Rotation-Invariant Shape Representation
Computational geometry and similarity-function project for rotation-invariant comparison of planar shapes.
Professional Summary
PhD student in Artificial Intelligence with a previous PhD in Mathematics (Harmonic Analysis). My research and coursework focus on large-scale data analysis, machine learning, algorithmic reasoning, geometric computation, and intersections between mathematics and computer science. I work with graph algorithms, signal sampling approaches, shape analysis methods, reinforcement learning techniques, and computational geometry.
Education
Ph.D. in Computer Science (Artificial Intelligence)
Ph.D. in Mathematics
M.Sc. in Mathematics
B.Sc. in Mathematics
Research & Projects
- Computational Geometry (Submitted Paper): Developed an interdisciplinary method for analyzing star-shaped and non-star-shaped objects in 2D space. Bridged mathematical structure with CS applications like shape recognition and boundary representation.
- Geometric Origami Modeling: Used Python + Rhino-Grasshopper to study curved origami behavior with mathematical and algorithmic insights.
- Discrete Curve Geometry: Investigated curvature, torsion, and shape properties of sampled curves for use in graphics and CAD.
Galaxy Shape Geometry
Computational geometry and similarity-function project focused on geometric structure and comparison of complex shapes.
Signature Tool
Interactive project for geometric signatures and similarity analysis of shapes.
Technical Skills & Coursework
Programming & Tools
Python
OOP
NumPy
SciPy
Matplotlib
Rhino-Grasshopper
Data & AI Specialties
High-dimensional data handling, signal sampling methods, noise reduction, graph algorithms (PageRank, Dijkstra), supervised/unsupervised learning, reinforcement learning, classification, and feature extraction.
Mathematics & Geometry
Harmonic analysis, linear algebra, probability, differential equations, complex analysis, discrete structures, 2D object classification, and structural analysis of star-shaped objects.
Graduate Coursework
High-Dimensional Data Analysis
Data Mining
Artificial Intelligence
Machine Learning
Additional Computer Science Coursework
Computational Topology
Additional Mathematics Coursework
Abstract Harmonic Analysis
Functional Analysis
Real Analysis
Complex Analysis
Algebraic Topology
Advanced Algebra
Operator Algebras
Calculus of Variations
Convex Optimization
Measure Algebras on Groups and Semigroups
Amenability of Groups and Semigroups
Professional Experience
Python Instructor
- Taught Python with a focus on data workflows, algorithm design, and machine learning fundamentals.
Mathematics Lecturer
- Taught Linear Algebra, Calculus, Analysis, Differential Equations, Complex Functions, and Discrete Mathematics.
- Guided students in mathematical thinking applied to algorithms and computational tasks.
Mathematics Teacher
- Taught advanced mathematics emphasizing quantitative reasoning and rigorous problem-solving.
Publications
Rotation-Invariant Vectorized Shape Representations
arXiv preprint, 2026
H. Shafieasl, J.M. Phillips
Parameterized Folded State Shape Modeling of David Huffman’s Ellipse
Journal for Geometry and Graphics, 28(2):199–212, 2025
A. Safary, H. Shafieasl, J. Mitani
Geometric Design Tool for One-Fold, a Curved Origami with a Single Fold
Journal for Geometry and Graphics, 28(1):089–101, 2024
A. Safary, H. Shafieasl, J. Mitani
Bounded Pseudo-Amenability and Contractibility of Certain Banach Algebras
Filomat, 34(5):1701–1712, 2020
H. Pourmahmood-Aghababa, M.H. Sattari, H. Shafieasl
A Note on Ramified Coverings of Riemann Surfaces
International Mathematical Forum, 15(8):377–381, 2020
H. Shafieasl
Symmetric Module and Connes Amenability
Sahand Communications in Mathematical Analysis, 5(1):49–59, 2017
H. Shafieasl, M.H. Sattari
Product of Derivations on Triangular Banach Algebras
Journal of Hyperstructures, 6(1), 2017
M.H. Sattari, H. Shafieasl
On the extension of inner derivations from dense ideals in Banach algebras
arXiv preprint 2026
H. Shafieasl, A. M. Tavakkoli