Abolfazl (Arash) Sodagartojgi

About

I am a PhD Candidate in Statistics at Rutgers University, specializing in statistical machine learning, high-dimensional inference, and deep generative models. I have 3+ years of quantitative finance experience at Rabobank (New York), building forecasting and risk tools for derivatives portfolios.

My current interests include dynamic factor models and sparse state-space inference; VAEs, flows, and diffusion models; causal inference in finance and healthcare; and machine-learning–based stochastic weather generators for renewable energy.

Research

Publications

• Enhanced classification of tinnitus patients using EEG microstates and deep learning techniques
  Raeisi Z, Sodagartojgi A, Sharafkhani F, Roshanzamir A, Najafzadeh H, Bashiri O, Golkarieh A. Scientific Reports (2025)
  DOI
• EEG microstate analysis in trigeminal neuralgia: identifying potential biomarkers for enhanced diagnostic accuracy
  Lashaki RA, Raeisi Z, Sodagartojgi A, Abedi Lomer F, Aghdaei E, Najafzadeh H. Acta Neurologica Belgica (2025)
  DOI
• Enhancing stock market prediction accuracy with recurrent deep learning models: A case study on the CAC40 index
  Sodagartojgi A, et al. World Journal of Advanced Research and Reviews 23(1) (2024)
  DOI
• Deep learning-based retinal abnormality detection from OCT images with limited data
  Talebzadeh M, Sodagartojgi A, Moslemi Z, Sedighi S, Kazemi B, Akbari F. World Journal of Advanced Research and Reviews 21(3) (2024)
  DOI
• Modeling and optimization of efficient removal of diclofenac and naproxen based on chemometric approaches
  Abdollahi SA, Pourabadeh A, Alishiri M, Sodagartojgi A, Ranjbar SF, Ehghaghi MB, Talati F. Water Resources and Industry 31 (2024): 100238.
  DOI Journal page
• Exploring the impact of supply chain integration and agility on commodity supply chain performance
  Dokhanian S, Sodagartojgi A, Tehranian K, Ahmadirad Z, Khorashadi Moghaddam P, Mohsenibeigzadeh M. World Journal of Advanced Research and Reviews 22(1) (2024)
  DOI

For a complete and up-to-date list of publications, please visit my Google Scholar profile.

Honors & Awards

• 🎓 Full 5-Year PhD Scholarship, Rutgers University (2022–2027)
• 🏆 Best Teaching Assistant Award, Rutgers Statistics (2024)
• 📊 Best Qualifying Exam Performance, Rutgers Statistics (2023)
• ✈️ JSM Travel Grant, American Statistical Association (2025)
• 🤖 2025 NBER-NSF Time Series Conference Travel Award (2025)
• 🔬 Graduate Student Research Award, Rutgers Statistics (2024)
• 🎖️ College of Business Valedictorian, JMU (2019) — Summa Cum Laude, Phi Beta Kappa

Teaching

Teaching Assistant, Rutgers (2022–Present)

Statistical Inference · Linear Regression · Time Series Analysis · Machine Learning. Best Teaching Assistant Award (2024)

Curriculum Vitae

📄 Download my CV (PDF) · Last updated: 2025-09

Education

• PhD in Statistics, Rutgers University (2022–Present) — GPA 3.9/4.0 · Advisors: Prof. Gemma Moran & Prof. Han Xiao
• MS in Statistics, Rutgers University (2022–2024)
• BS in Mathematics & Economics, James Madison University (2016–2019) — Valedictorian, GPA 3.95/4.0

Experience

• Commodity Derivatives Trading Analyst, Rabobank, New York (2020–2022)
• Corporate Derivatives Quantitative Analyst, Rabobank, New York (2019–2021)

Contact

📧 sodagaax@gmail.com

📍 Highland Park, NJ

💻 GitHub · 📚 Google Scholar · 💼 LinkedIn