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Dr Shaban
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Dr Shaban Ahmad, Postdoctoral Researcher at the University of Copenhagen

Dr Shaban Ahmad

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Postdoctoral Scientist, University of Copenhagen, Denmark
Seeking Assistant Professorship to build TCP Group
Publications
100+
Citations1780+
H-index28
Peer Reviews550+
Download Full CV

I develop AI-driven approaches to advance discovery across complex biology — from molecules to medicine and sustainability.

About Me

I am currently a Postdoctoral Scientist at the University of Copenhagen (UCPH), Denmark. Building on a foundation in AI-driven bioinformatics and molecular modelling, I am actively seeking an Assistant Professorship with the clear objective of establishing an independent research group.

My research programme centres on the Translational Computational Pharmacology (TCP) Group. The core aim is to connect AI architectures with real-world clinical and environmental challenges—producing results that are mechanistically interpretable, reproducible, and experimentally actionable.

My expertise spans computational biology—from building AI predictive models (DrLungker, DeepEntXAI, LungXAI) and molecular simulations, to discovering PFAS-degrading enzymes. Trained at institutions across India, Finland, and Denmark, I am building towards leading an independent research group focused on therapeutic innovation.

Academic Qualifications

PhD (AI in Biology)

2025
Jamia Millia Islamia IN

MSc Bioinformatics

2020
Jamia Millia Islamia IN

BSc (Hons) Botany

2018
University of Delhi IN

Honorary Alumnus of NIPER-Ahmedabad.

Scientific Frontiers

AI in Drug Design
Deep generative models for de novo ligand design & hit-to-lead optimisation.
AI in Genomics
Deep learning for variant calling, pathogenicity prediction & GWAS integration.
Molecular Modelling
All-atom MD simulations, conformational sampling & MM/PBSA free energy calculations.
Computational Genomics
Network-based stratification & multi-omics integration.
Phylogenetics
Maximum likelihood inference & Bayesian phylogenomic reconstruction.
Immunoinformatics
Reverse vaccinology, T/B-cell epitope prediction & HLA docking.
Translational Bioinformatics
Biomarker discovery & genotype-phenotype mapping for clinical oncology.
PFAS Biodegradation
Enzyme mining using homology search & structural activity prediction.
Deep Learning
CNNs/RNNs/Transformers for sequence analysis & protein structure prediction.
Computational Chemistry
QM/MM approaches, DFT calculations & electronic structure analysis.

Research Experiences

Postdoc Researcher
FULL TIME
University of Copenhagen DK
June 2025 - Present
Identifying PFAS-degrading enzymes using AI strategies.
Visiting Researcher
VISITING
University of Jyväskylä FI
Jan 2025 - Dec 2025
Predicting Colorectal Cancer susceptibility using AI.
PhD Scholar
FULL TIME
Jamia Millia Islamia IN
Sept 2021 - Feb 2025
AI-based Predictive Modelling and Molecular Enumeration against Lung Cancer.
Project Assistant
FULL TIME
SRM University IN
Nov 2020 - Sept 2021
Drug repurposing against COVID-19 using Machine Learning.
DBT-Studentship
TRAINEE
ICAR - Indian Agricultural Research Institute IN
Jan 2020 - June 2020
Denovo assembly, annotation of Ralstonia solanacearum.
Research Trainee
TRAINEE
International Centre Genetic Eng. & Biotech IN
Jan 2019 - Dec 2019
Analysis of whole and chloroplast genome of Vigna umbellata.
DBT-Studentship
TRAINEE
Hamdard University IN
March 2019 - April 2019
Comparative Genomics of Plasmodium spp.
Open to Collaboration

Interested in discussing a position, collaboration, or joint project? Share the context below and I will get back to you directly.

Key Scientific Contributions

AI Precision Oncology
Developed predictive models like DrLungker and DeepEntXAI using Deep Ensemble Learning and Hybrid CNN-LSTMs. These frameworks accurately classify drug activity and validate multitarget potency against resilient lung cancer variants.
Deep Learning CNN-LSTM Predictive Oncology Drug Discovery Explainable AI
Environmental Biotech & PFAS
Pioneering AI-guided enzyme mining and homology search strategies at UCPH. My current focus is identifying and optimising novel biocatalysts capable of degrading "forever chemicals" (PFAS), promoting sustainable bioremediation.
Enzyme Mining PFAS Degradation Bioremediation Green Biotechnology Sustainability
Advanced Molecular Modelling
Conducted extensive structural analyses through multitarget docking, all-atom MD simulations, DFT, and MM/PBSA free energy calculations to discover polypharmacological candidates for pathogens and tumours.
MD Simulations DFT Calculations Polypharmacology QM/MM
Computational Genomics
Unravelling complex genomic data using WGS/WES processing, variant pathogenicity prediction, and phylogenomic evolutionary mapping to combat diverse pathogens and diseases.
WGS/WES Variant Calling Phylogenomics NGS Data

Highlighted/Recent Publications

| View all articles →

Academic Vision & Group Strategy (TCP Group)

Future Academic Vision

Establishing the Translational Computational Pharmacology (TCP) Group

As an aspiring Assistant Professor, my goal is to establish the TCP Group at the intersection of AI, computational pharmacology, genomics, and sustainable biotechnology. The aim is to create models and workflows that do more than rank candidates: they explain mechanisms, support experimental decision-making, and generate outputs that are scientifically rigorous and practically useful.

This vision is portable and aligned with host institutions focused on precision medicine, biological data science, or environmental sustainability. It brings a recognisable signature: mechanism-aware AI, reproducible pipelines, and collaborative translation from prediction to biological insight.

Mechanism-aware AI Computational Pharmacology Precision Genomics Reproducible Pipelines Sustainable Biotechnology
Research Signature Prediction anchored in mechanism

Every computational result should be interpretable enough to guide validation, not just improve a benchmark.

Academic Mission Discovery plus training

The group should produce strong science while also training students to think across data, structure, and biology.

Long-Term Outcome A durable, collaborative lab identity

TCP should become a recognisable research home with clear themes, strong partnerships, and scalable mentoring.

