AICWhy AICTEAM & EXPERIENCE Contact Us

WHY AIC

Professional support grounded in
real research experience

AIC is led by experienced researchers and supported by an interdisciplinary collaboration and consulting network. We organize study design, data analysis, evidence integration, and scientific communication into a transparent, traceable, and reviewable workflow.

Meet Our LeadershipView Research Services

SCIENTIFIC LEADERSHIP

Two core leaders guide scientific direction and delivery quality

Our leaders participate in project assessment, study design, key methodological decisions, and final review, while engaging domain specialists as needed.

Hongbao Cao, Ph.D.

Hongbao Cao, Ph.D.

Senior Bioinformatics Leader, AIC LLC | Affiliate Faculty, George Mason University

Dr. Cao has a doctoral background in biomedical engineering and extensive experience in bioinformatics, medical data analysis, machine learning, genomics, and research-software development. He oversees project design, method development, data analysis, quality control, and organization of research outputs.

  • Bioinformatics and multi-omics integration
  • AI, machine learning, and biomedical analytics
  • Genetic causal inference and evidence networks
  • Research software, reports, and manuscript workflows

180+ peer-reviewed research publications

Research spanning bioinformatics, multi-omics integration, medical imaging, machine learning, psychiatric genetics, complex-disease mechanisms, and genetic causal inference.

View Google Scholar →
Ancha Baranova, Ph.D., D.Sc.

Ancha Baranova, Ph.D., D.Sc.

Professor of Systems Biology, George Mason University | Genetics & Personalized Medicine Researcher

Dr. Baranova brings extensive experience in systems biology, molecular genetics, complex-disease mechanisms, and translational research. She provides senior scientific guidance on research direction, biological plausibility, mechanistic interpretation, and output quality.

  • Systems biology and complex-disease mechanisms
  • Molecular genetics and omics research
  • Biomarkers and personalized medicine
  • Interdisciplinary and international research

400+ scholarly works

Research spanning systems biology, functional genomics, molecular genetics, complex-disease mechanisms, biomarkers, and personalized medicine.

View Public Research Profile →
54Ph.D.s · Professors · Senior Engineers

INTERDISCIPLINARY NETWORK

One project should not be limited by one discipline

AIC's collaboration and consulting network spans biological questions, computational implementation, statistical review, and scientific communication. Specialists are selected according to the research question, data type, and expected outputs.

BiomedicineBioinformaticsElectrical EngineeringStatisticsSystems BiologyArtificial IntelligenceMedical ImagingScientific Writing

WHY WORK WITH US

More than people: an executable research system

01

Matched Expertise

Specialists are selected by disease area, data type, and research objective.

02

Flexible Engagement

Choose independent tools, mentor-guided support, or comprehensive consulting.

03

Traceable Delivery

Essential records of methods, code, processing, results, and evidence are retained.

04

Clear Responsibilities

Scope, roles, milestones, and deliverables are confirmed before work begins.

REPRESENTATIVE EXPERIENCE

Capabilities grounded in published research

These examples summarize the types of problems our team has addressed and the methods we have used. They do not represent identifiable client engagements.

Multi-Omics Integration & Biomarkers

Combining genetic variation, gene expression, and other molecular data to prioritize candidate genes and biomarkers for complex diseases.

  • High-dimensional feature selection
  • Multi-source data integration
  • Candidate prioritization

Medical Imaging & Machine Learning

Integrating multichannel medical images and high-dimensional features through sparse representation, regularized classification, and performance evaluation.

  • Medical image processing
  • Machine-learning models
  • Classification and validation

Genetic Causal Inference

Using large-scale GWAS summary data to evaluate causal direction, shared genetic architecture, and robustness across exposures and disease outcomes.

  • Mendelian randomization
  • Genetic correlation
  • Sensitivity analyses

Regulatory Networks & Mechanisms

Integrating genetic associations, molecular regulation, pathways, and public evidence into traceable mechanistic models and evidence networks.

  • miRNA–mRNA networks
  • Functional pathway analysis
  • Evidence-network construction
Privacy note: To protect authors, collaborators, and institutions, these examples are generalized and de-identified. Publication titles, author lists, institutions, unpublished data, and other traceable information are not displayed.

RESEARCH INTEGRITY

Trust begins with clear boundaries

Authentic ResearchWe do not fabricate data, results, contributions, or research experience.
Transparent RolesClient, mentor, specialist, and AIC responsibilities are defined.
No Publication GuaranteesWe support research and submission, but do not guarantee acceptance.
Information ProtectionData access, confidentiality, and output use are agreed by project.

START A CONVERSATION

Tell us what you want your research to achieve

We will assess the expertise required, the appropriate engagement model, and the next steps.

Contact the AIC Team