Resume-aware faculty matching

Find professors who actually fit you

Upload your resume. Four AI agents analyze your background, rank the faculty who fit, inspect their recent research, and help you draft outreach — grounded in their actual work, not templates.

Free to startNo credit cardCancel anytime
Top matches Balanced preset
Dr. Sarah Chen
Stanford · Interpretability · NLP
91
Dr. Marcus Holloway
MIT · Robotics · RL
84
Dr. Aisha Okonkwo
CMU · Fairness · HCI
82
Nova · Professor Researcher · re-ranking top 20…
Mohammad Ali Saghiri

Mohammad Ali Saghiri

· Associate ProfessorVerified

Rutgers University · Restorative Dentistry

Active 2007–2026

h-index35
Citations4.1k
Papers20893 last 5y
Funding
See your match with Mohammad Ali Saghiri — sign in to PhdFit.Sign in

About

Dr. Mohammad Ali Saghiri is an Associate Professor in the Department of Restorative Dentistry at Rutgers School of Dental Medicine. He is a distinguished researcher at the intersection of dentistry, biomaterials, computer science, and AI. His groundbreaking work in endodontic biomaterials harnesses AI to transform dental diagnostics, treatment planning, and education. His research portfolio includes AI-powered image analysis for early disease detection, virtual reality simulations for dental training, and ethical AI applications. Additionally, he explores AI's role in optimizing treatment plans and secure data transfer in healthcare through blockchain technology. Dr. Saghiri has contributed extensively to the field with over 120 PubMed publications, nearly 40% of which focus on the intersection of dentistry and computer science. He serves as an Associate Editor for two journals and is on the editorial board of over ten journals, demonstrating his commitment to advancing dental research. His innovative projects include the development of novel biomaterials such as FitSeal, which addresses limitations of conventional endodontic sealers, and DentinVaccine, aimed at enhancing dentin durability. Recognized for his contributions, he received the New Jersey Health Foundation's Excellence in Research Award in 2024 and the DenburTech Award in 2020. Dr. Saghiri is passionate about fostering collaboration, mentoring future researchers, and engaging in biomedical research, international dentistry, and computer engineering.

Research topics

  • Medicine
  • Dentistry
  • Materials science
  • Composite material
  • Chemistry
  • Orthodontics
  • Metallurgy
  • Crystallography
  • Endocrinology
  • Computer Science
  • Artificial Intelligence
  • Internal medicine
  • Pathology
  • Surgery
  • Organic chemistry
  • Mathematics
  • Mineralogy
  • Chemical engineering
  • Psychology
  • Inorganic chemistry
  • Biochemistry
  • Food science
  • Nuclear chemistry
  • Medical education

Selected publications

  • Reply to the Letter to the Editor: “Diabetes Increases Residual Stress and Microcrack Length in Dentin: An XRD–SEM Study with AI-assisted Quantification”

    Journal of Endodontics · 2026-02-01

    article1st authorCorresponding
  • Discoloration, radiopacity, and push-out bond strength of bismuth-based radiopacifiers in endodontic sealers

    Odontology · 2026-02-06

    article1st authorCorresponding
  • Selenium anion substitution in hydroxyapatite: chemo-mechanical effects compared with root canal dentin

    Odontology · 2025-05-11

    article1st authorCorresponding
  • Effect of Pre- and Post-thermocycling Strontium Infiltration on Cracks and Tubular Structure in Human Root Dentin

    Journal of Endodontics · 2025-11-19

    article1st authorCorresponding
  • Cytotoxicity of Nanocarrier-Based Drug Delivery in Oral Cancer Therapy: A Systematic Review and Meta-Analysis

