Hamed Mohammadi

Email: ad4hn7@r.postjobfree.com

LinkedIn: https://www.linkedin.com/in/hamed-mohammadi-336a25a9/ Phone: 813-***-****

Address: Orlando, FL

SUMMARY

Experienced data scientist specializing in operations research, with a strong background in practical applications. Proficient in identifying operational gaps, formulating data-driven questions, and implementing innovative AI-based solutions to address organizational needs. Demonstrated success in leading impactful data science projects in collaboration with diverse corporations, emphasizing a commitment to achieving tangible and data-driven results. Dedicated to team development, continuous learning, and contributing to overall success in the dynamic and evolving field of data science. SKILLS

Programming Languages: Python, SQL, Matlab, C++, R Studio, Latex, RMarkdown

Data Science Proficiencies:

o Data Preprocessing, Data Cleaning, Data Manipulation, Data Visualization, Data Storytelling, Statistical Analysis (e.g., Hypothesis testing, Distribution fitting), Database Management o Complex Data Visualization: Skilled in creating visually appealing data representations using Matplotlib, Seaborn, and Tableau.

o Library: PyTorch, Tensorflow, Keras, NLTK, Scikit-learn, Numpy, Pandas, Matplotlib, Seaborn, Scipy, NeMo

Operations Research & Optimization :

o Mathematical Modeling: Expertise in formulating and solving optimization problems. Inventory Control, Route Optimization, Facility Location, transportation planning, supplier selection

o Proficient in formulating complex optimization problems using linear programming, integer programming, and nonlinear programming. Dynamic programming, Network optimization, Stochastic Optimization, Simulation Modeling

o Metaheuristic Optimization: Employing advanced optimization techniques for efficiency enhancement.

Deep Learning & Machine Learning Techniques:

o Graph Neural Networks: Node2Vec, GraphSAGE, DeepWalk, Graph Attention Mechanism, Node Importance Metrics, Graph Classification, Node Classification, Link Prediction o Convolutional Neural Networks (CNN): VGG, ResNet, Inception, Fine-tuning Pre-trained Models, Brain Region Segmentation, Tumor Detection in Medical Images o PCA, Neural Network, Decision Tree, Random Forest, XGBoost, SVM, K-NN, AdaBoost, Clustering Algorithms (e.g., K-means, DBSCAN), Linear Regression, Logistic Regression, Anomaly Detection, Reinforcement Learning

Software:

o Arena, Simio, Excel, Tableau, Power BI, Optimization Solvers (Gurobi and GAMS), SPSS, Minitab, Eviews, FSL (FMRIB Software Library)

Cloud Computing: Microsoft Azure, Databricks

Soft Skills: Idea Generation, Critical Thinking, Problem-Solving, Leadership, Communication, and Flexibility

EDUCATION

University of Central Florida

Ph.D. Candidate in Industrial Engineering & master's in System Engineering

Amirkabir University of Technology

B.Sc. and M.Sc. in Industrial Engineering & Management Systems Orlando, FL

2019-2024

Tehran, IRI

2009-2016

WORKING EXPERIENCE

University of Central Florida [Senior research assistant] 2021-Now

• Project Title: GNN-Based Prediction of Multiple Sclerosis (MS) Patients Utilized GNN methodologies to predict Multiple Sclerosis (MS) patients using rest state fMRI data, contributing to the advancement of diagnostic tools in neurology. Optimized Graph Neural Networks:

• Applied metaheuristic optimization techniques to fine-tune GNN parameters, enhancing the accuracy of MS patient prediction.

• Employed political optimizer and particle swarm optimizer to explore the parameter space efficiently.

• Project Title: Optimization for Brain Tumor Detection with CNNs Led the development of an innovative approach by combining political optimizer, particle swarm optimizer, and Convolutional Neural Network (CNN) for brain tumor detection. Responsibilities and Achievements:

Metaheuristic Optimization Integration:

• Utilized expertise in metaheuristic optimization to tailor political optimizer and particle swarm optimizer for optimizing CNN hyperparameters.

