Assoc. Prof. Dr. Catalin Dumitrescu | Machine Learning Awards | Excellence in Research

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Assoc. Prof. Dr. Catalin Dumitrescu | Machine Learning Awards | Excellence in Research

Assoc. Prof. Dr. Catalin Dumitrescu , University POLITEHNICA of Bucharest , Romania

Catalin Dumitrescu is an accomplished academic and researcher specializing in Computing and Artificial Intelligence. Currently serving as an Associate Professor and R&D Scientific Adviser at the National University of Science and Technology POLITEHNICA of Bucharest (UNSTPB), Romania, he holds a Ph.D. in Digital Signal Processing and Machine Learning from University Politehnica of Bucharest. Catalin’s extensive career spans over 20 years in research and development within the Machine Learning Defense Industry and Cyber Defence sectors. He has held pivotal roles in R&D, Artificial Intelligence, Machine Learning Software System Architecture, and Product Management. His expertise includes Mathematical Algorithms, Software Architecture, Digital Signal Processing, and applications in defense technologies. Catalin is also a certified expert in Critical Infrastructure Risk Management and Competitive Intelligence. His research interests encompass Artificial Intelligence, Machine Learning, Deep Learning, and their applications in areas like natural language processing, image processing, and neural networks. Catalin has contributed significantly to academic literature and continues to lead research initiatives at the forefront of technological innovation in his field.

Professional Profile:

Orcid

šŸŽ“Education:

Catalin Dumitrescu holds a diverse educational background reflecting his expertise in both technical and business domains. He earned his Ph.D. in Digital Signal Processing and Machine Learning from the University Politehnica of Bucharest, Romania, where his research focused on advanced algorithms and applications in signal and image processing. Complementing his technical qualifications, Catalin pursued a postgraduate degree in International Business and Economics at Bucharest University of Economic Studies. Additionally, he holds an engineering degree from the Transportation Engineering Faculty at University Politehnica of Bucharest, specializing in Signal Processing and Image Processing. This multidisciplinary educational foundation has equipped Catalin with a comprehensive skill set bridging technology innovation with strategic business acumen.

šŸ¢Work Experience:

Catalin Dumitrescu brings a wealth of experience across academia, industry, and defense sectors, showcasing a distinguished career path. Currently serving as an Associate Professor and R&D Scientific Adviser at the National University of Science and Technology POLITEHNICA of Bucharest (UNSTPB) in Romania since 2015, he plays a pivotal role in advancing research in Electronics & Telecommunication within the Transportation Engineering Faculty. Catalin’s industry experience includes serving as the Chief Technology Officer (CTO) at SoftGalaxy International from 2017 to 2021, where he led research and development initiatives in Artificial Intelligence. Prior to this role, he contributed significantly as a Software Systems Architect at UTI GROUP’s R&D department SYS-STD-SMART Technologies & Development from 2015 to 2017. His extensive tenure in defense research spans two decades, from 1995 to 2015, as an R&D Military Officer at the Defense Advanced Technology Institute, focusing on developing Machine Learning systems for Intelligence, Surveillance, Reconnaissance (IMINT), and Signals Intelligence (SIGINT). Catalin began his career as an Electronics Engineer at the Transport Research Institute from 1986 to 1995, laying the foundation for his subsequent achievements in technology and defense innovation

šŸ†Awards:

Catalin Dumitrescu holds certifications as a Certified Expert in Critical Infrastructure Risk Management and Competitive Intelligence, underscoring his specialized expertise in strategic risk assessment and competitive analysis. These certifications complement his extensive background in academia and research, enhancing his capabilities in navigating complex technological landscapes and contributing to advancements in defense and cyber security sectors.

