Aram Papoyan | Data Analysis Innovation | Best Researcher Award

Prof. Aram Papoyan | Data Analysis Innovation | Best Researcher Award

Prof. Aram Papoyan at Institute for Physical Research, NAS of Armenia, Armenia

๐Ÿ‘จโ€๐ŸŽ“ย  Profiles

๐ŸŒŸ Summary

Prof. Aram Papoyan is a distinguished expert in Laser Physics and Optics, known for his extensive research and leadership at the Institute for Physical Research in Armenia. He has played a pivotal role in international scientific collaborations.

๐ŸŽ“ Education

He earned his Master in Radiophysics from Yerevan State University in 1982, followed by a PhD in Optics from the Institute for Physical Research, NAS Armenia in 1991. In 2005, he completed his DSc in Laser Physics.

๐Ÿ’ผ Professional Experience

Prof. Papoyan has served as Director of the Institute for Physical Research since 2006 and heads the Laboratory of Optics. His previous roles include Vice-Director and Senior Researcher across various positions since 1986. He also supervises PhD students at the Russian-Armenian University.

๐Ÿ† Accolades and Recognition

He has received the Anania Shirakatsi Medal (2013) and the Galileo Galilei Award (2015) from the International Commission for Optics. Additionally, he was honored as an OSA Advocate of Optics in 2019 and holds multiple awards for contributions to physics.

๐Ÿ”ฌ Research Interests

Prof. Papoyan focuses on Laser Physics, Atomic Physics, and Quantum Optics, with interests in coherent population trapping, magneto-optical effects, and advanced optical imaging techniques, as well as laser-induced reactions and molecular spectroscopy.

 

๐Ÿ“– Top Noted Publications

Scanning technique for direct optical transmission imaging of highly-scattering objects
    • Authors: Svetlana Shmavonyan, Aleksandr Khanbekyan, Marina Movsisyan, Aram Papoyan
    • Journal: Optics and Lasers in Engineering
    • Year: 2025
Electromagnetically induced transparency with magnetically induced ฮ”F = 0, mF = 0 โ†’ mF = 0 probe transition
    • Authors: Armen Sargsyan, David Sarkisyan, Aram Papoyan
    • Journal: Laser Physics
    • Year: 2024
Mirrorless Lasing: A Theoretical Perspective
    • Authors: A. Ramaswamy, J. Chathanathil, D. Kanta, E. Klinger, A. Papoyan, S. Shmavonyan, A. Khanbekyan, A. Wickenbrock, D. Budker, S. A. Malinovskaya
    • Journal: Optical Memory and Neural Networks
    • Year: 2023
Peculiarities of Fluorescence of Rb Atomic Vapors Contained in a cell with an anti-relaxation coating
    • Authors: Aram Papoyan
    • Journal: Optics and Spectroscopy
    • Year: 2023
Wide range linear magnetometer based on a sub-microsized K vapor cell
    • Authors: M. Auzinsh, A. Sargsyan, A. Tonoyan, C. Leroy, R. Momier, D. Sarkisyan, A. Papoyan
    • Journal: Applied Optics
    • Year: 2022

Cancellation of D1 line transitions of alkali-metal atoms by magnetic-field values

    • Authors: Artur Aleksanyan, Rodolphe Momier, Emil Gazazyan, Aram Papoyan, Claude Leroy
    • Journal: Physical Review A
    • Year: 2022

Arun Chandramouli | Business Intelligence and Analytics | Global Innovations in Analytics Award

Mr. Arun Chandramouli | Business Intelligence and Analytics | Global Innovations in Analytics Award

Mr. Arun Chandramouli at Fulcrum Digital inc, United States

๐Ÿ”—ย Profile

Google Scholar Profile

๐Ÿง‘โ€๐Ÿ’ป Summary

Arun Chandramouli is a seasoned Data Scientist with nearly a decade of experience in driving data-centric strategies and innovations. Specializing in machine learning models, advanced statistical analysis, and data architecture, Arun excels in translating complex data into actionable insights. His technical proficiency is bolstered by a certificate in Machine Learning and AI and a strong track record in enhancing business performance through data-driven solutions. Adept at fostering cross-functional teams and cultivating analytics-driven cultures, Arun is dedicated to advancing data governance and strategic decision-making.

๐ŸŽ“ Education

  • Post-Graduate Program in Machine Learning & AI, University of Texas at Austin (2021)
  • Master of Science in Industrial Engineering & Operations Research, University at Buffalo (2014)
  • Bachelor of Technology (IT), SSN College of Engineering (2011)

๐Ÿ’ผ Professional Experience

With nearly a decade of experience as a Data Scientist, I have a proven track record of leveraging data-driven strategies to drive organizational success and innovation. My career spans diverse industries where I have developed and deployed sophisticated machine learning models, advanced statistical analyses, and comprehensive data architectures. Notable achievements include generating significant revenue growth through impactful dashboard development, streamlining operations with advanced data visualizations, and enhancing customer satisfaction by addressing critical data issues. My roles have consistently involved cross-functional collaboration, strategic problem-solving, and the application of cutting-edge technologies to optimize performance and inform strategic decision-making. I have worked with leading organizations such as Mastercard, Equifax, and Athenahealth, where my contributions have been instrumental in improving business processes and driving data-centric solutions.

๐Ÿ”ฌ Research Interests

My research interests lie at the intersection of advanced data analytics and machine learning, focusing on how these technologies can transform business processes and decision-making. I am particularly passionate about developing predictive models and algorithms to uncover actionable insights and drive strategic growth. My work involves exploring innovative techniques in data visualization to enhance the interpretability and impact of complex datasets. Additionally, I am dedicated to optimizing data-driven decision-making through robust analytical frameworks and cutting-edge AI applications, aiming to solve real-world problems and advance the field of data science.

๐Ÿ“– Publication

Strategies and Impact of Customer Loyalty Programs in the Technology Sector: A Comprehensive Analysis
    • Author: A Chandramouli
    • Journal: Journal of Technological Innovations
    • Year: 2020
Leveraging Predictive Analytics to Minimize Claim Denials in Healthcare Revenue Cycle Management
    • Author: A Chandramouli
    • Journal: Journal of Technological Innovations
    • Year: 2021
Implementing Volume-Based Rebates in E-commerce: A Comprehensive Case Study
    • Author: A Chandramouli
    • Journal: Journal of Technological Innovations
    • Year: 2021
An Automated Framework for Efficiently Predicting and Managing Dispatch Rates in Technology Service Sectors
    • Author: A Chandramouli
    • Journal: Journal of Technological Innovations
    • Year: 2021

Ebrahim Ghaderpour | Financial Data Analysis | Best Researcher Award

Dr. Ebrahim Ghaderpour, Financial Data Analysis, Best Researcher Award

Doctorate at Sapienza University of Rome, Italy

Professional Profile

Orcid Profile
Scopus Profile
Research Gate

Summary

Dr. Ebrahim Ghaderpour is an accomplished Assistant Professor in Remote Sensing for Engineering Geology at Sapienza University of Rome, specializing in ground deformation processes and cultural heritage monitoring using remote sensing techniques. He is also the Founder and CEO of Earth and Space Inc., focusing on Earth observation data analysis. With a robust background in academia and industry, Dr. Ghaderpour has extensive experience in teaching, research, and software development across various scientific disciplines.

Education

  • Ph.D. in Big Data Analytics, York University, Toronto, ON, Canada, 2018
  • Ph.D. in Theoretical and Computational Science, University of Lethbridge, Lethbridge, AB, Canada, 2014
  • M.Sc. in Mathematics, Isfahan University of Technology, Isfahan, Iran, 2010
  • B.Sc. in Applied Mathematics, University of Isfahan, Isfahan, Iran, 2007

Professional Experience

  • Assistant Professor, Department of Earth Sciences, Sapienza University of Rome, Italy (2022-present)
  • Founder and CEO, Earth and Space Inc., Calgary, AB, Canada (2020-present)
  • Postdoctoral Associate, Department of Geomatics Engineering, University of Calgary, Canada (2021-2022)
  • Sessional Instructor, University of Calgary and University of Lethbridge, Canada (2016-2022)
  • Research and Teaching Assistant, York University and University of Lethbridge, Canada (2013-2016)

๐Ÿ“– Publication Topย Noted

Article: A fractional-order multiple-model type-2 fuzzy control for interconnected power systems incorporating renewable energies and demand response

  • Authors: Yan, S.-R., Dai, Y., Shakibjoo, A.D., Ghaderpour, E., Mohammadzadeh, A.
  • Journal: Energy Reports
  • Volume: 12
  • Pages: 187โ€“196
  • Year: 2024

Article: On the stochastic significance of peaks in the least-squares wavelet spectrogram and an application in GNSS time series analysis

  • Authors: Ghaderpour, E., Pagiatakis, S.D., Mugnozza, G.S., Mazzanti, P.
  • Journal: Signal Processing
  • Volume: 223
  • Pages: 109581
  • Year: 2024

Article: Ground deformation monitoring via PS-InSAR time series: An industrial zone in Sacco River Valley, central Italy

  • Authors: Ghaderpour, E., Mazzanti, P., Bozzano, F., Scarascia Mugnozza, G.
  • Journal: Remote Sensing Applications: Society and Environment
  • Volume: 34
  • Pages: 101191
  • Year: 2024

Article: A fast and robust method for detecting trend turning points in InSAR displacement time series

  • Authors: Ghaderpour, E., Antonielli, B., Bozzano, F., Scarascia Mugnozza, G., Mazzanti, P.
  • Journal: Computers and Geosciences
  • Volume: 185
  • Pages: 105546
  • Year: 2024

Article: Personalized Blood Pressure Control by Machine Learning for Remote Patient Monitoring

  • Authors: Vu, M.T., Alattas, K.A., Bouteraa, Y., Ghaderpour, E., Mohammadzadeh, A.
  • Journal: IEEE Access
  • Year: 2024

Worldwide Research Analytics Distinction Award

Worldwide Research Analytics Distinction Award

Worldwide Research Analytics Distinction Award

Introduction: Step into the future of research excellence with the 'Worldwide Research Analytics Distinction Award.' This prestigious award recognizes pioneers in research analytics, pushing the boundaries of knowledge and making significant contributions to the global research landscape.

Eligibility: Open to researchers worldwide, the award has no age limits. Candidates must showcase an exceptional ability to leverage analytics in their research endeavors.

Qualification: Applicants should possess a proven track record of utilizing advanced analytics in research projects, demonstrating a minimum of 5 years of professional experience in the field.

Publications and Requirements: Candidates are expected to have a robust portfolio of publications showcasing the innovative application of analytics in their research. Original research papers, articles, or case studies are highly encouraged.

Evaluation Criteria: Judged on the innovative use of analytics, impact on research outcomes, and contribution to advancing analytical methodologies, candidates will undergo rigorous evaluation by a distinguished panel of experts.

Submission Guidelines: Submissions should include a comprehensive biography, an abstract of the candidate's research methodology, and supporting files that highlight the significance of their analytics-driven research. All documents must be submitted in a standard format.

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

Community Impact: Candidates should demonstrate a positive influence on the research community through the application of analytics, knowledge-sharing, or community-driven initiatives.

Biography: Provide a detailed biography outlining your journey, achievements, and impact on the research analytics 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 research analytics work.