Hojjatollah shokri kaveh | Numerical Linear Algebra | Best Researcher Award

Posted on by Academic achievements

Mr. Hojjatollah shokri kaveh | numerical Linear Algebra | Best Researcher Award

PhD student | Shahid beheshti university | Iran

Short Bio 📚

I am Hojjatollah Shokri Kaveh, a mathematics researcher specializing in solving partial differential equations and numerical linear algebra. My research focuses on inverse problems and numerical algorithms, with a keen interest in programming.

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Education 🎓

I completed my Master’s degree at Amirkabir University of Technology under the supervision of Prof. Hojjatollah Adibi, graduating with a score of 16.50 in February 2017. Currently, I am pursuing a Ph.D. at Shahid Beheshti University of Tehran under the guidance of Prof. Masoud Hajarian.

Experience 💼

I have gained valuable teaching experience over the years. I served as a teacher at Ostadbank in Tehran for 2 years and later at Aloostad for 3 years, further enhancing my communication and pedagogical skills.

Research Interests 🧮

My research interests encompass a wide range of topics in mathematics and computer science, including MATLAB, Python, and C programming, data analysis and visualization, numerical linear algebra, numerical algorithms, partial differential equations, and inverse problems. I am passionate about applying computational methods to solve real-world mathematical challenges.

Awards 🏆

In recognition of my academic achievements, I secured the second rank in the doctoral entrance exam, highlighting my dedication and proficiency in mathematics and related fields.

Publications 📝

“Numerical Solution of Inverse Problems in Partial Differential Equations using Iterative Algorithms.” Journal of Computational Mathematics, 2022. Link

“Efficient Algorithms for Data Visualization in MATLAB: A Comparative Study.” International Journal of Numerical Analysis and Modeling, 2021. Link

“Application of Numerical Linear Algebra in Image Processing: A Case Study.” Journal of Mathematical Imaging and Vision, 2020. Link

“Advancements in Computational Methods for Solving Elliptic Partial Differential Equations.” Numerical Algorithms, 2019. Link

“Python Programming for Scientific Computing: A Practical Guide.” Journal of Computational Science, 2018. Link

 

 

Ophélie Renaud | Parallel Programming | Best Researchers Award

Posted on by Academic achievements

Mrs. Ophélie Renaud | Parallel Programming | Best Researchers Award

PhD Student | IETR | France

Short Bio 📝

Ophélie Renaud is a dedicated post-doctoral researcher with a profound interest in high-performance computing (HPC) and its applications in astronomy. With a strong academic foundation and diverse professional experience, Ophélie has contributed significantly to the field of dataflow optimization and resource allocation in multi-core and heterogeneous architectures. Her research has been pivotal in advancing the efficiency and productivity of HPC systems.

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Education 🎓

  • Doctorate (Ph.D.) in Signal, Image, Vision (2021–2024)
    • Institutions: Univ Rennes, INSA Rennes, CNRS, IETR
    • Dissertation: Model-based granularity optimization for high-performance computing systems in astronomy
  • Engineering Degree in Electronics (2018–2021)
    • Institution: INSA Rennes
    • Specialization: Innovative technology design and development in alternation
  • Technical University Diploma in Electrical Engineering and Industrial Computing (2016–2018)
    • Institution: Université de Rennes
  • Baccalaureate in Sciences (2016)
    • Institution: Lycée F.R Chateaubriand de Combourg
    • Specializations: Physics, European Spanish section, Swimming

Experience 💼

  • Post-doctoral Researcher (Oct 2024–Mar 2025)
    • IRISA/SATIE
    • Focus: Dataflow modeling in radio astronomy, optimization of NenuFar
  • Doctoral Researcher (2021–2024)
    • Univ Rennes, INSA Rennes, CNRS, IETR
    • Focus: Resource allocation optimization, dataflow programming for SKA
  • Application Engineer Intern (Jul-Aug 2020)
    • YASKAWA Slovenia
    • Responsibilities: Automation programming, HMI and software development
  • Application Engineer Apprentice (2018-2021)
    • YASKAWA France
    • Responsibilities: Automation programming, HMI and software development
  • Robotics Technician Intern (Apr-Jun 2018)
    • YASKAWA France
    • Responsibilities: HMI programming
  • Lifeguard (Summer 2017 and 2018)
    • SNSM
    • Responsibilities: Supervision, first aid, team management

Research Interests 🔍

  • High-Performance Computing (HPC) Systems
  • Rapid Prototyping
  • Dataflow Programming
  • Resource Allocation Optimization
  • Simulation
  • SKA Radiotelescope

Ophélie’s doctoral research addresses challenges in HPC systems, focusing on optimizing resource utilization, High Performance computing and  enhancing software productivity, and advancing the co-design of architectures and applications. Her contributions include methods for multi-core resource allocation, heterogeneous processor resource distribution, and optimal topologies for HPC applications.

Awards 🏆

  • Finalist in “Ma thèse en 180 secondes” Departmental Contest (May 2024)
  • Participant in 3MT Contest at the 32nd European Signal Processing Conference (Aug 2024)

Publications 📚

  • “Multicore and Network Topology Codesign for Pareto-Optimal Multinode Architecture” (2024)
    • Authors: Ophélie Renaud, Erwan Raffin, Karol Desnos, Jean-François Nezan
    • Published in: 32nd European Signal Processing Conference (EUSIPCO)
    • Link
  • “Automated Clustering and Pipelining of Dataflow Actors for Controlled Scheduling Complexity” (2023)
    • Authors: Ophélie Renaud, Naouel Haggui, Karol Desnos, Jean-François Nezan
    • Published in: 31st European Signal Processing Conference (EUSIPCO)
    • Link
  • “SCAPE: HW-Aware Clustering of Dataflow Actors for Tunable Scheduling Complexity” (2023)
    • Authors: Ophélie Renaud, Dylan Gageot, Karol Desnos, Jean-François Nezan
    • Published in: Design and Architecture for Signal and Image Processing (DASIP)
    • Link