AI Precision Oncology
  • Developing deep ensemble architectures (DrLungker, DeepEntXAI, LungXAI etc).
  • Integrating Hybrid CNN-LSTMs for high-accuracy drug activity classification.
  • Utilising LIME/SHAP mapping to ensure clinical explainability.
  • Deciphering complex drug resistance mechanisms in mutative cancers.
Multitarget Polypharmacology
  • Designing singular therapeutics to modulate multiple targets concurrently.
  • Targeting key pathway proteins (EGFR, CDK2, STAT3, TrkA, KRAS).
  • Hit-to-lead optimisation of compounds like FEDPN and Imidurea.
  • Reducing clinical toxicity and circumventing acquired drug resistance.
MD & QM/MM Simulations
  • Building High-Throughput Virtual Screening (HTVS) pipelines.
  • All-atom MD trajectory dynamics via Desmond & GROMACS.
  • Employing Density Functional Theory (DFT) calculations.
  • Running rigorous MM/PBSA and MM/GBSA free energy profiling.
Translational Bioinformatics
  • Bridging bench-to-bedside with multi-omics data integration.
  • Driving biomarker discovery from clinical cohorts toward therapeutic application.
  • Correlating complex genotype-phenotype mappings.
  • Stratifying disease networks to drive personalised therapeutic regimens.
Evolutionary Genomics
  • Processing WGS/WES data for precise variant annotation.
  • Utilizing AI frameworks for variant pathogenicity prediction.
  • Mapping phylogenomic evolution (e.g., Vigna umbellata).
  • Analysing domestication genes and sequence analytics.
Precision Biocatalysis & PFAS
  • AI-guided enzyme mining and homology searching for biocatalyst discovery.
  • Engineering resilient microbial enzymes for targeted bioremediation.
  • Predicting structural activity of biocatalysts via AI.
  • Targeting the sustainable degradation of persistent "forever chemicals".

Phase 1: Foundation & Discovery

Years 1-2
  • Infrastructure: Establish high-performance computational GPU clusters and secure omics pipelines.
  • Funding: Strategically target early-career funding including ERC Starting Grants and national fellowships.
  • Recruitment: Build the core team by hiring highly motivated, interdisciplinary PhD scholars and Postdocs.
  • Outputs: Launch the baseline version of our proprietary XAI-driven drug discovery pipeline.

Phase 2: Validation & Expansion

Years 2-4
  • Scaling: Expand polypharmacological deep-learning models to analyse massive, pan-cancer datasets.
  • Validation: Transition from in silico predictions to rigorous in vitro / in vivo validation.
  • Collaboration: Establish cross-disciplinary ties with wet-lab experimentalists and clinical oncologists globally.
  • IPR & Publishing: Publish in high-impact journals and file provisional patents for biocatalysts and drug hits.

Phase 3: Translation & Leadership

Years 4-5
  • Translation: Focus on translating validated models into real-world clinical or industrial applications.
  • Leadership: Establish the TCP Group as a leading international hub for computational pharmacology.
  • Mentorship: Guide and support senior lab members toward their own independent careers.
  • Legacy: Ensure all tools and models are open-source to maximize community and clinical impact.

Funding Logic & Growth Strategy

Funding Logic
  • Pilot data directly supports people and initial validation frameworks.
  • Team members drive robust in vitro / in vivo validation of computational hits.
  • Validated outputs secure larger multi-year European/National programmes.
Partnership Strategy
  • Link funding closely to collaborations that are scientifically additive.
  • Focus heavily on experimental, translational, and infrastructure partners.
  • Target joint industry-academia consortium grants.
Growth Discipline
  • Expand the group responsibly rather than aggressively.
  • Add novel themes and people only when mentorship capacity is secure.
  • Ensure validation bandwidth and overarching strategic coherence.

Team Architecture

  • PI: Directs scientific vision, mentoring standards, and partnership development.
  • Postdocs: Provides method leadership across AI, genomics, and translational themes.
  • Students: Leads work-package-driven projects with clear technical ownership.

Collaboration Model

  • Structural biology, pharmacology, and assay partners for validation.
  • Genomics and disease-focused collaborators for multi-omic interpretation.
  • Environmental biotechnology collaborators for enzyme discovery.

Operating Model

  • Reproducible codebases and shared analysis standards from day one.
  • HPC-enabled workflows for AI and large-scale biological data processing.
  • Open, collaboration-ready outputs to boost external engagement.

The TCP group will not just be a hub for high-impact scientific output; it will be a dynamic, nurturing training ground. Having proudly mentored and guided numerous students globally, I am deeply committed to empowering the next generation of independent, ethical, and innovative researchers.

Teaching & Training Philosophy

Teaching Approach

  • Foster dual competency: conceptually strong and computationally confident.
  • Transition students from passive learning to active problem solving.
  • Utilise real biological data to navigate real uncertainty and scientific trade-offs.

Training Portfolio

  • AI in drug discovery and computational pharmacology.
  • Computational genomics and precision medicine data science.
  • Reproducible workflows, Python/R, HPC usage, and MLOps.

Mentorship Model

  • Structured at the start, independent over time.
  • Provide strong onboarding, shared tools, and clear milestones.
  • Empower trainees to frame their own unique biological questions.

Courses I Can Teach

Basics to Advanced Bioinformatics
UG / Graduate |
From DNA sequence analysis and BLAST to multi-omics integration. Covers NGS quality control, read alignment, variant calling, WGS/WES pipelines, and phylogenomics using R/Bioconductor and Snakemake.
NGS / WGS Variant Calling R / Bioconductor Multi-Omics
Computational Drug Design
UG / Graduate |
Structure-based drug design, molecular docking, virtual high-throughput screening, MD simulations, and free energy calculations. Lab-based practicals using AutoDock Vina, GROMACS, and PyMOL.
Molecular Docking SBDD MD Simulations Virtual Screening
ML in Drug Design
Graduate |
Graph neural networks, QSAR modelling, generative AI for de novo molecule design, and AI-assisted lead optimisation. Hands-on with DeepChem, RDKit, and PyTorch Geometric.
GNNs QSAR Generative AI DeepChem
Machine Learning in Genomics
Graduate |
Supervised and deep learning for genomics, transcriptomics, and epigenomics. Covers SHAP/LIME explainability, Python/scikit-learn practicals, and reproducible MLOps workflows for biological data.
Deep Learning XAI / SHAP Transcriptomics MLOps
AI in Precision Medicine
Advanced / Elective |
AI-guided biomarker discovery, patient stratification, translational omics pipelines, and clinical-to-bench data integration. Seminar-based with real clinical datasets and case studies from oncology and metabolic disease.
Biomarkers Patient Stratification Translational AI Omics Integration
AI in Biological Degradations & Biotech
Advanced / Elective |
AI-guided enzyme engineering, PFAS bioremediation, metabolic pathway modelling, and sustainable biotechnology. Case studies from computational environmental biology and directed evolution research.
PFAS / Enzymes Bioremediation Enzyme Engineering Environmental AI

Core Lab Culture

Collaborative Environment

  • Maintain a strictly flat hierarchy to empower all voices.
  • Ensure seamless dialogue across diverse computational fields.
  • Cultivate psychological safety to foster genuine innovation.

