Curriculum Vitae
Milad Rayka
Postdoctoral Research Fellow in Computational Chemistry & Machine Learning
Tehran, Iran | Email: milad.rayka@yahoo.com
Research Interests
My research interfaces data-driven artificial intelligence, molecular informatics, and quantum chemical physics to resolve complex structural bottlenecks in drug discovery, biocatalysis, and solid-state materials design.
- Thermoelectric Materials: Applying ML and DL models to accelerate the discovery of high-performance thermoelectric materials, focusing on key transport properties such as Seebeck coefficient, thermal conductivity, and figure of merit (zT). Utilizing active learning to explore high entropy material compositions and curate datasets by identifying and resolving noisy or inconsistent data points.
- Drug Discovery and Molecular Informatics: Designing ML and DL geometry-based scoring functions to predict protein-ligand binding affinity. Developing software for streamlined feature vector generation from protein-ligand complexes. Accelerating virtual screening pipelines to identify novel selective human carbonic anhydrase inhibitors. Leveraging ML and DL approaches to enhance enzyme engineering workflows.
- Reliability & Uncertainty Quantification: Integrating uncertainty quantification protocols within ML and DL models to enhance reliability, benchmark prediction confidence, and characterize uncertainty in predicted properties across molecular and materials science applications.
Professional Appointments & Grants
Computational Chemistry Postdoctoral Fellow | Shahid Beheshti University, Tehran
2024 - Present
Funding:
- Postdoctoral Research Grant | Iran National Science Foundation (INSF) (2024 & 2025)
- Co-Principal Investigator (Co-PI) | Pioneers Research Grant, INSF (2024)
- Co-Principal Investigator (Co-PI) | Institutional Research Project Grant, INSF (2025)
Education
Ph.D., Physical Chemistry (GPA: 18.93/20)
Chemistry & Chemical Engineering Research Center of Iran (CCERCI), Tehran
2018 - 2022
M.Sc., Physical Chemistry (GPA: 18.99/20)
Shahid Beheshti University, Tehran
2015 - 2017
B.Sc., Applied Chemistry (GPA: 18.42/20)
Shahid Beheshti University, Tehran
2011 - 2015
Technical Skills
Data-Driven Algorithms & AI
- Deep Learning Architectures
- Traditional Machine Learning Frameworks
- Uncertainty Quantification (UQ)
- Molecular & Crystalline Generative Pipelines
- ML-assisted QSAR / ADMET
Programming & Frameworks
AI / ML Core:
Scientific, Bio & Materials Stack:
Domain Software & Suites
- Quantum Chemistry: Gaussian, GAMESS, AIMAll
- Bioinformatics / Docking: AutoDock (Vina), PyMOL
Research Experience
Ph.D. Dissertation Work (2018 - 2022)
Title: Ligand and Protein Interaction Prediction Using Machine Learning
- Engineered distance-weighted interatomic contact pipelines generating localized mathematical descriptors for complex ensemble predictive engines.
- Engineered and deployed the standalone 3S Application, establishing graphical user interfaces for non-programming computational biology cohorts.
M.Sc. Thesis Work (2015 - 2017)
Title: Development of Effective Electronic Structure Theory for Muonic Molecular Systems: Hartree-Fock and Kohn-Sham Equations
- Isolated light nuclear effects outside classical Born-Oppenheimer constraints utilizing multi-particle nuclear-electronic orbital (NEO) methods.
- Derived non-Coulombic mathematical operators, embedding structural quantum variances directly into standard Hartree-Fock and Density Functional Theory (DFT) solvers.
Honors & Awards
- National Elite Fellowship: Awarded by the Iran National Elite Foundation (2022).
- National Elite Fellowship: Awarded by the Iran National Elite Foundation (2018).
- National Ph.D. Matriculation Examination: Ranked 2nd Nationwide in Physical Chemistry across all applicants (2018).
- M.Sc. Academic Valedictorian: Ranked 1st over graduate class, Shahid Beheshti University (2017).
- Direct M.Sc. Graduate Admission: Admitted under "Exceptional Talents" quota, bypassing the standard National Entrance Exam (2015).
- B.Sc. Academic Valedictorian: Ranked 1st over undergraduate class, Shahid Beheshti University (2015).
Teaching & Mentorship
- Graduate Teaching Assistant: Advanced Quantum Chemistry I & II, Shahid Beheshti University (2016 - 2017)
- Undergraduate Teaching Assistant: Quantum Chemistry, Shahid Beheshti University (2014 - 2015)
- Technical Instructor: Python for Molecular Modeling, CCERCI (2020 - 2021)
- Technical Instructor: Applied Molecular Modeling via Wolfram Mathematica, CCERCI (2019 - 2020)
Peer-Reviewed Publications & Software
Publications and projects are available in the below links: