positron, RStudio, Git/GitHub, Linux, VS Code, Google Colab, SQL Server

• Cloud Computing: Google Cloud Platform fundamentals and tools

See Computer Education

Current Role: Bridging Research, Teaching, and Innovation

Since 2007, I have been contributing to Sri Ramachandra Institute of Higher Education and Research (SRIHER) University, Chennai, progressing from Lecturer to my current role as Assistant Professor. Here, I actively apply my integrated background across several domains:

• Research: My research program focuses on complex biological problems, particularly in breast cancer and infectious disease. I guide PhD scholars and students in projects that explicitly combine wet-lab experiments with computational analysis and data science techniques. This includes investigating the microbiome's influence on breast cancer, utilizing Computer-Aided Drug Design (CADD) for inhibitor discovery, and applying machine learning models to clinical and biological datasets to uncover patterns and make predictions (You can find details on specific projects on the Research Page).

• Teaching: I teach core subjects like Biochemistry, Immunology, Medical Microbiology, and Cell Biology to Biotechnology and Biomedical Sciences students, grounding their learning in fundamental principles while incorporating relevant examples of modern data analysis where applicable.

• Innovation: Drawing on my computational skills, I developed a Stock Management Software using Microsoft Visual Studio to streamline departmental reagent tracking, a tool still utilized and appreciated today.

I also contribute actively to university administration through various committees and have experience organizing scientific conferences and workshops.

Research Philosophy

Today, my research philosophy is centered on the synergy between these domains. I believe that significant advances in understanding and treating complex diseases like breast cancer require researchers who can comfortably navigate both the intricacies of biological systems in the lab and the power of data science at the keyboard. My unconventional path, from the clinical lab through biotechnology and into computational biology, provides me with a unique perspective to train students and conduct research in this exciting, interdisciplinary space.