Publication Top Notes:

  1. Artificial Intelligence Application in the Field of Functional Verification
    • Journal: Electronics
  2. Modeling and Prediction of Sustainable Urban Mobility Using Game Theory Multiagent and the Golden Template Algorithm
    • Journal: Electronics
  3. Contributions to Power Grid System Analysis Based on Clustering Techniques
    • Journal: Sensors
  4. Urban Traffic Noise Analysis Using UAV-Based Array of Microphones
    • Journal: Sensors
  5. On the Feasibility and Efficiency of Self-Powered Green Intelligent Highways
    • Journal: Energies

 

 

Ms. Nathalia Hidalgo Leite | Artificial Neural Networks | Best Researcher Award

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Ms. Nathalia Hidalgo Leite | Artificial Neural Networks | Best Researcher Award

Ms. Nathalia Hidalgo Leite, State University of Campinas, Brazil

šŸŽ“ Nathalia Hidalgo Leite is a Ph.D. candidate in Energy Systems Planning at the State University of Campinas (Unicamp) šŸ‡§šŸ‡·, focusing on electric mobility. She also holds an MBA in Value Investing from UniBTA and an M.S. in Energy Systems Planning from Unicamp, and a B.S. in Agronomic Engineering from UFSCar šŸŒ±. As a researcher at CPTEn and CPFL Energy, and an instructor at Unicamp, she has contributed significantly to energy systems planning and education. Her international academic experience includes programs in Portugal šŸ‡µšŸ‡¹, Denmark šŸ‡©šŸ‡°, Spain šŸ‡ŖšŸ‡ø, Italy šŸ‡®šŸ‡¹, and the USA šŸ‡ŗšŸ‡ø. Nathalia’s research interests span the economic and financial viability of energy systems, artificial neural networks, and renewable energy integration šŸŒž. Proficient in Portuguese, English, and Spanish, she holds numerous certifications in finance and technical skills šŸ“Š. Her achievements are recognized by multiple academic and extracurricular awards, underscoring her dedication and multifaceted talents šŸŒŸ.

šŸŒ Professional Profile:

Google Scholar

šŸŽ“ Educational Background

Nathalia Hidalgo Leite is currently pursuing a Ph.D. in Energy Systems Planning at the State University of Campinas (Unicamp) šŸ‡§šŸ‡·, focusing on the economic and financial viability for electric mobility. She also holds an MBA in Value Investing from UniBTA and an M.S. in Energy Systems Planning from Unicamp, where she studied the economic viability of photovoltaic solar energy. Nathalia completed her B.S. in Agronomic Engineering at the Federal University of Sao Carlos (UFSCar), researching artificial neural networks applied to Asian soybean rust šŸŒ±.

šŸ¢ Professional Experience

Nathalia is an accomplished researcher and instructor. At Unicamp, she has taught courses in computer algorithms, programming, numerical calculation, and discrete mathematics. As a researcher at the Sao Paulo Center for Energy Transition Studies (CPTEn) and previously at CPFL Energy, she has made significant contributions to energy systems planning. Nathalia also worked as a Financial Planning and Analysis Specialist at Grupo JLJ and interned at Ecomark IndĆŗstria e ComĆ©rcio de Fertilizantes Especiais Ltda šŸŒŸ.

šŸŒ International Experience

Nathalia has enriched her academic journey with several exchange programs. She spent six months at the University of Lisbon šŸ‡µšŸ‡¹ and the University of Southern Denmark šŸ‡©šŸ‡°, three months at Universitat PolitĆØcnica de ValĆØncia šŸ‡ŖšŸ‡ø, one month at UniversitĆ  degli Studi di Roma La Sapienza šŸ‡®šŸ‡¹, and also attended Beverly Hills High School šŸ‡ŗšŸ‡ø and Moore Elementary School in Colorado šŸ‡ŗšŸ‡ø during her earlier education šŸ“š.

šŸ“ Research Interests

Nathalia’s research interests include the economic and financial viability of energy systems, artificial neural networks, and the integration of renewable energy sources. She is particularly focused on interdisciplinary approaches to solving complex problems in energy planning and sustainability šŸŒž.

šŸŒ Certifications and Skills

Nathalia holds numerous certifications in finance, photovoltaic systems, scientific writing, and programming. She is proficient in Portuguese (native), English (fluent), and Spanish (advanced). Her technical skills and continuous learning make her a versatile and knowledgeable professional in her field šŸ“Š.

šŸ† Awards and Recognitions

Nathalia has received several awards for academic and extracurricular excellence, including the Excellence in Academic Performance award from Anglo Middle School šŸ‡§šŸ‡· and multiple accolades from Lincoln Junior High School šŸ‡ŗšŸ‡ø for academic achievement, athletic performance, and leadership. These recognitions highlight her dedication and multifaceted talents šŸŒŸ.