• Enhanced the CNN model's sensitivity and specificity for improved brain tumor detection performance.

• Project Title: Medicinal Plant Identification using Deep Learning Responsibilities and Achievements:

AI-Based Medicinal Plant Identification

• Implemented deep learning techniques for the accurate identification of medicinal plants.

• Focused on global average pooling to enhance model generalization and robustness.

• Achieved high accuracy in medicinal plant identification, contributing to pharmaceutical research and species conservation.

• Established a robust framework for automated plant identification adaptable to various ecological settings.

• Project Title: Developing a Dynamic Traffic Management System Responsibilities and Achievements:

Intelligent Traffic Management System

• Led the development of a dynamic traffic management system using advanced graph-based optimization techniques.

• Utilized graph models to optimize real-time traffic flow, adapting signal timings, and rerouting strategies.

• Successfully developed and implemented an intelligent traffic management system, resulting in a significant reduction in traffic congestion.

• Improved overall traffic flow through dynamic signal adjustments and adaptive rerouting strategies.

Iran Transportation organization [Data scientist] 2019-2021

Project Title: Data-Driven Optimization for locate Logistic Hubs and Dry Ports Played a pivotal role as a data scientist in a project utilizing data-driven optimization models to locate Iranian logistic hubs and dry ports.

Network Analysis and Graph Theory:

• Applied network analysis and graph theory to model and optimize the logistics network for efficient location planning of hubs and dry ports.

Dadeh Pardazan Company [Data Analyst] 2017-2019

Responsibilities and Achievements:

• Collaborated as a data analyst in a team responsible for implementing Enterprise Resource Planning

(ERP) software for various organizations.

• Conducted data analysis to streamline business processes and optimize the utilization of ERP systems.

• Played a key role in facilitating the adoption of ERP software, contributing to enhanced organizational efficiency and workflow optimization.

Amirkabir University of Technology 2013-2017

Teacher assistant

Project Title: Jobshop Planning for the Printing Industry Responsibilities and Achievements:

• Developed a flexible jobshop planning model for the printing industry.

• Considered factors such as the selection of manufacturing power, priority of work, and changing paper types.

• Successfully implemented a flexible planning model, improving efficiency and adaptability in the printing industry.

• Addressed manufacturing power selection, work prioritization, and paper type changes for enhanced operational optimization.

Project Title: Green Supplier Selection under Fuzzy Uncertainty Responsibilities and Achievements:

• Developed a novel group decision-making method for green supplier selection.

• Addressed uncertainties using type 2 fuzzy logic to enhance the decision-making process.

• Successfully implemented a group decision-making method for green supplier selection.

• Contributed to sustainable supply chain practices by incorporating type 2 fuzzy uncertainty in the decision-making process.

Thesis Title: Metaheuristic Models for Inventory Control under Uncertainty Responsibilities and Achievements:

• Developed novel metaheuristic optimization models (PSO_BBO, MOPSO_BBO) for inventory control, focusing on improving efficiency under uncertainty.

• Applied fuzzy logic for demand forecasting, enhancing single and multi-objective inventory optimization strategies.

• Successfully developed and implemented metaheuristic models for advanced inventory control.

• Improved efficiency under uncertainty, contributing to more robust and adaptive inventory optimization.

RESEARCH

University of Central Florida

Decoding Task-Based fMRI Data with Graph Neural Networks

GNN-Based Prediction of Multiple Sclerosis (MS) Patients

Optimization for Brain Tumor Detection with CNNs

Amirkabir University of Technology

Data-Driven Optimization for Iranian Logistic Hubs and Dry Ports

AI-Based Medicinal Plant Identification with Deep CNN

Develop new metaheuristic optimization models (PSO_BBO) LANGUAGES

English, Persian

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