    Cancer Control · 2025-01-01 · 6 citations

    reviewOpen access1st author

    Background Oral cancer remains 1 of the biggest health care challenges; it has a poor response to treatment, and treatment often results in severe side effects. Nano-targeted drug carrier-assisted drug delivery systems can improve the benefits of targeted drug delivery and treatment efficacy. A systematic review and meta-analysis was conducted to investigate the effect of targeted nano carrier drug delivery systems on the management of oral cancer. Methods A comprehensive literature search was performed using PubMed, ScienceDirect, the Cochrane Library, Google Scholar, and Scopus using PRISMA guidelines, to identify relevant in vitro and in vivo (human) studies. Studies evaluating the impact of nanocarrier-based delivery systems on oral cancer cells or human models were selected. Pooled effect sizes were calculated using random-effects models via RevMan 5.4, and heterogeneity among studies was assessed. Results After full-text assessment, 15 research articles were included [14 in vitro studies and 1 randomized controlled trial (RCT)]. In the meta-analysis, the pooled data (IC 50 ) for the impact of the nanocarrier delivery system vs control on oral cancer was −7.67 (95% CI: −41.77, 26.43), with a high heterogeneity ( I 2 = 92%, P < 0.00001). Moreover, in vitro studies had a medium risk of bias, while the RCT had some concerns in the randomization domain. Conclusion Nanocarrier-based drug delivery has been found to be a superior approach compared to drug delivery in free form, increasing the efficacy and safety of oral cancer treatment.

  • Efficacy of Bioactive Glass Vs Traditional Bone Grafts in Maxillofacial Reconstruction: A systematic Review and Meta-analysis of Clinical Outcomes.

    2025-04-25

    reviewOpen access1st authorCorresponding

    Main outcome(s) Bone volume retention, new bone formation, resorption rate, and biomaterial retention.Additional outcome(s) Complication rates, osseointegration, and overall clinical success.Data management EndNote for screening, Excel for extraction, and PRISMA-guided systematic review. Quality assessment / Risk of bias analysisCochrane RoB2 for RCTs, ROBINS-I for nonrandomized studies, GRADE framework for evidence certainty. Strategy of data synthesisFixed/random-effects models standardized mean differences (SMD), and I statistic for heterogeneity.Subgroup analysis Not explicitly conducted; analysis focused on overall pooled estimates. Sensitivity analysis Conducted using Duval andTweedie's trim-and-fill method to address potential publication bias. Language restriction Only articles in English.Country(ies) involved Saudi Arabia.

  • Efficacy of bioactive glass versus traditional bone grafts in maxillofacial reconstruction: A systematic review and meta-analysis of clinical outcomes

    Cell Transplantation · 2025-10-01 · 2 citations

    articleOpen access1st author

    The aim of this article is to identify whether bioactive glass (BG) is a valid substitute for autogenic bone grafting in maxillofacial reconstruction. PubMed, Scopus, Web of Science, and Cochrane Library databases were searched. Meta-analyses with fixed- and random-effects models were performed by using standardized mean differences (SMDs) with 95% confidence intervals (CIs). Heterogeneity was assessed by using the I² statistic. The significance of results was evaluated at P < 0.05. The BG leads to greater total bone volume retention 6 months after surgery compared with autografts (SMD = 0.796, 95% CI = 0.445–1.147, P = 8.74 × 10⁻⁶, I² = 0%). The resorption rate of BG grafts (SMD = −0.768, 95% CI = −1.360 to −0.176, P = 0.011, I² = 3.82%) was less common, while the retention of the biomaterial (SMD = 1.165, 95% CI = 0.540–1.790, P = 0.00026, I² = 0%) was higher in the experimental group. Both BG and autogenic grafts result in the formation of new bone to a similar extent. However, BG is able to provide long-term stability by maintaining the graft volume, reducing resorption, and preserving the graft scaffold, representing an effective alternative to autogenous bone grafting for a durable maxillofacial reconstruction.

  • Diabetes Increases Residual Stress and Microcrack Length in Dentin: An XRD–SEM Study with AI-assisted Quantification

    Journal of Endodontics · 2025-09-09 · 3 citations

    article1st authorCorresponding
  • Efficacy of early rituximab treatment in primary Sjögren’s syndrome: a systematic review and meta-analysis

