Dr.Gurudeeban Selvaraj, Ph.D. MISV
Assistant Professor in Medical Biotechnology

GS is a highly skilled and self-motivated computational biochemist with over fifteen years of experience in interdisciplinary academic research spanning biotechnology, bioinformatics, and artificial intelligence in biomedical sciences. His expertise lies at the interface of computational biology, cheminformatics, machine learning, and translational biomedicine, with a strong focus on AI-driven drug discovery and biomarker identification.
Currently, GS is actively engaged in developing advanced machine learning and graph neural network (GNN)-based predictive models for pharmaceutical property prediction, including molecular descriptors, bioactivity, ADMET parameters, and target-specific inhibition. He is also working on generative deep learning frameworks for de novo chemical design and AI-assisted therapeutic discovery. In addition, his research portfolio includes AI-based biomarker discovery using multi-omics data, systems biology approaches for metabolic pathway analysis, and ML-guided vaccine and nanotherapeutic development for multidrug-resistant infections and complex diseases. His work integrates transcriptomics, proteomics, metabolomics, molecular docking, molecular dynamics simulations, and explainable AI for precision medicine applications.
GS joined Prof. GHP's lab at Concordia University as a Mitacs Globalink Research Awardee (GRA) in November 2019 and subsequently continued as a Research Associate, where he contributed to computational drug discovery and molecular modeling projects. Before this, GS worked in Prof. Wei’s lab at Henan University of Technology (2017–2019) in a role equivalent to Research Assistant Professor. During this period, he focused on computational oncology, identifying precise cancer biomarkers and potential therapeutic targets using transcriptomic and systems biology approaches. He developed predictive models for mRNA, miRNA, and lncRNA-based biomarkers across multiple cancer types. He also applied quantum chemical calculations using the Gaussian program to investigate structural, electronic, and optical properties of microbial toxins and pharmaceutical compounds. Furthermore, he contributed to immunoinformatics-driven subunit vaccine design against Human Papillomavirus (HPV) using genomics and immunomics datasets.
GS began his academic journey in Tamil Nadu, India. He completed his schooling in Erode district and earned his Bachelor’s degree in Biochemistry from Bharathiar University, strengthening his foundation in biomolecular chemistry. He obtained his Master’s degree in Biotechnology with a minor in Marine Biological Science from Annamalai University. During his Master’s research under Dr. Ram, he investigated plant-derived metabolites and their mechanisms of action in diabetic animal models. He also received advanced analytical training in metabolite characterization at CSIR-CFTRI, Mysore, under Dr. Rao. This early exposure to phytomedicine-based drug discovery shaped his long-term interest in drug–disease mechanisms and translational therapeutics. GS pursued his doctoral research in Biotechnology (minor in Marine Biological Science) at Annamalai University. His Ph.D. work focused on in vivo and in vitro characterization of novel plant metabolites for managing non-insulin-dependent diabetes mellitus (NIDDM), integrating biochemical assays with protein–drug docking studies to elucidate molecular mechanisms. In September 2014, GS joined Dr. Cakmak’s lab at Istanbul Medeniyet University as a Postdoctoral Research Associate. There, he employed molecular biology and biochemical techniques to characterize novel DPP-IV inhibitory peptides derived from microphytes for diabetes management, further strengthening his expertise in translational biotherapeutics. Overall, GS’s career reflects a seamless evolution from experimental biotechnology to AI-driven computational biomedicine, with a strong commitment to developing intelligent therapeutic discovery platforms and precision biomarker systems for complex diseases.

Highlights of research and published articles in Media

Mitacs -  What do researchers do when stuck abroad? Work on a COVID-19 vaccine
Concordia University - Two international postdocs are finding ways to defeat the virus that has left them stranded in Montreal
La Presse - Coincés à Montréal, deux chercheurs en exil planchent sur un vaccin
Montreal Blogs - Scientists In Montreal Have Made 'Good Progress' On A COVID-19 Vaccine
Daily Hive Montreal - Concordia University researchers developing COVID-19 vaccine
​CTV News hosts Professor Gilles Peslherbe regarding potential COVID-19 vaccine
Global News The Concordia researcher developing a COVID-19 vaccine from home
Innovations of the world (July 29, 2021): AI Québec AI drives solutions for COVID-19 vaccine (pages 82-83)
News-Medical Life Science (Jun 1, 2021) :  Scientists explain possible causes of anaphylaxis following mRNA COVID-19 vaccination
Daily pioneer Magazine (December 11, 2018): TN Scientists claim drug breakthrough to cure diabetes
​NewsRx : Diabetes Week, 65, ISSN: 1537-1433, BUTTER® ID: 004604713 (April 30, 2012): Scientists at Annamalai University Target Diabetes ​

​"Action speaks louder than words"

