Monir Ashrafi | Data Analysis Innovation | Best Researcher Award

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Ms. Monir Ashrafi, Data Analysis Innovation, Best Researcher Award

Ms. Monir Ashrafi at Sharif University of Technology, France

Professional Profile:

Scopus Profile

Professional Summary:

A dedicated Ph.D. candidate with extensive practical and technical experience in Power System Engineering, focusing on the advancement, modernization, and decarbonization of power distribution systems. Seeking collaborative opportunities with research groups to enhance professional knowledge and contribute to innovative energy solutions.

Education:

Ms. Monir Ashrafi is currently pursuing a Ph.D. in Power System Engineering at both the University of Grenoble Alpes, France, and Sharif University of Technology, Iran. At the University of Grenoble Alpes, under the supervision of Seddik Bacha and advisor Raphael Cairo, he began his studies in January 2023. Concurrently, since September 2019, he has been working towards his Ph.D. at Sharif University of Technology, Iran’s top-ranking institution, with guidance from Ali Abbaspour and advisor Mahmud Fotuhi-Firuzabad. His doctoral research focuses on “The Management of Peer-to-Peer Energy Sharing in Active Distribution Network,” demonstrating his commitment to advancing sustainable energy solutions.

Prior to his Ph.D. studies, Monir earned a Master of Science in Electrical Engineering, specializing in Power System Engineering, from Shahrood University of Technology, Iran, in June 2017. His master’s thesis, titled “Power Sharing in Microgrids using Virtual Impedance,” earned him top 10% honors with a GPA of 17.93. He also holds a Bachelor of Science in Electrical Engineering from the same university, completed in August 2014, where he investigated “The Investigation of DFIGs” for his thesis and graduated in the top 25% of his class with a GPA of 16.34. Monir’s educational journey began at Bentolhoda High School in Shahrood, Iran, where he excelled in Mathematics and Physics, graduating with a GPA of 19.24, placing him in the top 1% of his program.

Professional Experience:

Ms. Monir Ashrafi has accumulated extensive experience in various roles within the power distribution sector. As a Grid Studies Expert at the Power Distribution Company in Tehran Province, Iran (December 2020 – December 2022), Monir conducted in-depth analyses and advanced grid modeling techniques to enhance the operational efficiency and reliability of power distribution networks. This role involved close collaboration with cross-functional teams to improve grid performance and resilience. Prior to this, Monir worked as a GIS Expert at the Power Distribution Company in Semnan Province, Iran (September 2018 – August 2019), where he developed and maintained Geographic Information Systems (GIS) for power distribution networks. He ensured accurate mapping and data management, which were critical for supporting operational decisions and optimizing asset management. Additionally, Monir served as a Grid Designer at the same company (March 2018 – August 2018), where he was responsible for designing and planning distribution grid infrastructure projects. His work included performing load flow analysis and grid optimization, ensuring compliance with industry standards and regulations. Earlier in his career, Monir gained valuable practical experience during an internship at a 230KV Power Transmission Station in Semnan Province, Iran (June 2014 – August 2014). In this role, he assisted in the operation and maintenance of high-voltage power transmission systems, contributing to troubleshooting and resolving technical issues while gaining a thorough understanding of the monitoring and control processes involved in power transmission.

Research Interests:

Ms. Monir Ashrafi is deeply invested in advancing the field of power systems engineering, with particular focus on the development and optimization of smart grids. His research interests include the modeling and operation of power distribution systems, where he aims to enhance reliability and resiliency through innovative solutions. Monir is also passionate about integrating renewable energy resources into power grids to support sustainable and decarbonized energy systems. Additionally, he explores the dynamics of energy markets, aiming to facilitate efficient energy trading and management. His work seeks to address the challenges of modern power systems, promoting advancements that contribute to more robust, adaptive, and environmentally friendly power distribution networks.

