プロフィール詳細

プロジェクトを作成

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Şerafettin G.に依頼

Turkey

Chemical Engineer & Data Scientist | Machine Learning & Process Simulation

プロフィール概要

I am a Chemical Engineer and Data Scientist specializing in the intersection of chemical processes, and advanced machine learning. With a Master's degree in Chemical Engineering and Data Science, alongside hands-on laboratory experience in pharmaceutical quality control, I bridge the gap between physical chemistry and predictive modeling. My expertise lies in translating complex chemical data into actionable, automated, and predictive systems. I am highly proficient in Python and specialize in building robust machine learning pipelines, process simulations, and digitalization tools. Core Competencies & Tech Stack: Data Science & ML: Python, TensorFlow, PyTorch, Pandas, Scikit-learn, XGBoost, LSTM. Cheminformatics & Chemistry: RDKit, Molecular Property Prediction, Pharma QC workflows. Process Engineering: Process Simulation (DWSIM, Chemcad), MATLAB, Process Control & Fault Detection. Selected Project Experience: Engineered deep learning models using RDKit to predict molecular solubility from SMILES strings. Built comprehensive fault detection frameworks for complex chemical processes (Tennessee Eastman Process) comparing XGBoost and LSTM architectures. Whether you need to optimize a manufacturing process, build predictive models for molecular properties, or digitalize your laboratory data workflows, I deliver rigorous, data-driven solutions tailored to the chemical and pharmaceutical industries.

専門分野

• ☆ Catalysis
• ☆ Mathematical Chemistry
• ☆ Chemoinformatics
• ☆ Analytical Chemistry
• ☆ Spectroscopy
• ☆ Atomic Absorption Spectroscopy
• ☆ Atomic Emission Spectroscopy
• ☆ UV Spectroscopy
• ☆ Fluorescence Spectroscopy
• ☆ IR Spectroscopy
• ☆ Spectrophotometry
• ☆ Mass Spectrometry
• ☆ Liquid Chromatography/HPLC
• ☆ Gas Chromatography
• ☆ Particle Size Distribution
• ☆ Optical Rotation
• ☆ Computational Chemistry
• ☆ Chemical Engineering
• ☆ Chemical Manufacturing
• ☆ Process Chemistry
• ☆ Reactor Design
• ☆ Heat Transfer & Calorimetry
• ☆ Fluid Mechanics
• ☆ Computational Fluid Dynamics
• ☆ Data Analysis
• ☆ Computer Simulation/Computational Modeling
• ☆ Algorithm Design
• ☆ Data Processing
• ☆ Data Exploration
• ☆ Cluster Analysis
• ☆ Data Visualization
• ☆ Data Collection
• ☆ Machine Learning
• ☆ Neural Networks
• ☆ Artificial Intelligence
• ☆ Deep Learning
• ☆ Thermodynamics
• ☆ Mass Transfer
• ☆ Process Engineering
• ☆ Engineering Design
• ☆ Python
• ☆ SPSS
• ☆ Matlab
• ☆ Excel
• ☆ Tensorflow
• ☆ Scikit-learn
• ☆ Hypothesis
• ☆ Peer Review
• ☆ Research Methodology
• ☆ Survey Design & Methodology
• ☆ Meta-Research
• ☆ Feasibility Studies
• ☆ Literature Search
• ☆ Process Design
• ☆ Literature Review
• ☆ Traditional/Narrative Literature Review
• ☆ Systematic Literature Review

サービス

• Research
• Data & AI

Research Meta-Research, Feasibility Study, Scientific and Technical Research

Data & AI Predictive Modeling, Statistical Analysis, Algorithm Design-ML, Data Visualization, Data Mining, Data Cleaning, Data Processing

職務経験

Chemist, Quality Control

Pharmavision

6月 2023 - 2月 2025

学歴

Masters in Chemical Engineering

Yildiz Technical University

9月 2022 - 8月 2024

BS in Chemical Engineering

Bursa Tecnical University - Turkey

9月 2015 - 8月 2021

認定資格

• CFD Simulation Through a Centrifugal Pump

  coursera

  https://coursera.org/share/39c579b53861e9a922c9d9286831f3ae

  6月 2026 - 現在

• ANOVA and Experimental Design

  coursera

  https://coursera.org/share/df2fde1307d5c9a00ce53543e2bd0158

  7月 2025 - 現在

出版物

JOURNAL ARTICLE

Serafettin Gungor, Mert Akin Insel, Hasan Sadikoglu, Mehmet Melikoglu (2025). Prediction of Biocrude Oil Yield From Biomass Hydrothermal Liquefaction Via Interpretable Machine Learning Using Higher Heating Value and Process Parameters . BioEnergy Research.