PHYSICS • DATA • AI • SCIENTIFIC COMPUTING

Dr. Asnakew Bewketu Belete

Physicist · Data Scientist · Machine Learning Engineer · Researcher

PhD-trained physicist and data scientist with more than five years of international experience across astrophysics, machine learning, scientific computing, and full-stack data systems.

AB
Researcher & Engineer
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About Me

I am a PhD-trained physicist and data scientist working at the intersection of fundamental research, computational science, machine learning, and software engineering.

My scientific background is rooted in astrophysics and cosmology, with research spanning active galactic nuclei, galaxy evolution, gas kinematics, variability, time-series analysis, statistical inference, and computational modeling.

Alongside academic research, I develop practical data and machine-learning systems, including scalable ETL pipelines, analytics platforms, predictive models, APIs, and full-stack web applications.

My work is driven by a simple principle: use rigorous scientific thinking and modern computational tools to transform complex data into useful knowledge and intelligent systems.

PhD Physics — Astrophysics & Cosmology
5+ Years of International Experience
12+ Peer-Reviewed Publications
3 Core Domains: Physics, Data & AI
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Professional Experience

2025 — Present
INDUSTRY & APPLIED AI

Freelance Data Scientist & Machine Learning Engineer

  • Designed and deployed machine-learning models for classification, regression, and forecasting.
  • Built scalable ETL pipelines and data processing workflows.
  • Performed exploratory data analysis and statistical modeling on complex datasets.
  • Developed production-ready analytics systems and APIs.
2024 — 2025
MACHINE LEARNING

Machine Learning Engineer Intern

Zeekr Technology Europe · Sweden

  • Developed deep-learning models for time-series and sensor-based data.
  • Performed feature engineering, model validation, and optimization.
  • Built reproducible machine-learning pipelines for scalable data processing.
2021 — 2024
ASTROPHYSICS & RESEARCH

Postdoctoral Researcher

Chalmers University of Technology · Sweden

  • Conducted large-scale statistical analysis of astrophysical and observational datasets.
  • Investigated AGN host galaxies, gas kinematics, and multi-wavelength properties.
  • Applied computational modeling and uncertainty-quantification methods.
  • Contributed to peer-reviewed publications and international collaborations.
  • Supervised and supported PhD students in data-driven astrophysical research.
2017 — 2021
ASTROPHYSICS & COSMOLOGY

PhD Researcher

Federal University of Rio Grande do Norte · Brazil

  • Performed time-series analysis of AGN and quasar variability.
  • Developed statistical and numerical models for astrophysical systems.
  • Applied Bayesian inference and parameter estimation techniques.
  • Published research in international peer-reviewed journals.
2012 — 2017
ACADEMIA & TEACHING

Physics Lecturer

Addis Ababa University & Madda Walabu University

  • Taught Classical Mechanics, Quantum Mechanics, Electrodynamics, and Statistical Physics.
  • Supervised laboratory work and undergraduate research projects.
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Research

My research combines astrophysics, statistical inference, computational modeling, and advanced time-series analysis to investigate complex astrophysical systems.

Active Galactic Nuclei

Research into AGN, quasars, variability, host galaxies, nuclear environments, and multi-wavelength observations.

Time-Series Analysis

Statistical analysis and modeling of complex temporal signals, including variability, multifractality, and causal relationships.

Computational Modeling

Numerical simulations, statistical inference, Bayesian methods, parameter estimation, and uncertainty quantification.

Large-Scale Data Analysis

Scientific data processing, statistical analysis, reproducible workflows, and computational approaches to large observational datasets.

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Selected Projects

01
FULL-STACK WEB APPLICATION

iSpotera

A hospitality platform for booking and listing services, built as a full-stack web application.

React Node.js SQL REST APIs
Visit iSpotera
02
AI & EDUCATION

YeneMind

An AI-driven adaptive learning platform using machine learning, real-time analytics, and personalized learning workflows.

Machine Learning Python SQL APIs
Visit YeneMind
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SCIENTIFIC COMPUTING

Astrophysical Data Modeling

Computational and statistical modeling of astrophysical systems, including AGN variability, galaxy kinematics, and observational datasets.

Python Bayesian Inference Statistics Modeling
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MACHINE LEARNING

ML & Data Pipelines

Development of reproducible machine-learning workflows, ETL pipelines, predictive models, and scalable data-processing systems.

Scikit-learn TensorFlow Pandas NumPy
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Technical Skills

Programming

Python JavaScript SQL

Machine Learning & AI

Scikit-learn TensorFlow Deep Learning Time-Series Analysis

Data & Visualization

Pandas NumPy Matplotlib Seaborn Plotly Power BI Tableau

Scientific Computing

Numerical Simulation Bayesian Inference Statistical Modeling Computational Modeling

Data Engineering

ETL Pipelines Data Processing SQL Databases Data Architecture

Systems & Cloud

Linux Docker AWS Git

Web Development

React Node.js REST APIs

Research

Astrophysics AGN Physics Galaxy Evolution Statistical Inference
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Education

2021

PhD in Physics

Astrophysics & Cosmology

Federal University of Rio Grande do Norte, Brazil

2012

MSc in Physics

Addis Ababa University

2010

BSc in Applied Physics

Mizan-Tepi University

Certifications

Machine Learning with Python — MITx, 2024 AWS Certification — 2025 Higher Diploma in Teaching — 2015
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Selected Publications

2026 · MNRAS

Multifractal behaviour and causality effects in the time series of the blazar Mrk 421

2025 · MNRAS

Kinematics of synthetically observed high-z rotating discs: reliability and biases of 3D fitting tools

2024 · A&A

AGN feeding along a one-armed spiral in NGC 4593

2024 · MNRAS

Multifractality signatures in lensed quasars

2023 · arXiv

Probing the interstellar medium of the quasar BRI0952-0115

2021 · A&A

Molecular gas kinematics in the nuclear region of nearby Seyfert galaxies with ALMA

2020 · ApJS

A Search for Rotation Periods in 1000 TESS Objects of Interest

2019 · ApJ

A Novel Approach to Study the Variability of NGC 5548

Additional publications cover quasars, multifractality, Seyfert galaxies, molecular gas, AGN variability, and cosmological evolution.

View ORCID Profile
Languages English — Advanced German — A2 Portuguese — Very Good Amharic — Native Swedish — Intermediate
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Let's Connect

Whether you are interested in scientific collaboration, data science, machine learning, research, or software development, I would be happy to connect.