Bio
For all inquiries, email moc.doosrelyk@0.
Education
University of Southern California | Ph.D. Student, Chemical Engineering.
Advisor:
Prof. Anupam Madhukar
at the
Nanostructure Materials and Devices Lab.
Quantum photonics, deep learning, and information science.
May 2026 - Present
Stanford University | Ph.D. Student, Chemical Engineering. GPA: 4.1 / 4.0.
Core courses in ChemE and physics. Transferred to USC in Summer 2026.
Sept. 2025 - March 2026
University of Minnesota, Twin Cities | B.Ch.E. in Chemical Engineering, B.S. in Mathematics with high distinction at age 19. GPA: 3.99 / 4.0.
Double minors in chemistry and computer science.
Sept. 2021 - May 2025
USC graduate courses
- Directed Research (with Prof. Anupam Madhukar)
Stanford graduate courses
- Applied Math: A World of Flows (with legendary Prof. Tadashi Tokeida)
- Chemical Kinetics and Reaction Engineering
- Microhydrodynamics
- Molecular Thermodynamics
- Solid-State Physics II
- Ultrafast Quantum Physics
UMN graduate-level courses
- Advanced Machine Learning
- Deep Learning
- NLP with Deep Learning
- Robot Vision
- Nonlinear Dynamic Systems and Control
- Numerical Optimization
- Microelectronic Fabrication+Lab
- Computational Fluid Dynamics
- Stochastic (Ito) Calculus
- Quantitative Hedge Fund Strategies
- Portfolio Optimization
Undergraduate courses (Math)
- Partial Differential Equations I/II
- Honors Algorithms/Data Structures I/II
- Enumerative Combinatorics
- Graph Theory
- Numerical Methods I/II
- Complex Analysis
- Fundamental Structures of Algebra
- Numerical Linear Algebra
- Readings: Number theory, Galois theory, point-set and algebraic topology, Analysis I/II/III (Amann & Escher), measure theory, classical mechanics (Lanczos), Riemannian geometry/general relativity
Undergraduate courses (ChemE)
- Mass/Energy Balances
- Organic Chemistry I/II/Lab
- Materials Eng.
- Physical Chemistry
- Thermodynamics
- Process Analytical Chemistry
- Transport Phenomena
- Reaction Eng.
- Mass Transport/Separations
- Unit Operations Lab I/II
- Biomolecular Eng.
- Quantum Mechanics
- Solid-State Physics (with legendary Prof. Boris Shklovskii)
- Chemical Engineering Design
Past Projects
- Directed reading on partition theory & reinforcement learning (Fall 2021, Spring 2022)
- Java library for computing chromatic polynomials of graphs (Spring 2022)
- TA for CSCI 1933: Algorithms and Data Structures (Spring 2022)
- UROP project on 2D cellular harmonics using graph Fourier analysis with Prof. Meghan Driscoll and Prof. Jeff Calder (Spring 2024)
- Novella: Hierarchical models of generative author imitation learning (Fall 2022)
- St3: Exploration algorithm for deep reinforcement learning models in environments with sparse rewards and deceptive constraints
- ChemE capstone design: Fully-integrated plant for catalytic hydrogenation of CO2 to CH3OH
- Fabrication of CMOS transistors (Fall 2023)
Work Experience
Huntington Ingalls Industries | Machine Learning Engineering IV Intern
Deep reinforcement learning: Deceptive-reward exploration, model-free and offline RL for satellite guidance. Publications pending.
May 2025 - Aug. 2025
Applied Materials | Process Engineering Intern
PECVD and dielectric depositions. Engineered various thin-film chemistries and direction-selective deposition processes.
May 2024 - Aug. 2024
Altair Engineering | Polymer Material Data Analytics Intern
Developed CFD solvers and machine-learning test suite for simulating polymer melt flows in injection molding.
May 2023 - Aug. 2023
Talyn Air | Data Science Intern
Market research and competitive intelligence, cost/GHG estimates, and optimal routing for eVTOL fleet.
Sep. 2022 - Dec. 2022