At Sunfire, I contribute to the design, construction, and commissioning of industrial electrolysis plants, focusing on megawatt-scale solutions that enable the transition to renewable energy. My role involves collaborating with a multidisciplinary engineering team, customers, and suppliers to ensure the efficient and successful implementation of projects.Key Responsibilities:- Basic Engineering:Develop the fundamental design of electrolysis plants, including P&IDs, mass and energy balances, and process documentation.Participate in key workshops (P&ID reviews, HAZOP, LOPA) to optimize system design with customers.- Detail Engineering & Fabrication:Create technical specifications, evaluate supplier offers, and detail engineering documentation to support plant design.Collaborate on 3D model development and guide external production through the fabrication of complex assemblies such as skids and gas separators.- Commissioning & Handover:Oversee the installation, performance testing, and commissioning of electrolysis systems.Ensure successful system handover to the customer after achieving optimal performance.- Innovation & Process Improvement:Integrate innovative technologies from R&D into customer projects.Contribute to process optimization and digitization efforts within the engineering team.

During my working on the application of Reinforcement Learning (RL) in Wastewater Treatment Plants (WWTP), I focused on leveraging advanced machine learning techniques to optimize and improve wastewater treatment processes. Key Responsibilities:- Development of Gymnasium Environment for WWTP:Created a customized simulation environment using OpenAI Gym tailored specifically for WWTP operations.Integrated real-world data and process simulations to ensure the environment accurately reflected the dynamics of wastewater treatment processes.- Evaluation of RL Agents' Performance:Implemented and tested Proximal Policy Optimization (PPO) agent.Conducted rigorous performance evaluations to compare the efficiency and effectiveness of different RL agents in optimizing treatment parameters.Skills Utilized and Developed:- Reinforcement Learning: Applied advanced RL techniques to real-world industrial processes, enhancing decision-making and operational efficiency.- Process Simulation: Utilized process simulation tools to model and simulate WWTP operations, ensuring accurate and reliable RL environment setup.- Python Programming: Leveraged Python for developing simulation environments, implementing RL algorithms, and conducting data analysis.- OpenAI Gym: Customized OpenAI Gym environments to suit the specific needs of WWTP simulations.Wastewater Treatment: Applied engineering principles and domain-specific knowledge to address the challenges in wastewater treatment.This project underscored the potential of RL in optimizing complex industrial processes and contributed to advancing sustainable practices in wastewater treatment. The combination of technical expertise and practical application resulted in a significant enhancement of WWTP operations, showcasing the transformative impact of AI in environmental engineering.

During my work at the Jülich Research Center in Germany, I conducted my master's thesis focused on advancing green hydrogen production through Proton Exchange Membrane Water Electrolysis (PEMWE). This involved:- PEM Cell Development and Improvement: - Developing and refining PEM cells to enhance their efficiency and reliability as a clean energy solution. - Gas Bubble Detection with Deep Learning Algorithm: - Implementing a deep neural network to analyze gas bubbles within different flow field designs of PEMWE cells, specifically targeting the anode side. - Characterizing the Gas Bubble Formation in PEM Cell: - Conducting rigorous testing using transparent PEMWE cells with varied flow field configurations and channel widths to gain insights into performance differences among different designs. - Key Findings: - Demonstrating the superiority of Pin design flow fields, while Serpentine designs showed significant improvement at specific spacings. - Identifying weaker performance of Parallel schemes at certain spacings.Through this experience, I gained valuable experience in PEM cell development, gas bubble detection using machine learning algorithms, and the intricate dynamics of gas bubble formation within PEM cells.Overall, my work at the Jülich Research Center contributed to the ongoing efforts in transitioning towards sustainable energy solutions, particularly in the realm of green hydrogen production. This experience equipped me with invaluable skills in research, problem-solving, and interdisciplinary collaboration, laying a solid foundation for my future endeavors in the field of renewable energy.

I had the privilege of completing an enriching internship at Evonik Industries in Hanau, Germany, from April 1, 2023, to September 30, 2023. Evonik is a global leader in specialty chemicals, with operations in over 100 countries and production plants across six continents.- Key Responsibilities:Conducting Simulations: Utilized ASPEN Plus and AVEVA process simulation software to simulate electrolyte systems.Comparing Results: Generated comprehensive comparisons of simulation results between AVEVA and ASPEN, including thorough analyses of differences.Collaborating with Support Teams: Worked closely with AVEVA and ASPEN support teams to resolve technical queries and enhance simulation accuracy.Presenting Findings: Presented simulation results and analyses within the working group, contributing to team discussions and decision-making.Exploring Dyssol: Investigated the capabilities of the dynamic solid simulator Dyssol, creating initial models and engaging in effective communication with the Dyssol support team.- Learning and Development:This internship allowed me to:Enhance Technical Skills: Gained hands-on experience with advanced process simulation software and techniques.Apply Academic Knowledge: Applied theoretical concepts from my university courses to real-world scenarios, deepening my understanding of the subject matter.Collaborate with Experts: Worked alongside seasoned professionals in a highly professional and scientifically oriented environment.- Reflection:My time at Evonik Industries was transformative, providing me with a platform to contribute meaningfully to innovative projects within the Process Simulation and CFD group. I am grateful for the opportunity to develop my skills, work with experts, and gain insights that will be invaluable in my future endeavors. I extend my sincere appreciation to Evonik Industries for this incredible opportunity and look forward to applying the lessons and skills I gained in my future career.

