プロフィール詳細

プロジェクトを作成

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Dr. Anikeya A.に依頼

Belgium

Computational Scientist | Research Software Engineer (RSE) | Machine Learning Engineer | PhD Materials Science + MS CS

プロフィール概要

I am a Computational Scientist with a technical background spanning Materials Science, Computer Science, Physics, and Mathematics. My work focuses on the intersection of physical system modeling and high-performance software engineering. Technical Background: Modeling & Simulation: Extensive experience in density functional theory (DFT), molecular dynamics (MD), and developing machine-learned interatomic potentials (MLFF). Machine Learning: Implementation of Graph Neural Networks (GNNs), Equivariant Neural Networks (NequIP, Allegro), and computer vision pipelines (YOLOv8). Scientific Computing: Development of scalable computational workflows for HPC environments, including parallel analysis scripts for processing trajectories exceeding 1 billion atoms. Applied Mathematics: Background in Bayesian inference for statistical modeling and the application of analytical expressions to optimize numerical methods. Professional Experience & Projects: Research Software: Developed a Python-based toolkit for the generation of periodic multi-layer moiré supercells, utilizing Numba JIT and multiprocessing for scalability. Project Leadership: Led a team to design a computer vision pipeline for real-time player tracking and trajectory prediction using YOLOv8 and LSTMs. Software Tools: Contributor to open-source repositories for estimating photoluminescence (PL) line shapes and analyzing stacking configurations in large-scale simulations. Current Status & Goals: I am currently based in Mons, Belgium, with unlimited labor market access. I am specifically interested in 100% remote positions in Research Software Engineering (RSE), algorithm development, or system modeling where I can contribute to long-term R&D goals. Technical Stack: Python (NumPy, SciPy, Numba, PyTorch), C++, Linux, SLURM, VASP, LAMMPS, Quantum ESPRESSO.

専門分野

• ★ Computational Physics
• ★ Applied Physics
• ★ Computational Sciences
• ☆ Data Analysis
• ☆ Image Processing
• ☆ Computer Simulation/Computational Modeling
• ☆ Data Processing
• ☆ Data Exploration
• ☆ Machine Learning
• ☆ Neural Networks
• ☆ Deep Learning
• ☆ Computer Vision
• ☆ Statistics
• ☆ Applied Statistics
• ☆ Statistical Computing
• ☆ Mathematical Statistics
• ☆ Wave Mechanics
• ☆ Statistical Mechanics
• ☆ Quantum Mechanics
• ☆ Theoretical Physics
• ☆ Applied Mathematics
• ☆ Mathematical Models
• ☆ Mathematics Education
• ☆ Mathematical Physics
• ☆ Differential Equations
• ☆ Computational Mathematics
• ☆ Pure Mathematics
• ☆ Calculus
• ☆ Geometry
• ☆ Discrete Mathematics
• ☆ Integral Equations

サービス

• Writing
• Research
• Data & AI

Writing Translation

Research Scientific and Technical Research

Data & AI Predictive Modeling, Statistical Analysis, Data Visualization

職務経験

Computational Research Scientist (PhD Researcher)

University of Southern California, Los Angeles

8月 2019 - 12月 2025

学歴

Ph.D. in Materials Science

University of Southern California

8月 2019 - 12月 2025

MS Computer Science

University of Southern California

5月 2023 - 5月 2025

BS

University of California, Santa Cruz

9月 2014 - 6月 2018

BA

University of California, Santa Cruz

9月 2014 - 6月 2018

認定資格

• Python for Data Science and Machine Learning Bootcamp

  udemy

  https://www.udemy.com/certificate/UC-b3d66706-a609-45e3-9c10-c28bbb80a5e7/

  1月 2026 - 現在

出版物

JOURNAL ARTICLE

Anikeya Aditya, Ayu Irie, Nabankur Dasgupta, Rajiv K. Kalia, Aiichiro Nakano, Priya Vashishta (2026). Emerging Ferroelectric Domains: Stacking and Rotational Landscape of MoS2 Moiré Bilayers . ACS Nano.

Anikeya Aditya, Ayu Irie, Ken-ichi Nomura, Shogo Fukushima, Shinnosuke Hattori, Rajiv K. Kalia, Aiichiro Nakano, Vadim Rodin, Fuyuki Shimojo, Shigetaka Tomiya, et al. (2024). Thermoelectric Grain Boundary in Monolayer MoS2 . The Journal of Physical Chemistry C.

Anikeya Aditya, Kory Burns, Anne Marie Z. Tan, Jordan A. Hachtel, Nitish Baradwaj, Ankit Mishra, Thomas Linker, Aiichiro Nakano, Rajiv Kalia, Eric J. Lang, et al. (2023). Tailoring the Angular Mismatch in MoS2 Homobilayers through Deformation Fields . Small.

Anikeya Aditya, Ankit Mishra, Nitish Baradwaj, Ken-ichi Nomura, Aiichiro Nakano, Priya Vashishta, Rajiv K. Kalia (2023). Wrinkles, Ridges, Miura-Ori, and Moiré Patterns in MoSe2 Using Neural Networks . The Journal of Physical Chemistry Letters.