Helia Aghaee Rad

Ph.D. researcher in computational and theoretical chemistry with experience in electronic-structure theory, DFT, HF/SCF, molecular-orbital analysis, variational quantum algorithms, scientific Python, and HPC, while actively building expertise in machine learning for chemistry and quantum information. I enjoy taking on unfamiliar scientific problems, quickly learning the methods and tools they require, and applying that knowledge to practical computational work. I am especially motivated by challenging projects where I can continue learning while contributing meaningfully to the team.

Molecular-Orbital Localization for Quantum Computing - University of Toronto - Toronto, ON

(2026-09)

• Research Goal: Investigating how molecular-orbital representations influence resource requirements in distributed quantum computing for chemistry.
• Workflow & Methods: Using Hartree–Fock/self-consistent-field (SCF) theory and PySCF for molecular electronic-structure calculations and orbital analysis, with quantum-computing workflows being developed using Qiskit and IBM Quantum.
• Analysis & Current Direction: Evaluating molecular-orbital representations for chemical interpretability, electronic-structure accuracy, and their impact on quantum-circuit resource requirements.
• Tools: Python, PySCF, Qiskit, IBM Quantum, NumPy, ChemCraft, Git/GitHub.

Shot-Efficient VQE for Molecular Systems - NCSU

(2025-09 - 2025-12)

• Research Goal: Investigated Variational Quantum Eigensolver (VQE) approaches for estimating molecular ground-state energies while reducing quantum-measurement requirements.
• Workflow & Methods: Developed a computational framework for small molecular systems such as H2 and LiH, including molecular Hamiltonian construction, qubit representations, variational circuits, and symmetry-based qubit reduction.
• Analysis & Outcome: Studied VQE performance under finite-shot and noisy conditions and examined benchmarking and error-mitigation strategies using Full Configuration Interaction (FCI) reference energies, zero-noise extrapolation (ZNE), and ML-based post-processing.
• Tools: Python, Qiskit, PySCF, OpenFermion.

Photoinduced Electronic Transitions and Metastable Quantum Materials - NCSU

(2024-08 - 2026-05)

• Research Goal: Investigated photoinduced reaction pathways and metastable states in A2 X2 compounds (A = Na, Rb; X = S, Se, Te), with emphasis on light-induced electronic and structural transformations and nonclassical bonding.
• Workflow & Methods: Performed k-point convergence testing, full geometry optimizations, ground-state DFT calculations, and excited-state ∆SCF simulations using VASP, including excitation, structural relaxation, and de-excitation calculations on HPC systems.
• Analysis & Outcome: Analyzed projected band structures, density of states, structural energetics, and phonon calculations to characterize photoinduced electronic and structural changes and assess the stability of predicted metastable states.
• Tools: VASP 6.4/6.5.1 (PBE, r2SCAN), Python (py4vasp), Phonopy, VESTA, Linux/Bash, SLURM, NCSU HPC.

Computational Conformational Analysis of Strapped Metal Porphyrins - NCSU

(2025-08 - 2026-03)

• Research Goal: Investigated conformational energy landscapes of strapped metal porphyrins to identify low-energy structures relevant to experimental synthetic targets.
• Workflow & Methods: Built molecular models and performed systematic 30◦ dihedral-angle scans with constrained DFT optimizations to map conformational energy landscapes, followed by full relaxation of selected low-energy structures using PBE0/def2-TZVP.
• Analysis & Outcome: Compared relative energies and geometries of candidate conformers to identify energetically favorable structures and relate computational predictions to experimental observations.
• Tools: ORCA 6.1, Gaussian, Avogadro.

MOF-Based Nanocarriers for Drug Delivery - Sharif University of Technology

(2022-01 - 2023-09)

• Research Goal: Developed pH-responsive MOF-based nanocarriers for targeted drug-delivery applications.
• Workflow & Methods: Synthesized and functionalized metal-organic-framework (MOF) materials and characterized their structural, surface, thermal, and spectroscopic properties using XRD, BET, TGA, NMR, FT-IR, and UV-Vis.
• Analysis & Outcome: Evaluated cytotoxicity, imaging, and drug-release data to assess material performance and drug-delivery behavior.
• Tools: XRD, BET, TGA, NMR, FT-IR, UV-Vis.

Ph.D. - Chemistry - University of Toronto (2026-09 - 2030)

M.S. - Chemistry, Computational & Theoretical Chemistry - North Carolina State University (2024-08 - 2026-05)

B.Sc. - Applied Chemistry - Sharif University of Technology (2019 - 2023)