During my tenure at the Institute of Energy Process Engineering at FAU in Nuremberg, Germany, I worked on optimizing catalytic methanation using machine learning algorithms. This involved:- Data Processing and Feature Mapping:Processing large datasets and mapping relevant features to identify key variables affecting bio methane production processes.- Unit Construction and Development:Constructing and developing units for catalytic methanation experiments, ensuring precision and reliability in experimental setups.- Industrial Field Test of Bench Scale Methanation Plant:Conducting industrial field tests of bench-scale methanation plants to evaluate the performance of catalytic methanation processes under real-world conditions.My responsibilities encompassed not only data analysis and experimental design but also practical implementation and field testing. Through this experience, I gained valuable insights into catalytic methanation processes, machine learning applications in process optimization, and the complexities of translating laboratory findings to industrial settings.This work contributed to advancing the understanding and optimization of catalytic methanation processes, laying the groundwork for more efficient and sustainable energy production methods. It also provided me with valuable skills in research, experimental design, and interdisciplinary collaboration, further enriching my expertise in the field of energy process engineering.

Development of the Brownian Dynamic simulation for Analytical Ultra Centrifugation (AUC).o MATLAB programming code development for Brownian Dynamic.o Simulation validation with AUC experimental data.

Providing consultancy services on environmentally friendly processes, including wastewater treatment, industrial waste removal, and waste valorization, with the following responsibilities:- Conducting research on process development for waste removal- Creating technical documentation and performing technical analysisDeveloping the biomass pyrolysis process to produce biofuel, with the following responsibilities:- Modifying processes to upgrade products- Making adjustments to pilot-scale setups- Evaluating the various feedstocks- Optimizing operating conditions to enhance both the amount and quality of products- Analyzing the elemental and chemical composition of the products

As a Process Engineer at Iran Offshore Oil Company, I played a pivotal role in the production of crude oil at the Soroosh Oil Field offshore platform. My responsibilities included:- Conducting research on Produced Water Treatment using Compact Flotation Unit (CFU)- Exploring process modifications to stabilize production- Investigating the impact of various additives on product quality- Conducting field test measurements and product evaluations- Developing conceptual designs for new process developments- Revising and enhancing process Piping and Instrumentation Diagrams (P&IDs)

During my time at the Center of Process Simulation and Design at the University of Tehran, I performed various roles, including chemical engineering process design and teaching software usage. My responsibilities and projects included:Design and Validation Projects:- Designing bench-scale bubble detection apparatuses.- Validating the wastewater treatment process design for Temad Pharmaceutical Company, including calculations and modifications for a three-stage evaporator and stripping column.Simulation and Improvement Projects:- Simulating a Butadiene production plant using Aspen Plus software.- Improving the color and consolidating low-quality Turquoise stones with epoxy resin.Industrial Proposals and Experimental Setups:- Preparing industrial proposals for designing and constructing two bench-scale fluidized beds for Oxidation Coupling of Methane (OCM).- Constructing an experimental setup for CO2 capture development in a fluidized bed reactor.Teaching Responsibilities:- Teaching "Aspen Plus Polymer," covering topics such as Aspen environments, component classification, polymer structure properties, thermodynamic properties, polymerization reactions, and simulation of polymerization reactors.- Teaching "Introduction to Aspen Plus," which included an overview of Aspen Plus, basic principles of process design, applications of thermodynamics in simulation, phase equilibrium calculations, material property predictions, reaction rate introduction, reactor simulation, and exchanger simulation.In summary, my responsibilities at the Center of Process Simulation and Design were:- Consolidating and improving the color of Turquoise stones.- Proposing the design and construction of bench-scale fluidized beds for OCM.- Simulating the Butadiene production process using Aspen Plus.- Constructing experimental setups for CO2 capture in fluidized bed reactors.- Teaching courses on Aspen Plus Polymer and Introduction to Aspen Plus.

• Esfahan Oil Refinery 2009. Project: “H2S removal from sour water and amine with absorption and desorption processes and also Sulfur production”