Career Development

  • Establish tailored Individual Development Plans (IDPs) for each lab member.
  • Actively facilitate critical grant-writing workshops.
  • Ensure robust international conference and networking opportunities.

Open Science

  • Maintain a strong commitment to scientific transparency.
  • Adhere strictly to FAIR data and reproducible code principles.
  • Maintain well-documented, public GitHub repositories for all outputs.

Awards & Recognitions

World's Top 2% Scientists
Recognised by Stanford University and Elsevier for citation impact (2025).
Felicitated by Vice Chancellor
Felicitated by Vice Chancellor for academic excellence (2025).
Achievers of the Year
Awarded by University Registrar and Provost, Jamia Millia Islamia (2025).
Best Presentation Award
3rd International Electronic Conference on Cancers (MDPI) (2023).
Best Presentation Award
21st International Conference on Bioinformatics (InCoB), KAUST (2022).
DBT-Studentship Fellowship
Awarded 6-month fellowship at ICAR-IARI (2020).
Best Oral Presentation
Interdisciplinary Science Conference, JMI, New Delhi (2019).
Best Poster Presenter
National Conference on CCSMAP, MRIIRS (2019).
DBT-Studentship Fellowship
Awarded 2-month fellowship at Jamia Hamdard (2019).
1st Prize in Working Model
"PARIVARTAN 2K18", Sri Aurobindo College, DU (2018).
Society Contributions Award
Awarded by WEED (UNESCO) for Greenest Campus Initiatives (2016).
2nd Prize (Quiz/Contest)
Explico Know Your Green in SANJEEVANI, DBC, DU (2016).
Best Poster Award
ICSSR-sponsored National Seminar, Sri Aurobindo College, DU (2016).
Innovation Fellowship
DBC311 Innovation Project Fellowship, University of Delhi (2015).

Patents (IPR)

Granted 01 (German)

