Ahmad Mousavi

Ahmad Mousavi

Assistant Professor of Data Science,
Department of Mathematics and Statistics,
American University

Curriculum Vitae

Positions

  • American University, Washington, DC
    • Assistant Professor of Data Science, Department of Mathematics and Statistics (Fall 2024–present)
    • Affiliate Faculty, Institute of Artificial Intelligence, Kogod School of Business (2024–present)
    • Faculty Fellow, Center for Data Science, School of Public Affairs (2026–present)
    • Professorial Lecturer, Department of Mathematics and Statistics (Fall 2023–Spring 2024)
  • University of Florida, Gainesville, FL
    • Postdoctoral Associate, Informatics Institute (2021–2023)
  • University of Minnesota, Minneapolis, MN
    • Industrial Postdoctoral Fellow, Institute for Mathematics and its Applications (2019–2021)

Education

  • University of Maryland, Baltimore County, Baltimore, MD — Ph.D. in Applied Mathematics, 2013–2019
    • Advisor: Prof. Jinglai Shen
    • Thesis: Topics in Sparse Recovery via Constrained Optimization: Least Sparsity, Solution Uniqueness, and Constrained Exact Recovery
  • University of Maryland, Baltimore County, Baltimore, MD — M.Sc. in Applied Mathematics, 2013–2015
  • Sharif University of Technology, Tehran, Iran — M.Sc. in Applied Mathematics, 2008–2011
    • Advisor: Prof. Nazam Mahdavi-Amiri
    • Thesis: An Inexact Newton Method for Nonconvex Equality Constrained Optimization
  • University of Guilan, Rasht, Iran — B.Sc. in Applied Mathematics, 2004–2008

Work Experience

  • Research and Development Intern, Precima, R&D division, Chicago, IL (Summer 2019)

Supervising Experience

  • Data Science Practicum
    • Fall 2024: Yen-Chun Lin, Sean Hsu, Ting Yi Chuang, and Po-Yu Lai. Fairness in Imbalanced Data — Guided students in exploring Universum-based quadratic and linear SVM models to address bias in imbalanced datasets, with applications such as fraud and disease detection.
    • Spring 2025: Meet Patel, Dwanith Venkat Girish. Neural Network Pruning — Supervised the development and evaluation of structured and unstructured pruning methods to improve the efficiency and scalability of deep learning models.
    • Fall 2025: Peter Ozo-Ogueji, Kaitlin Works-Figueroa, Aidan Hennessy, and Kennya Jiles. Multimodal Emergency Department Diagnosis Discordance — Led students in designing multimodal models integrating clinical notes, vitals/labs time series, and medical imaging (MIMIC-IV) to predict diagnostic discordance between ED admissions and discharge diagnoses.
  • Independent study / capstone
    • Fall 2024: Spencer Grewe (DATA 690). Medical Computer Vision — Supervised architectural and empirical analysis of U-Net for biomedical image segmentation, leading to development of LFASNet.
  • External and cross-institutional supervision
    • Spring 2026–present: Yanjia Zhang, Pooja Jitendra Shah, and Sai Praneet Reddy Chinthala (George Mason University), co-supervised with Dr. Lindi Liao (George Mason University); Katherine Lessard (American University; Spring 2026, discontinued before completion). Fair Bilevel Optimization with Synthetic Data for Collaborative Classification — Guiding students in developing and implementing an efficient bilevel optimization algorithm for fairness-aware collaborative learning using synthetic data generation.
    • 2026–present: Aruthra Satish Kumar (George Mason University). CAM-Soft: Scalable Multimodal Fusion for Soft Hate Speech Detection via Camouflaged-Implicature Modeling and Counterfactual Invariance — Mentoring research on this manuscript (in preparation; intended for IEEE BigData).
    • Spring 2025–present: Yeganeh Abdollahinejad (Michigan State University, Department of Biology; mentorship began while she was at Pennsylvania State University). Robust Multi-Modal and Multi-Scale Learning under Distribution Shift — Mentoring work on EMO-CARE, E-CaTCH, MOMENTA (under review at Information Fusion), and CAM-Soft (manuscript in preparation; intended for IEEE BigData), including model design, experiments, and manuscript preparation.
    • Fall 2025–present: Md Toufikuzzaman (Pennsylvania State University), co-advised with Dr. Dongwon Lee (Pennsylvania State University). BLADE: Bilevel Low-Rank Augmented-Lagrangian Erasure for LLM Unlearning — Co-advising the student in the constrained bilevel unlearning framework (submitted to EMNLP 2026), including theoretical formulation, implementation, and evaluation on TOFU, MUSE, and KnowUndo.
    • 2025–present: Majid Alikhani (independent researcher, Toronto). Multimodal Recommendation and Soft Hate Speech Detection — Supervised research on MURAL (in revision after RecSys 2026) and CAM-Soft (manuscript in preparation; intended for IEEE BigData).
    • 2026–present: Miguel Esparza (Texas A&M University) and Aydin Ayanzadeh (UMBC), co-mentored with Dr. Ali Mostafavi (Texas A&M University). Physics-Conditioned Attention Bias and Retrieval-Augmented Correction for Next-Day Wildfire Spread Prediction — Co-mentoring research on this preprint (July 2026).

