Portfolio

Selected work in AI, robotics, optimization, creativity, and intelligent engineering systems

I design algorithms and engineering systems that operate under uncertainty, where assumptions are incomplete and traditional methods lose reliability. My work spans AI-driven physical systems, humanoid and autonomous robotics, geometry-aware modeling, intelligent optimization, and aerospace-relevant computation, with a consistent emphasis on robustness, interpretability, and creative system design.

This portfolio presents representative contributions, not an exhaustive record.

Core Focus Areas

• Creative Engineering and Innovation Methodologies

• AI and Machine Learning for Physical Systems

• Humanoid and Embodied Robotics

• Intelligent Optimization and Swarm Algorithms

• Geometry-Aware Modeling of Curves and Surfaces

• Autonomous, Control, and Decision Systems

• Aerospace Trajectory Optimization and NASA-Relevant Research

Aerospace Trajectory Optimization and NASA-Relevant Research

Orbital mechanics under realistic constraints

Space mission design frequently involves constrained, multi-revolution transfers where classical Lambert solvers and idealized assumptions fail.

I implemented and analyzed advanced Lambert formulations and trajectory optimization frameworks, including constrained and multi-revolution methods relevant to aerospace mission planning and NASA-related research.

Key contributions

• Orbital mechanics and boundary-value problem solvers

• Constrained and multi-revolution trajectory optimization

• Numerical validation against analytical and contour-integral references

Impact

• NASA-relevant research contributions

• High-fidelity, aerospace-grade trajectory solutions

• Robust computational tools for mission design under uncertainty

Intelligent Braking Systems

Treating braking as a decision-making process

Despite major advances in sensing and autonomy, vehicle braking systems remain largely reactive.

I proposed an intelligent braking framework that treats deceleration as a predictive, decision-based control problem rather than a reflexive response, with direct relevance to safety-critical and autonomous systems.

Key contributions

• Control-theoretic formulation of intelligent braking

• System-level decision-making architecture

• Safety-critical design under uncertainty

Impact

• Independently conceived intelligent braking system concept

• Strong commercialization potential in a multi-billion-dollar industry

Humanoid and Embodied Robotics

Intelligence emerging through physical interaction

Many humanoid robotic systems rely on predefined stability assumptions that break during transitions, balance recovery, or real-world interaction.

My work focuses on balance, posture transitions, and motion initiation, treating intelligence as an emergent property of embodiment and interaction rather than scripted behavior.

Key contributions

• Dynamics and control of humanoid systems

• Balance and posture transitions under uncertainty

• Embodiment-aware system design

• Integration of control theory and physical interaction

Impact

• Robotics research contributions

• Cross-disciplinary insight connecting control, intelligence, and embodiment

NIMA: Geometry-Aware NURBS Modeling

Adaptive curve and surface refinement driven by curvature

Conventional NURBS modeling relies on uniform refinement or heuristic error measures, which often fail in regions of high curvature and geometric complexity.

I developed NIMA (NURBS Iterative Micro-move Adjuster), a geometry-aware refinement framework that adapts control points and knot placement based on curvature and stability.

Key contributions

• Curvature-driven knot insertion and control-point adjustment

• Stability-aware refinement rules

• Robust benchmarking against IRLS, greedy, uniform, and spline-based methods

• Extension from curve fitting to surface modeling

Impact

• Peer-reviewed publications

• Extensive numerical validation

• Foundation for future geometry-aware optimization frameworks

Intelligent Optimization and PSO Variants

Robust swarm-based optimization for real engineering systems

Standard PSO methods often degrade in noisy, constrained, or ill-conditioned environments.

I designed and evaluated adaptive PSO variants with improved convergence stability, constraint handling, and robustness, tailored for real engineering problems rather than idealized benchmarks.

Key contributions

• Adaptive swarm dynamics

• Noise-robust objective evaluation

• Constraint-aware optimization strategies

• Statistical robustness analysis

Impact

• Reliable optimization in complex design landscapes

• Practical pipelines for engineering design and control

AI for Physical and Engineering Systems

Learning where equations alone are insufficient

Highly nonlinear and multiphysics systems often exceed the limits of purely analytical modeling.

I applied AI and physics-aware learning methods to model, predict, and interpret complex engineering data, including defect detection, fatigue assessment, and intelligent system behavior.

Key contributions

• Physics-informed neural modeling

• AI-assisted defect detection and prediction

• Hybrid data-driven and physics-based reasoning

Impact

• 40+ peer-reviewed publications

• 2,900+ citations | H-index: 23

• Cross-disciplinary impact across AI and engineering

Creativity and Innovation

Engineering beyond optimization

Creativity is a central part of my engineering philosophy. I develop systems, algorithms, and methodologies that challenge conventional formulations and explore alternative representations when standard approaches quietly fail.

Representative activities

• Authoring a forthcoming book: Creative Methods for MATLAB Programming

• Developing curvature-adaptive and geometry-aware algorithms

• Exploring creative balance and stability mechanisms in humanoid robots

• Integrating AI, control, and intuition into system-level design

Teaching Excellence and Mentorship

From memorization to independent reasoning

I bring over a decade of university-level teaching and mentoring experience, spanning undergraduate to graduate education.

• Instructor and lecturer for more than 15 engineering courses

• Academic Tutor & Mentor at Iowa State University (teaching 12 engineering courses)

• Technical workshops in MATLAB, optimization, scientific computing, and programming

Selected recognition

• Tutor of the Month, Athletic Academic Services, Iowa State University (2025)

• Best Lecturer Award (MATLAB), Isfahan Municipality (2014)

• Top Ten Lecturer, Islamic Azad University (2014)

Awards, Leadership, and Recognition

• Inventor of an independently conceived intelligent braking system concept

• Excellent Paper Award for humanoid robotics research (2017)

• President, Iranian Scholars & Students Association, Iowa State University

• Academic and professional leadership roles across institutions

Design Philosophy

I do not design systems solely to optimize performance.
I design systems that remain reliable when assumptions fail.

Much of my work begins where existing methods appear sufficient, until they quietly break under real conditions.

Writing and Thought Leadership

I write on creativity, innovation, and future engineering systems, exploring how ideas form before proof exists and how intuition, structure, and computation interact at the edge of discovery.

Get in Touch

Reach out anytime; I’ll respond promptly.

contact@nimasina.com

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