Alma mater :
TN State Board of Govt. High School (SSLC)
TN State Board of Govt. Higher Sec. School (HSC)
Bharathiar University (BSc in Biochemistry)
Annamalai University (MSc & PhD in Marine Biotechnology)
Istanbul Medeniyet University (Postdoc)
Henan  University of  Technology (Postdoc)
Concordia University (Postdoc)
Concordia University (Research Associate)
AVMC&H -VMRF (Current)

Current Position: 
​Assistant Professor in Medical Biotechnology
Strategists Research Initiative
Office address:
Compute Medicine Lab,
Department of Medical Biotechnology
Faculty of Interdisciplinary Studies
AVMC &H, VMRF (Deemed to be University), Kirumampakkam, Puducherry 607402
Email: ​[email protected]

Teaching 

UG-DMBT - Biomolecules and their Interactions
UG-DMBT - Endocrinology and Metabolic Disorders
​PG-DMBT - Immunology and Immunotechnology 
PG-DMBT-EA - Marine Biotechnology - Application of marine chemicals in drug discovery
​VAC-DMBT-01 - AI in Medicine and Medical Biotechnology 

​Research interests

My research is focusing on interdisciplinary science based on the flexible opportunities provided by my academic mentors and available resource in the workstation. I love to learn new things greater and smarter ----"If you want to be powerful, educate yourself"
  • Computational Functional Genomics (transcriptomics, gene ontology, PPI network, functional network and gene set enrichment analysis, machine learning and predictive modeling),
  • Immunomics (immunoinformatics, immune epitope prediction, and vaccine design)
  • Pharmaco-informatics (modeling, docking, MD simulation, QSAR, Library construction, and machine learning)
  • Network Pharmacology (systems pharmacology and drug repurposing) 
  • AI and machine learning-based app development for small molecules and epitopes design 

Countries Visited

Concordia University, Canada (Research) 2019 ;  University of Paris-SUD, France  (Training), 2019 ; Queen Elizabeth Hospital (Research), Hong Kong, 2018 ; Henan University of Technology, China (Research), 2017; Istanbul Medeniyet University, Turkey, (Research), 2014

Experimental & Computational Skills

​High-performance computing (HPC) system

  • Using resources and clusters in Digital Research Alliance of Canada (DRAC) formerly Compute Canada, Calcul Québec and CERMM for different omics and chemical data analytics 

Computational Biology (Multi-omics)

  • R packages                    : Limma, WGCNA, H2O
  • Softwares                      : Cytoscape (plug-ins)
  • Web-interface             : NetworkAnalyst, Galaxy, MG-RAST, QIIME (for NGS data analysis)
  • Sequence analysis    :  MEGA 5.0, BioEdit, Mfold (RNA Structure Prediction)
  • Languages                    : HTML, Python basic
  • Operating Systems  : Windows & LINUX basic
  • Package                          : MS Office and Packages for NGS data analysis
  • Statistical software  : Origin, GraphPad Instat

Computational Chemistry (Drug Design) 

  • Cheminformatics    : RDKit, PaDEL, Deepchem, COSMOtherm, EPI-SUITE, JChem for Excel 
  • Docking                        : AutoDock, Molecular Forecaster, Discovery Studio, PyRx
  • Simulation                  : GROMACS, NAMD (Nanoscale Molecular Dynamics)
  • Visuvalization          : VMD, Discovery Studio, PyMol, Open Babel, LigPlot, Chimera
  • Web-interface           : SwissDock, HADDOCK 
  • QM/MM                        : Gaussian program, Discovery Studio​

Machine Learning

  • Machine Learning : Lazypredict, SVM, RF, XGBoot (Classification and Regression)
  • Deep Learning         : PyToruch (Graph neural networks)
  • Web-platform          : GoogleColab

Laboratory Skills

  1. Biomedical Science: Anti-diabetic, acute toxicity, analgesic, anti-pyretic, anti-oxidant and diabetic foot ulcer on experimental animals (Albino rats, Swiss mice)
  2. Molecular Techniques: Isolation of DNA, PCR Amplification,  Electrophoresis (Agarose, SDS-PAGE), and ELSIA
  3. Microalgae biotechnology: Identification, Culture techniques, Cryopreservation, Stress induced biodiesel feedstock production, Influence of antibiotics and different media components on growth of microalgae
  4. Nanobiotechnology: Nanoparticle synthesis, Characterization and Biomedical applications
  5. Plant tissue culture techniques: Different type of callus induction, Effect of phyto-hormones on direct & indirect method for plantlet regeneration,              Ex vivo transplantation
  6. Environmental Biotechnology: Dissolved oxygen, BOD, COD, Salinity, pH, Isolation of bioflim bacteria
  7. Analytical Techniques for isolation of metabolites from plants :  Auto analyzer for biochemical studies, Chromatographic methods (Column, TLC, HPLC, GC–MS, HPLC-MS) 
  8. Analysis of secondary metabolites from plants 
  9. Bioprocess Techniques  Enzyme production using different sources through the plant pathogenic micro organisms and enzyme kinetics

My Journey to the Best Mountains