Extended-Release Tablet Composition for Multitarget Cancer Therapy

View Details

In Pipeline: 06

05 Indian, 1 US (Drug Molecules Designed During PhD Tenure)

Publications & Scholarly Works

  1. Benchmarking inflammation-nutrition and TyG-related indices for 5-year mortality risk in adults with questionnaire-defined obstructive sleep apnea: a survey-weighted NHANES derivation cohort with multicenter external validation
    Submitted: JTRM-D-26-08634 (2026) (In Pipeline)
  2. DeepEntXAI: A CNN-LSTM and Hybrid, LIME-Based Explainable Framework for Enterobacteriaceae Drug Activity Classification and Efficacy Prediction
    Submitted: CIBM-D-24-06110 (2026) (In Pipeline)
  3. LUNGXAI: A Deep Learning Framework with LIME-based Interpretability for Gene Expression and Classification
    Submitted: INFFUS-D-25-02490 (2026) (In Pipeline)
  4. Blind vs LigSite Docking Identifies Oxanthrazole as a Top Multitargeted Lung Cancer Inhibitor from PubChem BioAssays
    Submitted: IJBIOMAC-D-25-04108 (2026) (In Pipeline)
  1. Natural Products as Therapeutics for Lung and Respiratory Diseases
    SAGE- Natural Product Communications (2026) DOI
  2. Multitarget docking and molecular enumeration reveal DdpMPyPEPhU as a potent modulator of cell cycle, glucocorticoid, and estrogen signalling in breast cancer
    Plos- PlosOne (2026) DOI Data
  3. Multimodal evaluation of Mannose Engineered Poly Lactic Glycolic Acid Nanoparticles with Granulocyte Colony Stimulating Factor Focused Delivery to Bone Marrow for Neutropenia
    Nature- Scientific Reports (2026) DOI
  4. DrLungker: A Deep Ensemble Learning Framework for Predicting Anti-Lung Cancer Compound Activity and Validating Multitarget Potency through WaterMap, DFT, MD Simulations, and MM-GBSA Analysis
    Wiley-Advanced Theory and Simulations (2025) DOI Data Code
  5. Evaluating the Polypharmacological Potential of Cosmetic Preservative Imidurea Against Lung Cancer-Associated EGFR, CDK2, STAT3, BCL2, p53, and ABCB1 Proteins
    Intl. J. Bio. Macromol. (2025) DOI Data
  6. Machine Learning for Genomic Profiling and Drug Discovery in Personalised Lung Cancer Therapeutics
    Journal of Drug Targeting (2025) DOI
  7. Correction: Integrative Computational Approaches Identify Haptoglobin Inhibitors to Modulate Erythrocyte Sedimentation Rate in Trauma-Linked Inflammatory and Haematological Malignancies
    Frontiers in Chemistry (2025) DOI
  8. FDA-approved Levophed as an alternative multitargeted therapeutic against cervical cancer transferase, cell cycle, and regulatory proteins
    Computers in Biology and Medicine (2025) DOI Data
  9. Probing the multitargeted potency of Theodrenaline and its comparative evaluation with Crizotinib against transferase, hydrolase, signalling, and apoptosis-related proteins to overcome lung cancer drug resistance
    Intl. J. Bio. Macromol. (2025) DOI Data- 1 Data- 2
  10. Integrative Computational Approaches Identify Haptoglobin Inhibitors to Modulate Erythrocyte Sedimentation Rate in Trauma-Linked Inflammatory and Haematological Malignancies
    Frontiers in Chemistry (2025) DOI Data
  11. Evaluating the polypharmacological potency of FEDPN from ChEMBL BioAssays against lung cancer EGFR, ALK, TrkA and KRAS proteins
    Intl. J. Bio. Macromol. (2025) DOI Data Code
  12. RCSB Protein Data Bank: Revolutionising Drug Discovery and Design for Over Five Decades
    Medical Data Mining (2025) DOI
  13. Investigating the Inhibitory Effects of Paliperidone on RAGES: Docking, DFT, MD Simulations, MMPBSA, MTT, Apoptosis, and Immunoblotting Studies
    Intl. J. Mol. Sci. (2025) DOI Data
  14. Probing the Role of Coniferin and Tetrahydrocurcumin from Traditional Chinese Medicine against PSAT1 in Early-stage Ovarian Cancer
    PLoS ONE (2025) DOI Code
  15. Molecular Dynamics Simulation and Docking Studies Reveal Inhibition of NF-kB Signalling as a Promising Therapeutic Drug Target for Reduction in Cytokine Storms
    Nature- Scientific Reports (2025) DOI Data
  16. Synthesis, structural elucidation, and antibacterial activities of novel copper(II), cobalt(II), and nickel(II) complexes with a bidentate Schiff base ligand against pathogenic bacteria
    Journal of Molecular Structure (2025) DOI Data
  17. Reporting multitargeted potency of Tiaprofenic acid against lung cancer: Molecular fingerprinting, MD simulation, and MTT- based cell viability assay studies
    Intl. J. Bio. Macromol. (2024) DOI
  18. Integrative Analysis Discovers Imidurea as a dual multitargeted inhibitor of CD69, CD40, SHP2, Lysozyme, GATA3, cCBL, and S-cysteinase from SARS-CoV-2 and M. tuberculosis
    Intl. J. Bio. Macromol. (2024) DOI Data- 1 Data- 2
  19. Deciphering the influenza neuraminidase inhibitory potential of naturally occurring bioflavonoids: An in-silico approach
    Open Chemistry (2024) DOI Data
  20. Meet the Executive Guest Editor of Mini-Reviews in Medicinal Chemistry (Shaban Ahmad)
    Mini-Reviews in Medicinal Chemistry (2024) DOI
  21. Microbial biofilm inhibition using magnetic cross-linked polyphenol oxidase aggregates
    ACS Applied Biomaterials (2024) DOI Data
  22. An Extensive Review on Lung Cancer Therapeutics Using Machine Learning Techniques: State-of-the-art and Perspectives
    Journal of Drug Targeting (2024) DOI
  23. 2-hydrazinobenzothiazole-based derivatives: Synthesis, characterisation, antifungal, DNA binding and molecular modelling approaches
    Journal of Molecular Structure (2024) DOI Data