Review Experience

Review for the following journals and conferences: Neural Networks, NeurIPS 2025 Workshop on Constrained Optimization in Machine Learning (COML), IEEE Transactions on Signal Processing, Journal of Optimization Theory and Applications, Mathematical Methods of Operations Research, Optimization Methods and Software, Digital Signal Processing, Physica A: Statistical Mechanics and its Applications, Numerical Algorithms, Set-Valued and Variational Analysis, Mathematical Problems in Engineering, Infor: Information Systems and Operational Research, Complex and Intelligent Systems, and so on.

Conference And Workshop Presentations And Attendance

  • (Poster presentation) E-CaTCH: Event-Centric Cross-Modal Attention with Temporal Consistency and Class-Imbalance Handling for Misinformation Detection, AU Research Conference, American University, Washington, DC, USA, May 11, 2026.
  • (Attendance) StatConnect@AI, Georgetown University, Washington, DC, USA, 2026.
  • (Attendance) NeurIPS 2025, San Diego, CA, USA, 2025.
  • (Attendance) IEEE International Conference on Data Mining (ICDM 2025), Washington, DC, USA, 2025.
  • (Presentation) Exploring Sparsity: Modeling and Algorithmic Insights in Machine Learning and Finance, Departmental Seminar, Department of Mathematics, Semnan University, October 13, 2025.
  • (Attendance) Workshop on Intersections between Control, Learning, and Optimization, UCLA, Los Angeles, CA, USA, 2019.
  • (Poster presentation) Solution Uniqueness of Convex Piecewise Affine Functions Based Optimization with Applications to Constrained ℓ1 Minimization, Princeton Day of Optimization, 2018; ICERM Computational Imaging Workshop, 2019; ICERM Optimization Methods in Computer Vision and Image Processing Workshop, 2019.
  • (Presentation) Some Topics in Sparse Optimization, Norbert Wiener Center seminars, University of Maryland, College Park, MD, USA, 2018.
  • (Presentation) Solution Uniqueness of Convex Piecewise Affine Functions Based Optimization with Applications to Constrained ℓ1 Minimization, SIAM Annual Meeting session, Portland, OR, USA, 2018.
  • (Attendance) SIAM Annual Meeting, Pittsburgh, PA, USA, 2017.
  • (Presentation) A Mathematical Introduction to Compressive Sensing, University of Maryland, Baltimore County, Optimization Seminar, Baltimore, MD, USA, 2016.
  • (Attendance) American Mathematical Society Spring Eastern Sectional Meeting, Baltimore, MD, USA, 2014.
  • (Attendance) 3rd and 4th Workshop on Optimization and its Applications, Tehran, Iran, 2011 and 2012.
  • (Attendance) 3rd and 4th International Conference of Iranian Operations Research Society, Tehran and Rasht, Iran, May 2010 and 2011.
  • (Attendance) 40th Annual Iranian Mathematics Conference, Tehran, Iran, 2009.

Service

  • Member, AI Steering Committee, American University, Fall 2025–present.
    • I also serve as a member of both the Student Engagement and Scholarship Group and the Responsible AI Group within the committee.
  • Member, Student Research Committee, Department of Mathematics and Statistics, American University, Fall 2025–present.
  • Program Committee Member, 5th IEEE Big Data Workshop on Multimodal AI (MMAI 2025), IEEE International Conference on Big Data, 2025.
  • Program Committee Member, Multimodal AI (MMAI) Workshop, IEEE International Conference on Big Data, 2026.
  • External PhD Thesis Reviewer and Defense Examiner, Mohammadigohari Mahdi, Computer Science, Free University of Bolzano (38th Cycle).
  • Judge, Smith Analytics Consortium Datathon, Robert H. Smith School of Business, University of Maryland (UMD–American University student analytics competition sponsored by Deloitte), 2025 and 2026.
  • Vice President, Mathematics and Statistics Graduate Student Association (MSGSA), University of Maryland, Baltimore County, 2015.
  • Orientation Advisor, University of Maryland, Baltimore County, Summer 2017.

Selected Honors And Awards

  • CAS Faculty Grant for Scholarship and Creative Inquiry, College of Arts and Sciences, American University, $2,500 (“Fair Collaborative Learning via Synthetic Payloads in Imbalanced Settings”), awarded December 2025.
  • Outstanding Graduate Research Award in Mathematics, College of Natural and Mathematical Sciences, UMBC, 2019.

Miscellaneous

Computer skills

  • R
  • Python
  • MATLAB
  • LaTeX
  • Microsoft Office

Memberships

  • IEEE (Regular Member)
  • Society for Industrial and Applied Mathematics (SIAM; previous)

Download full CV (PDF)