    Journal of Rheumatic Diseases · 2025-02-23 · 6 citations

    reviewOpen access

    Objective: This systematic review and meta-analysis aimed to assess Rituximab (RTX)'s efficacy and safety in primary Sjögren's syndrome (pSS), particularly how treatment timing influences outcomes. Methods: The study included randomized controlled trials (RCTs) and quasi-experimental studies evaluating RTX in pSS patients, focusing on disease activity (European League Against Rheumatism Sjögren's Syndrome Disease Activity Index [ESSDAI] score) and adverse events (AEs). Searches were conducted in MEDLINE, Embase, SCOPUS, and Cochrane Library databases up to July 2024. Risk of bias was assessed using Cochrane Risk of Bias 2.0 (RoB 2) and Joanna Briggs Institute (JBI) checklists. Meta-analysis was performed in Stata 17 with a random-effects model, reporting mean differences in ESSDAI and I² for heterogeneity. Results: From 555 articles, 15 studies were included (4 RCTs and 11 quasi-experimental studies). RCT meta-analysis showed a mean difference of 0.09 (95% confidence interval [CI] -0.43, 0.61), indicating no significant RTX efficacy. In contrast, the pooled quasi-experimental analysis revealed a mean difference of -4.36 (95% CI -5.83, -2.89), suggesting a significant reduction in disease activity. Meta-regression indicated no significant correlation between RTX efficacy and mean disease duration. Subgroup analysis of disease duration (under vs. over 60 months) showed no significant difference. Safety assessment indicated no significant differences in AEs between RTX and placebo in RCTs. In quasi-experimental studies, infusion reactions and infections were the most common AEs, with serious infections being the most severe. Conclusion: RTX did not show significant improvement in RCTs. However, RTX significantly reduced pSS activity at week 24 or month 6 following treatment, based on quasi-experimental studies. We found no significant correlation between RTX efficacy and disease duration.

  • Graphene and its modifications for enhanced adhesion in dental restoratives: a molecular docking and dynamics study

    Scientific Reports · 2025-03-19 · 7 citations

    articleOpen access1st author

    Graphene has attracted significant attention in dentistry due to its structural and adhesive properties, enhancing the mechanical performance of dental composites. This study investigates the behavior and interaction of monomers and graphene-based adhesives using molecular docking and molecular dynamics (MD) simulations. Binding energies and interactions between monomers and graphene derivatives were assessed using molecular docking, while MD simulations with the Forcite module and COMPASS II force field provided insights into the mechanical properties of the composites. The simulations involved energy minimization, NVT/NPT ensembles, and equilibration for 50 ns. The binding energies of the monomer-graphene complexes ranged from - 16.27 to -18.55 kcal/mol, with the Bis-GMA-Graphene Quantum Dot complex showing the most stable interaction. Mechanical properties such as Young's modulus, shear modulus, and flexural strength were calculated for selected complexes: Bis-GMA-Graphene Quantum Dot (14.74 GPa, 9.32 GPa, 120.51 MPa), EBPADMA-Graphene Quantum Dot (14.28 GPa, 9.13 GPa, 118.22 MPa), HEMA-Nitrogen-doped Graphene (9.85 GPa, 6.86 GPa, 95.7 MPa), TEGDMA-Graphene Oxide (11.96 GPa, 8.12 GPa, 110.23 MPa), and UDMA-CCOOH Functionalized Graphene (13.82 GPa, 8.43 GPa, 115.4 MPa). The Bis-GMA-Graphene Quantum Dot complex showed the highest stability with 20 hydrogen bonds. These results highlight graphene quantum dots and functionalized graphene derivatives as promising candidates for high-performance dental composites, offering strong adhesive properties and improved mechanical strength. Future research may focus on further optimizing these interactions and exploring additional graphene modifications.

Frequent coauthors

  • Nader Sheibani

    64 shared
  • Armen Asatourian

    51 shared
  • Mehrdad Lotfi

    University of Kashan

    50 shared
  • Franklin García‐Godoy

    University of Tennessee Health Science Center

    48 shared
  • Steven M. Morgano

    Rutgers, The State University of New Jersey

    37 shared
  • Julia Vakhnovetsky

    University of Michigan–Ann Arbor

    36 shared
  • Kasra Karamifar

    34 shared
  • James L. Gutmann

    Texas A&M University

    33 shared

Labs

  • Biomaterials Research LaboratoryPI

Awards & honors

  • New Jersey Health Foundation's Excellence in Research Award…
  • DenburTech Award (December 2020)
  • FitSeal project award from the National Collegiate Inventors…
  • Resume-aware match score
  • Save to shortlist
  • AI-drafted outreach

See your match with Mohammad Ali Saghiri

PhdFit ranks faculty by your research interests, methods, and publications — grounded in their actual work, not templates.

  • Free to start
  • No credit card
  • 30-second signup