  24. Structure-based virtual screening, molecular docking, molecular dynamics simulation, and metabolic reactivity studies of quinazoline derivatives for their anti-EGFR activity against tumour angiogenesis
    Current Medicinal Chemistry (2024) DOI
  25. Multisampling-based docking reveals Imidazolidinyl urea as a multitargeted inhibitor for Lung Cancer: An optimisation followed multi-simulation and in-vitro study
    J. Biomol. Struct. Dyn. (2023) DOI Data- 1 Data -2
  26. In-silico and in-vitro studies reveal ziprasidone as a potential aromatase inhibitor against breast carcinoma
    Nature- Scientific Reports (2023) DOI Data
  27. Investigating the multitargeted anti-diabetic potential of cucurbitane-type triterpenoid from Momordica charantia: An LC-MS, docking-based MM\GBSA and MD Simulation Study
    J. Biomol. Struct. Dyn. (2023) DOI Data
  28. Identification of 5-nitroindazole as a multitargeted inhibitor for CDK and transferase kinase in lung cancer: a multisampling algorithm-based structural study
    Molecular Diversity (2023) DOI
  29. Design, synthesis, X-ray crystal structures, anticancer, DNA binding and modelling studies of pyrazole-pyrazoline derivatives
    RSC Advances (2023) DOI Data- 1 Data- 2
  30. Structural-functional analysis and Molecular characterisation of arsenate reductase from Enterobacter cloacae RSC3 for arsenic biotransformation
    3-Biotech (2023) DOI Data
  31. Computational screening and MM\GBSA-based MD simulation studies reveal the high binding potential of FDA-approved drugs against Cutibacterium acnes Sialidase
    J. Biomol. Struct. Dyn. (2023) DOI Data
  32. Structure-Based Design of Novel MAO-B Inhibitors: A Review
    Molecules (2023) DOI
  33. Comparative genomic assessment of members of Genus Tenacibaculum: An exploratory study
    Mol. Gen. Genomics (2023) DOI Data- 1 Data- 2
  34. Synthesis, Single crystal, TD-DFT, Molecular Dynamics Simulation and DNA binding studies of Carbothioamide Analogue
    Journal of Molecular Structure (2023) DOI Data- 1 Data- 2
  35. Comprehensive Computational Studies of Naturally Occurring Kuguacins as Anti-diabetic Agents by Targeting Visfatin
    Chemistry Africa (2023) DOI Data
  36. Comparative insight into Rice chloroplasts genome: Mutational Phylogenomics reveals Echinochloa oryzicola as the ongoing progenitor of rice
    Gen. Res. Crop Evol. (2023) DOI Data- 1 Data- 2
  37. SARS-CoV-2 Variants Show a Gradual Declining Pathogenicity and Pro-Inflammatory Cytokine Stimulation, an Increasing Antigenic and Anti-Inflammatory Cytokine Induction, and Rising Structural Protein Instability: A Minimal Number Genome-Based Approach
    Inflammation (2022) DOI Data- 1 Data- 2 Data- 3 Data- 4 Data- 5
  38. Predictive modelling and therapeutic repurposing of natural compounds against the receptor-binding domain of SARS-CoV-2
    J. Biomol. Struct. Dyn. (2022) DOI Data
  39. Correction to: Novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and other coronaviruses: a genome-wide comparative annotation and analysis
    Mol. Cell. Biochem. (2022) DOI
  40. Macrophage-Targeted Punicalagin Nanoengineering to Alleviate Methotrexate-Induced Neutropenia: A Molecular Docking, DFT, and MD Simulation Analysis
    Molecules (2022) DOI
  41. In silico analysis reveals Quinic acid as a multitargeted inhibitor against Cervical Cancer
    J. Biomol. Struct. Dyn. (2022) DOI
  42. Multitargeted molecular dynamic understanding of Butoxypheser against SARS-CoV-2: An in-silico study
    Nat. Prod. Comm. (2022) DOI
  43. Reporting dinaciclib and theodrenaline as a multitargeted inhibitor against SARS-CoV-2: an in-silico study
    J. Biomol. Struct. Dyn. (2022) DOI
  44. In-silico Screening and Molecular Dynamics Simulation of Drug Bank Experimental Compounds against SARS-CoV-2
    Molecules (2022) DOI
  45. Unveiling the multitargeted potential of N-(4-Aminobutanoyl)-S-(4-methoxybenzyl)-L-cysteinylglycine (NSL-CG) against SARS-CoV-2: A virtual screening and molecular dynamics simulation study
    J. Biomol. Struct. Dyn. (2022) DOI
  46. Hemi-Babim and Fenoterol as Potential Inhibitors of MPro and Papain-like Protease against SARS-CoV-2: An In-Silico Study
    Medicina (2022) DOI
  47. In silico analysis of the ACE2 receptor to find potential herbal drugs in COVID-19-associated neurological dysfunctions
    Nat. Prod. Comm. (2022) DOI
  48. Molecular dynamics simulation and docking analysis of NF-kB protein binding with sulindac acid
    Bioinformation (2022) DOI
  49. Antiviral Potential of Indian Medicinal Plants Against Influenza and SARS-CoV: A Systematic Review
    Nat. Prod. Comm. (2022) DOI
  50. Novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and other coronaviruses: a genome-wide comparative annotation and analysis
    Mol. Cell. Biochem. (2021) DOI
  51. Phytochemical Analysis and Antifungal Activity of Weed Extracts against Rhizoctonia Root Rot in Buckwheat (Fagopyrum tataricum)
    Biopesticide International (2020) DOI
  52. Probing the effect of a plus 1bp frameshift mutation in the protein-DNA interface of the domestication gene, NAMB1, in wheat
    J. Biomol. Struct. Dyn. (2019) DOI
  1. Artificial intelligence in molecular screening: Advances, challenges, and future perspectives.
    Elsevier- Artificial Intelligence in Precision Drug Design (2026) DOI
  2. Artificial intelligence in multi-omics integration for precision drug design.
    Elsevier- Artificial Intelligence in Precision Drug Design (2026) DOI