Publication Top Noted:

Paper Title: Fault-resilient energy management of grid-connected energy communities in presence of distance-driven P2P and P2G energy transactions
  • Authors: Ashrafi, M.; Abbaspour, A.; Fotuhi-Firuzabad, M.; Bacha, S.; Caire, R.
  • Journal: Electric Power Systems Research
  • Volume: 233
  • Pages: 110468
  • Year: 2024
Paper Title: MILP-based Service Restoration in Prosumer-based Active Distribution Networks
  • Authors: Ashrafi, M.; Abbaspour-Tehranifard, A.; Fotuhi-Firuzabad, M.; Bacha, S.; Caire, R.
  • Conference: IEEE PES Innovative Smart Grid Technologies Conference Europe
  • Year: 2023
Paper Title: Topology-based Peer-to-Peer Energy Sharing or Trading for Active Distribution Network
  • Authors: Ashrafi, M.; Abbaspour, A.; Fotuhi-Firuzabad, M.
  • Conference: 2022 12th Smart Grid Conference, SGC 
  • Year: 2022

Global Data Innovation Recognition Award

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Global Data Innovation Recognition Award

Global Data Innovation Recognition Award

Introduction: Embark on a journey of transformative data excellence with the 'Global Data Innovation Recognition Award' This distinguished accolade honors visionaries in the realm of data innovation, celebrating those who have revolutionized the global landscape through groundbreaking data-driven solutions.

Eligibility: Open to innovators worldwide, this award transcends age limits. Candidates must showcase a remarkable ability to drive positive change through innovative data practices.

Qualification: Applicants should demonstrate a proven track record of implementing innovative data solutions, with a minimum of 5 years of professional experience in the field.

Publications and Requirements: Candidates are encouraged to present a portfolio of publications highlighting their innovative data practices. Original research papers, articles, or case studies are highly valued.

Evaluation Criteria: Judged on the innovation, impact, and contribution to the field of data, candidates will undergo a comprehensive evaluation by a panel of esteemed experts in data science and innovation.

Submission Guidelines: Submissions must include a comprehensive biography, an abstract showcasing the candidate's innovative data practices, and supporting files that exemplify the transformative impact of their work. Ensure all documents are submitted in a standard format.

Recognition: Winners will receive global recognition for their outstanding achievements, with featured spotlights in leading industry publications and international events.

Community Impact: Candidates should demonstrate a positive influence on the data science community through innovative solutions, knowledge-sharing, or community-driven initiatives.

Biography: Provide a detailed biography outlining your journey, achievements, and impact on the global data innovation landscape.

Abstract and Supporting Files: Include a compelling abstract summarizing your key innovative data contributions and attach supporting files that showcase the depth and impact of your work.

International Data Mastery Achievement Award

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International Data Mastery Achievement Award

Introduction: Welcome to the pinnacle of data excellence - the 'International Data Mastery Achievement Award.' This prestigious accolade recognizes trailblazers in the field of data science, honoring those whose groundbreaking work reshapes our understanding and utilization of data.

Eligibility: Open to data enthusiasts worldwide, this award has no age limits. Candidates must possess a proven track record of remarkable achievement in the realm of data science.

Qualification: Candidates should demonstrate exceptional proficiency in data analysis, algorithm development, and innovative data-driven solutions. A minimum of 5 years of professional experience in the field is required.

Publications and Requirements: Applicants should have a history of impactful publications showcasing their contributions to the data science community. Original research papers, articles, or case studies are highly encouraged.

Evaluation Criteria: Judged on innovation, impact, and contribution to the field, candidates will be assessed by a panel of distinguished experts in data science.

Submission Guidelines: Submissions must include a comprehensive biography, an abstract of the candidate's work, and supporting files highlighting the significance of their contributions. Ensure all documents are submitted in a standard format.

Recognition: Winners will receive global recognition for their outstanding achievements, with a featured spotlight in prominent industry publications and events.

Community Impact: Candidates should demonstrate a positive influence on the data science community through mentorship, knowledge-sharing, or community-driven initiatives.

Biography: Provide a detailed biography outlining your journey, achievements, and impact on the data science landscape.

Abstract and Supporting Files: Include a compelling abstract summarizing your key contributions and attach supporting files that showcase the depth and impact of your work.