Publication Top Notes:

1. Ā Artificial Neural Networks Applied to Plant Disease
2. Ā Study of Asian Soybean Rust

 

 

Prof. Subir Das | Neural Networks | Best Researcher Award

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Prof. Subir Das | Neural Networks | Best Researcher Award

Prof.Subir Das, Indian Institute of Technology (BHU) Varanasi, India

Prof. Subir Das is a distinguished Professor in the Department of Mathematical Sciences at the Indian Institute of Technology (BHU), Varanasi, India. Additionally, he holds the position of Visiting Professor at UCSI University in Kuala Lumpur, Malaysia. With a solid educational background, Subir earned his M.Sc. in Applied Mathematics and subsequently completed his Ph.D. in Science, being honored with the Griffith Memorial Award in Science from the University of Calcutta in 2001. Renowned for his expertise, Subir’s research interests span diverse areas such as Fracture Mechanics, Fractional Calculus, Mathematical Modeling, and Nonlinear Dynamics. His significant contributions to these fields have earned him recognition, including being listed among the world’s top 2% scientists in a global database curated by Stanford University, California, USA. With a passion for advancing mathematical sciences, Subir Das continues to leave an indelible mark in his academic journey.

šŸŒĀ Professional Profile:

Scopus

Orcid

Google Scholar

šŸŽ“ Education:

  • M. Sc. (Applied Mathematics)
  • Ph. D. (Science)
  • Recipient of the Griffith Memorial Award in Science from the University of Calcutta in 2001.

šŸ” Research Interests:

  • Fracture Mechanics
  • Fractional Calculus
  • Mathematical Modelling
  • Nonlinear Dynamics

šŸŒ Recognition:

  • Listed among the WORLD’S TOP 2% SCIENTISTS in a world database created by Stanford University, California, USA.

šŸ† Awards:

He was honored with the Griffith Memorial Award in Science by the University of Calcutta in 2001, recognizing his outstanding contributions to the field.

šŸ”¬ Research Focus:

Prof. Das has made significant contributions to various areas, including Fracture Mechanics, Fractional Calculus, Mathematical Modelling, and Nonlinear Dynamics. His research reflects a deep understanding of these subjects and contributes to advancements in the mathematical sciences

šŸ“šĀ Publication Impact and Citations :

Scopus Metrics:

  • šŸ“Ā Publications: 186 documents indexed in Scopus.
  • šŸ“ŠĀ Citations: A total of 3,164 citations for his publications, reflecting the widespread impact and recognition of Prof. Subir Dasā€™s research within the academic community.

Google Scholar Metrics:

  • All Time:
    • Citations: 4167 šŸ“–
    • h-index: 33 šŸ“Š
    • i10-index: 104 šŸ”
  • Since 2018:
    • Citations: 2327 šŸ“–
    • h-index: 24 šŸ“Š
    • i10-index: 74 šŸ”

šŸ‘Øā€šŸ« A prolific researcher with significant impact and contributions in the field, as evidenced by citation metrics. šŸŒšŸ”¬

PublicationĀ  Ā TopĀ  Notes:

 

 

 

 

Mr. Adrian Ly | Reinforcement learning | Best Researcher Award

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Mr. Adrian Ly | Reinforcement learning | Best Researcher Award

Mr. Adrian Ly, Deakin University, Australia

šŸŒ Mr. Adrian Ly, a distinguished alumnus of Deakin University in Australia, stands as a beacon of the transformative power of education. His academic journey at Deakin not only equipped him with knowledge and skills but also ignited a passion for lifelong learning. As a Principal Data Scientist at National Australia Bank, Adrian spearheads innovation, combating scams and enhancing customer experiences globally. Leading a dynamic team, he achieved a remarkable 32% revenue boost in unsecured lending and transaction portfolios through cutting-edge machine learning models. His tenure as a Data Science Manager at Commonwealth Bank showcased his prowess in developing impactful credit risk models and managing large-scale projects. As a Consultant at NAB, Adrian applied unsupervised learning to create personalized communication strategies, contributing significantly to revenue growth. With a background in Marketing and Sales Operations, Adrian’s diverse expertise has left an indelible mark in the realms of data science and artificial intelligence. šŸš€šŸ’»