  3. Deep learning in variant detection and annotation.
    Elsevier- Deep Learning in Genetics and Genomics (2025) DOI
  4. Artificial Bee Colony Algorithms in Gene Expression Studies: A Case Study.
    Springer Nature- Solving with Bees (2024) DOI
  5. Generative AI in Drug Designing: Current State-of-the-Art and Perspectives.
    Springer Nature- Generative AI in Drug Designing (2024) DOI
  6. Beispielhafte Implikationen von naturinspirierten Berechnungsmethoden auf Therapeutika und computergestützte Arzneimittelentwicklung.
    Springer Nature (2024) DOI
  7. Bedeutende Innovationen in naturinspirierten intelligenten Computertechniken zur Identifizierung von Biomarkern und potenziellen therapeutischen Mitteln.
    Springer Nature (2024) DOI
  8. Deep learning in computer-aided drug design: a case study.
    Elsevier- Deep Learning Applications in Translational Bioinformatics (2024) DOI
  9. Application of machine learning-based approaches in stem cell research.
    Elsevier- Computational Biology for Stem Cell Research (2024) DOI
  10. Natural Product-Based Drug Designing for Treatment of Human Parasitic Diseases.
    Springer- Natural Product-based Drug Discovery against Human Parasites (2023) DOI
  11. 5-Nitroindazole against Lung Cancer: A Multitargeted in-silico Molecular Docking and Molecular Dynamics Simulation Study.
    MDPI- Medical Sciences Forum (2023) Link
  12. Multialgorithm-based docking reveals Imidazolidinyl urea as a multitargeted inhibitor for Lung Cancer.
    MDPI- Medical Sciences Forum (2023) DOI
  13. Protein-based Therapeutic Vaccines.
    Springer- Protein-Based Therapeutics (2023) DOI
  14. Nanoinformatics and Nanomodelling: Recent developments in computational nanodrug design and delivery systems.
    Elsevier- Emerging Nanotechnologies for Medical Applications (2023) DOI
  15. Illustrious Implications of NIC Methods in Therapeutics and Computer-Aided Drug Design.
    Springer- Nature-Inspired Intelligent Computing Techniques in Bioinformatics (2022) DOI
  16. Consequential Innovations in NIC Techniques for Biomarkers and Potential Therapeutics Identification.
    Springer- Nature-Inspired Intelligent Computing Techniques in Bioinformatics (2022) DOI
  17. Fundamentals of molecular modelling in drug design.
    Elsevier- Computer Aided Drug Design (2022) DOI
  18. The Incipient Role of Computational Intelligence in Oncology: Drug Designing, Discovery, and Development.
    Springer- Computational Intelligence in Oncology (2022) DOI
  19. From molecules to patients: The clinical applications of biological databases and electronic health records.
    Elsevier- Translational Bioinformatics in Healthcare and Medicine (2021) DOI
  20. Clinical Applications of Next-Generation Sequencing Analysis in Acute Myelogenous Leukaemia.
    T & F- Translational Bioinformatics Applications in Healthcare (2021) DOI
  21. Mitogen-activated protein kinase, plants, and heat stress.
    Springer- Harsh Environment and Plant Resilience (2021) DOI
  22. Exosomes as an emerging nanoplatform for functional therapeutics.
    Elsevier- Handbook on Nanobiomaterials for Therapeutics and Diagnostic Applications (2021) DOI
  23. A review of predictive systems and data models for COVID-19.
    Springer- Computational Intelligence Methods in COVID-19 (2020) DOI
  24. Mobile Technology Solution for COVID-19: Surveillance and Prevention.
    Springer- Computational Intelligence Methods in COVID-19 (2020) DOI
  1. Code and Dataset: DrLungker- Deep Ensemble Learning Framework. Code Data
  2. Code and Dataset: DeepEntXAI- Hybrid Explainable Framework. Code
  3. Code and Dataset: LungXAI- Deep Learning Framework. Code
  4. Code: RMSD-RMSF Plots Code
  5. Code and Dataset: FEDPN Polypharmacology (Lung Cancer) Code Data
  6. Code and Dataset: ChEMBL BioAssays (Lung Cancer) Code Data- 1 Data- 2
  7. Code and Dataset: PubChem BioAssay Code
  8. Code: PSAT1 Screened Compounds (Coniferin and Tetrahydrocurcumin) Code
  9. Dataset: Imidurea Polypharmacology (Lung Cancer) Data
  10. Dataset: Haptoglobin Inhibitors in Haematological Malignancies Data
  11. Dataset: Levophed Multitargeted Therapy Data
  12. Dataset: Theodrenaline vs Crizotinib Data- 1 Data- 2
  13. Dataset: Paliperidone on RAGES Data
  14. Dataset: Inhibition of NF-kB Signalling Data
  15. Dataset: Copper(II), cobalt(II), and nickel(II) complexes Data
  16. Dataset: Imidurea Dual Inhibitor Data- 1 Data- 2
  17. Dataset: Influenza neuraminidase inhibitory potential of bioflavonoids Data
  18. Dataset: Microbial biofilm inhibition (Polyphenol oxidase) Data
  19. Dataset: 2-hydrazinobenzothiazole-based derivatives Data
  20. Dataset: Imidazolidinyl urea Multisampling Data- 1 Data- 2
  21. Dataset: Ziprasidone as aromatase inhibitor Data
  22. Dataset: Cucurbitane-type triterpenoid from Momordica charantia Data
  23. Dataset: Pyrazole-pyrazoline derivatives Data- 1 Data- 2
  24. Dataset: Arsenate reductase from Enterobacter cloacae Data
  25. Dataset: Cutibacterium acnes Sialidase Data
  26. Dataset: Genus Tenacibaculum (Comparative genomic) Data- 1 Data- 2
  27. Dataset: Carbothioamide Analogue Data- 1 Data- 2
  28. Dataset: Kuguacins as Anti-diabetic Agents Data
  29. Dataset: Rice Chloroplasts Genome's Evolutionary Comparison Data- 1 Data- 2
  30. Dataset: SARS-CoV-2 Variants Gradual Declining Pathogenicity Data- 1 Data- 2 Data- 3 Data- 4 Data- 5
  31. Dataset: Predictive Modelling of Natural Compounds (SARS-CoV-2) Data

Conferences & Events

  1. 5-Nitroindazole against Lung Cancer: A multitargeted in-silico molecular docking and Molecular Dynamics simulation study
    3rd International Electronic Conference on Cancers (IECC 2023) | Mar 16-30, 2023
  2. Multialgorithms-based docking reveals Imidazolidinyl urea as a multitargeted inhibitor for Lung Cancer
    2nd International Electronic Conference on Biomedicines | 2023
  3. Multitargeted docking-based simulative understanding of Theodrenaline against lung cancer: an in-silico study
    21st International Conference on Bioinformatics (InCoB), KAUST, Saudi Arabia | Nov 21-23, 2022
  4. In silico study of aromatase inhibitors using computer-aided drug design
    World Congress on Reproductive Health (ISSRF2020), Katra, J&K | Feb 14-16, 2020
  5. Rice Bean (Vigna umbellata) draft genome sequence: unravelling the late flowering and unpalatability related genomic resources
    Young Scientist Conference India International Science Festival (YSC-IISF), Kolkata | Nov 05-07, 2019
  6. Deep learning and Artificial intelligence in Biological sciences
    Interdisciplinary Science Conference, JMI, New Delhi | Oct 21-22, 2019
  7. Presenting First Draft Genome Sequence Rice Bean
    Interdisciplinary Science Conference, JMI, New Delhi | Oct 21-22, 2019
  8. Efficacy of Weed based botanicals against Rhizoctonia root rot in Buckwheat (Fagopyrum sp.)
    1st National Conference on 'Neglected and Underutilized Crop Species', NIPGR, New Delhi | Aug 02, 2019
  9. Sustainable Agriculture and Global Food Security: Perspective, importance and Opinion
    Symposium on 'Avenues in Plants Sciences', Deshbandhu College, New Delhi | Mar 8-9, 2019
  10. Buckwheat (Kuttu): As food, good health and Medicine
    National Conference on CCSMAP, MRIIRS | Feb 21-22, 2019
  11. Biofuels: A sustainable approach of Futuristic Energy
    National Conference on 'Trends in Life Sciences and Biotechnology', Maitreyi College, New Delhi | Feb 19-20, 2019
  12. Biodiversity: Threats and Conservation
    Fourth National Symposium on 'Environment', Deshbandhu College, New Delhi | Sep 25, 2018
  13. Role of Nanobiotechnology in Enhancing Crop production
    'Trends in Nanobiotechnology', TERI University | Sep 28-29, 2017
  14. Study of Bioactive component in Buckwheat and in-silico analysis of fagopyritol synthase
    'Emerging Issues of Climate change', Sri Aurobindo College, New Delhi | Oct 21-22, 2016
  1. 2025 Summer School in Applied Deep Learning in Bioinformatics
    Faculty of Health and Medical Sciences, University of Copenhagen, Denmark | Aug 11-15, 2025
  2. Clinical Interpretation of Whole Genome Sequences
    Knowmics (Online Course) | June 29, 2025
  3. New Education Policy (NEP) 2020 Sensitisation Programme
    UGC-MMTTC, Jamia Millia Islamia, New Delhi | Aug 05-14, 2024
  4. Enabling Technology Training (ETT-5) Workshop
    SCIS, JNU, New Delhi | Feb 17, 2024
  5. Artificial Intelligence in Modern Biology-2
    ICGEB, New Delhi | Sep 12-14, 2023
  6. Indo-Vietnam Hands-on Workshop on Sequencing Techniques
    CSIR-IGIB, New Delhi | Aug 02-06, 2023
  7. Computational Techniques for AI and Data Science Applications
    DST-STUTI, Banasthali Vidyapith, Rajasthan | July 25-31, 2023
  8. Hands-on Workshop on Design, Synthesis, Computational Studies and Data Interpretation of Drug-Like molecules
    SERB-KARYASHALA, NIPER-Ahmedabad | Jan 30 - Feb 05, 2023
  9. Accelerate your Research Using Elsevier’s Science Direct and Scopus
    NIPER-Ahmedabad | Jan 31, 2023
  10. Application of High-Performance Computing in Drug Designing
    SERB, MNNIT Allahabad | Aug 06, 2022
  11. BioC2022- Bioconductor Conference 2022
    Seattle Children’s Hospital (Virtual) | July 27-29, 2022
  12. Cloud-based Hands-on Workshop on Molecular Docking, Pharmacophore Modelling and Machine Learning
    ICMR-NICPR & Schrodinger Inc, Noida | Mar 15-16, 2022
  13. Discovery of Vaccines and Drugs for Infectious Diseases
    ICGEB, New Delhi | Dec 06-09, 2021
  14. 7 days International Workshop on Artificial Intelligence
    AiCHEF & St Claret College, Bengaluru | Nov 15-21, 2021
  15. 2-days Cloud-based Hands-on Workshop: Computational SBDD & MD Simulations
    SRM University & Schrodinger Inc | Sep 02-03, 2021
  16. Quantitative genetics genomics and plant breeding
    Vignan's Foundation, Guntur | Nov 23-27, 2020
  17. Advanced Structural Bioinformatics
    DBT-ABTIC, ICGEB, New Delhi | Nov 18-21, 2019
  18. Deep learning and IoT using MATLAB
    Dept. of Computer Science, Jamia Millia Islamia | Oct 03, 2019
  19. BioTecNika Schrodinger Joint Workshop on CADD
    Biotecnika Info Pvt. Ltd | July 22 - Aug 02, 2019
  20. Application of Artificial Intelligence in Modern Biology
    ICGEB, New Delhi | Mar 28-29, 2019
  21. Translational Bioinformatics: Guinness Book Recording to Digital Era
    Jamia Millia Islamia | Mar 06-07, 2019
  22. Interactive NGS Data Analysis
    NEHU, Shillong | Nov 15-17, 2018
  1. 3rd Symposium on Applied Deep Learning in Bioinformatics
    Faculty of Health and Medical Sciences, University of Copenhagen, Denmark | Aug 15, 2025
  2. Springer Nature: Navigate the World of Scientific Article Writing
    Online Session | May 15, 2025
  3. Springer Nature: How to Navigate Platforms to Access all Journals
    Online Session | Mar 19, 2025
  4. The 3rd International Electronic Conference on Cancers
    MDPI | Mar 16-30, 2023
  5. The 2nd International Electronic Conference on Biomedicines
    MDPI | Mar 01-31, 2023
  6. Seminar: Recent Advances in Translational Cancer Research
    IGNTU, Amarkantak | Feb 08, 2023
  7. 21st International Conference on Bioinformatics (InCoB)
    KAUST, Saudi Arabia | Nov 21-23, 2022
  8. Seminar on Intellectual Property Rights
    Jamia Millia Islamia, New Delhi | Feb 28, 2022
  9. 3rd ICGA 2022 Virtual Conference: Biobanking to Omics
    Online | Jan 13-14, 2022
  10. Economic botany and plant genetic resources: National Perspective
    Deshbandhu College, New Delhi | Jan 18, 2022
  11. ISCBSC- RSG India Student Symposium 2019
    JNU, New Delhi | Nov 22, 2019
  12. Young Scientist Conference - India International Science Festival (YSC-IISF)
    Kolkata | Nov 05-07, 2019
  13. Interdisciplinary Science Conference: Big Data and Computational Biology
    JMI, New Delhi | Oct 21-22, 2019
  14. DST-PURSE National Seminar on Biophysics
    JMI, New Delhi
  15. Mini-symposium on Tracking Antimicrobial Drug Resistance Tuberculosis
    VPCI, Delhi University
  16. 20th Distinguished Lecture by Sir Prof. Tom Blundell
    Jamia Hamdard, New Delhi | Mar 20, 2019
  17. Symposium on Avenues in Plants Sciences
    Deshbandhu College, New Delhi | Mar 08-09, 2019
  18. National Conference on CCSMAP
    MRIIRS | Feb 21-22, 2019
  19. Fourth National Symposium on "Environment: Green Technology..."
    Deshbandhu College, New Delhi | Sep 25, 2018
  20. National Science Congress Association Delhi Chapter
    Zakir Hussain Delhi College | Oct 25, 2017
  21. PARIVARTAN 2K18
    Sri Aurobindo College, New Delhi | Apr 13, 2018
  22. 26th World Environmental Congress (WEED)
    India International Centre, New Delhi | Nov 08, 2017
  23. BIOTIKOS 2017
    TERI School of Advanced Sciences | Sep 28-29, 2017
  24. Conference on Growth control in development and disease
    NII, New Delhi | Oct 07, 2016
  25. National Conference on Galapagos Island and Darwin's Theory of Evolution"
    NII, New Delhi | Oct 06, 2016
  26. ICSSR-sponsored seminar Emerging Issues of Climate change
    Sri Aurobindo College, New Delhi | Oct 21-22, 2016
  27. Environmental Concerns of the 21st century
    Zakir Hussain Delhi College

Professional Activities

  1. Guest Editor: Frontiers in Oncology (2025-date)
    Topic: Artificial Intelligence for Polypharmacology and Resistance-Aware Cancer Drug Discovery
  2. Guest Editor: Current Genomics (2025-date)
    Topic: AI-Driven Genomics and Multi-Omics Approaches for Drug Discovery and Precision Medicine
  3. Guest Editor: Discover Biotechnology (2025-date)
    Topic: Artificial Intelligence Applications in Bioinformatics for Cancer Research
  4. Guest Editor: Natural Product Communications (2024-date)
    Topic: Harnessing Nature's Pharmacy for the Therapeutics of Lung and Respiratory Diseases
  5. Guest Editor: Mini-Reviews in Medicinal Chemistry (2024-date)
    Topic: Computational Frontiers in Medicinal Chemistry
  1. Member of the International Association for the Study of Lung Cancer (18/10/2024 to 17/10/2026)
  2. Member of the European Society for Medical Oncology (10/05/2024 to 09/05/2026)
  3. Member of the Bioinformatics and Drug Discovery Society (Life Member)
  4. Council Member of the Botanical Society (Sanjeevani), Deshbandhu College, University of Delhi.

490+ Verified Peer Reviews on Publons (WoS)

Accreditation and Quality Assurance Applied Mathematics and Information Sciences Archives of Computational Methods in Engineering Archives of Microbiology Biochemical and Biophysical Research Communications Biochemical Genetics Bioinformatics and Biology Insights Biomedical Reports BMC Artificial Intelligence BMC Infectious Diseases BMC Veterinary Research Brazilian Journal of Biology Cancer Investigation Cancer Medicine Cancer Reports Cell Biochemistry and Biophysics Chemical Engineering Journal Advances Chemistry and Biodiversity Computational Biology and Chemistry Computer Methods in Biomechanics and Biomedical Engineering Computers in Biology and Medicine Crop Protection Current Cancer Drug Targets Current Medicinal Chemistry Current Plant Biology Digital Health Discover Applied Sciences Discover Oncology Drug Development Research European Journal of Medicinal Chemistry Experimental and Therapeutic Medicine Expert Systems with Applications F1000Research Frontiers in Artificial Intelligence Frontiers in Dental Medicine Frontiers in Immunology Frontiers in Radiology Future Medicinal Chemistry Heliyon In Silico Pharmacology In Silico Research in Biomedicine Intelligence-Based Medicine International Journal of Oncology IScience Journal of Biological Research and Reviews Journal of Biomolecular Structure and Dynamics Journal of Chemistry Journal of Computational Biophysics and Chemistry Journal of Computational Science Journal of Computer-Aided Molecular Design Journal of Drug Targeting Journal of Experimental & Clinical Cancer Research Journal of Genetic Engineering and Biotechnology Journal of Molecular Modelling Journal of Pharmaceutical Analysis Journal of Pharmaceutical Innovation Journal of Proteins and Proteomics Journal of the Brazilian Chemical Society Journal of the Egyptian National Cancer Institute Journal of Translational Medicine Knowledge-Based Systems Letters in Drug Design & Discovery Lung Cancer: Targets and Therapy Medical Oncology Mini-Reviews in Medicinal Chemistry Molecular Diversity Molecular Medicine Reports Natural Resources for Human Health Naunyn-Schmiedeberg's Archives of Pharmacology Neural Computing and Applications Npj Precision Oncology Oncology Letters Open Chemistry PeerJ Pharmacological Research Pharmacological Research - Modern Chinese Medicine PLoS Neglected Tropical Diseases Plos One Qeios Results in Chemistry Saudi Medical Journal Scientific African Scientific Reports SN Applied Sciences Structural Chemistry VEGETOS Virology Virulence
  • Currently Supervising 3 MSc and 1 BSc dissertation students at University of Copenhagen, Denmark.
  • Guided 10 MSc and 5 BSc dissertation students during PhD tenure at Jamia Millia Islamia, India.
  • Guided many PhD Students as a mentor on quality research and publication.

Expertise & Technical Proficiencies

Agentic AI & GenAI
  • Autonomous Agent Workflows (LangChain, AutoGPT)
  • Retrieval-Augmented Generation (RAG) architecture
  • Fine-tuning Large Language Models (LLMs) for biology
  • Multi-agent simulations for complex data parsing
Deep Learning & ML
  • Advanced Architectures: Transformers, CNNs, LSTMs
  • Classical ML pipelines: Scikit-learn, XGBoost, LightGBM
  • Explainable AI (XAI) algorithms: LIME, SHAP
  • Hyperparameter optimisation and cross-validation
Scientific Computing
  • Python Ecosystem: NumPy, Pandas, SciPy, PyTorch, Keras
  • R Bioconductor & Tidyverse integration
  • Complex data visualisation: Seaborn, Plotly, Matplotlib
  • MATLAB for specialized mathematical modelling
AI-Driven Drug Design
  • Generative diffusion models for de novo ligand design
  • High-throughput Virtual Screening (HTVS) pipelines
  • Molecular docking (AutoDock Vina, Glide, SwissDock)
  • Binding free energy profiling (MM/GBSA, MM/PBSA)
Molecular Dynamics & Simulation
  • All-atom MD: Desmond, GROMACS, NAMD, AMBER
  • Trajectory dynamics: PCA, RMSD/RMSF, FEL mappings
  • Force field parametrization (OPLS, CHARMM, AMBER)
  • Markov State Models for conformational sampling
Quantum & Structural Biology
  • Density Functional Theory (DFT) calculations
  • Homology modelling & protein refinement (MODELLER)
  • Predictive toxicology and pharmacokinetics (ADMET)
  • Advanced 3D visualisation (PyMOL, UCSF ChimeraX)
Advanced Omics Analysis
  • WGS/WES data processing & variant annotation
  • Single-cell RNA-seq (scRNA-seq) trajectory inference
  • Alignment (Bowtie2, BWA) & Variant calling (GATK)
  • AI-based variant pathogenicity prediction frameworks
Systems Biology & Networks
  • Multi-omics data integration and harmonization
  • Protein-protein interaction mapping (Cytoscape, STRING)
  • Gene regulatory network reconstruction & pathway mining
  • Biomarker discovery via systems-level interpretation
Evolutionary & Sequences
  • Phylogenomics and maximum likelihood estimations
  • Multiple sequence alignment (Clustal, MAFFT, MUSCLE)
  • Motif discovery and hidden Markov models (HMMs)
  • Comprehensive BLAST and FASTA heuristic searches
HPC & Cloud Infrastructure
  • Linux/Unix architectures and system administration
  • HPC job scheduling (SLURM, PBS Pro)
  • Cloud computing platforms (AWS, Google Cloud)
  • Parallel computing and GPU acceleration strategies
MLOps & Containerization
  • Deploying AI models in production environments
  • Containerized scientific workflows (Docker, Singularity)
  • CI/CD pipelines for automated testing & deployment
  • Bash scripting for scalable batch automation
Version & Dev Standards
  • Git/GitHub for collaborative code management
  • Building reproducible, modular scientific codebases
  • Strict documentation and Jupyter Notebook integration
  • Agile methodologies in computational research

Academic Referees

Dr Tue K. Nielsen
Postdoc PI
Associate Professor
University of CopenhagenDK
Dr Khalid Raza
PhD Supervisor
Associate Professor
Jamia Millia IslamiaIN
Dr Murugesh Eswaran
Mentor
Assistant Professor
More School of MedicineUS
Dr Tiina Jokela
JYU Visiting PI
Research Director
University of JyväskyläFI
Dr Manoj K Yadav
PI- SARS-CoV-2
Associate Professor
SRM UniversityIN
Dr Mansaf Alam
MSc Supervisor
Professor
Jamia Millia IslamiaIN
AI Analysis Result