šŸŽ“Ā Education :

Adrian Ly, a proud alumnus of Deakin University in Australia šŸŽ“, is a shining example of the transformative power of education. Armed with knowledge and skills acquired during his time at Deakin, Adrian has become a trailblazer in his field. šŸš€ His educational journey has not only shaped his professional success but has also instilled in him a passion for lifelong learning. šŸ“š Adrian’s connection to Deakin is not just academic; it’s a symbol of growth, resilience, and the pursuit of excellence. šŸŒŸ As he continues to make waves in his career, Adrian carries the spirit of his alma mater with him, a testament to the impact of quality education on shaping individuals into leaders of tomorrow. šŸŒ

šŸŒ Professional Profiles :

Google Scholar

šŸŒ Principal Data Scientist at National Australia Bank (May 2022 – Present) šŸ“Š

  • Spearheaded innovative functions in NAB’s web and mobile apps to combat scams, enhance customer experience, and drive retail bank growth.
  • Led a global team of 6 data scientists and engineers, fostering cross-functional collaboration across different time zones.
  • Developed machine learning models resulting in a 32% revenue boost in unsecured lending and transaction portfolios.
  • Deployed cutting-edge neural networks, improving incremental revenue across 15 models by 9%.

šŸ“ˆ Data Science Manager at Commonwealth Bank of Australia (June 2021 – May 2022) šŸ¦

  • Produced impactful credit risk models for unsecured lending, automating quality assurance and visualization processes.
  • Led development and delivery of default models using novel algorithms.
  • Managed large-scale model development and deployment projects on greenfield systems.
  • Mentored and trained junior analysts in model development and monitoring.

šŸ“Š Consultant, Data Scientist at National Australia Bank (April 2019 – June 2021) šŸ’»

  • Applied unsupervised learning to create personalized communication strategies.
  • Delivered business lending acquisition models, driving substantial incremental revenue growth.
  • Implemented real-time and batch decisioning solutions for marketing models.
  • Rebuilt home lending machine learning models in the cloud using Pyspark and EMR.

šŸ“Š Marketing Analyst at Liberty Financial (April 2018 – March 2019) šŸ“ˆ

  • Developed predictive models to improve lead pipeline conversion.
  • Identified opportunities for new data streams.
  • Collaborated with stakeholders to understand problems and recommend analytical models.
  • Analyzed data to identify process bottlenecks and suggest improvements.

šŸ” Graduate Marketing Analyst at Aesop (Nov 2015 – Jan 2017) šŸŒ

  • Conducted research to outline global strategic implications of discontinuing products.
  • Provided insights into the impact of product launches and marketing campaigns on sales.
  • Assisted in developing business cases for entry into new markets.
  • Established global marketing success metrics and facilitated the implementation of a marketing dashboard.

šŸš— Graduate Sales Operations Analyst at Honda Australia (Jan 2015 – June 2015) šŸ“ˆ

  • Increased productivity by 150% through automation of data entry, weekly reports, and monthly reviews in sales operations and product teams.

šŸ§  Research Interests šŸ”¬šŸŒ :

šŸŒ Adrian Ly, a trailblazer in the realm of artificial intelligence, is fueled by a profound passion for cutting-edge technologies. His research interests encompass the dynamic trio of reinforcement learning, machine learning, and deep learning, symbolizing a commitment to unraveling the intricacies of intelligent systems. With a mind attuned to innovation, Adrian’s journey reflects a fusion of curiosity, expertise, and a relentless pursuit of excellence in the ever-evolving landscape of AI.

Publications Top NotesĀ  :

1.Ā  Elastic Step DQN: A novel multi-step algorithm to alleviate overestimation in Deep Q-Networks (2023)

Published in Neurocomputing, Cited by 1

2.Ā  Elastic Step DDPG: Multi-step reinforcement learning for improved sample efficiency (2023)

Published in 2023 International Joint Conference on Neural Networks (IJCNN), Cited by 1

 

 

 

 

 

FarshadĀ Bolouri | Artificial Intelligence | Best Researcher Award

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MrĀ FarshadĀ Bolouri:Ā Artificial Intelligence |Ā Best Researcher Award

Research Associate atĀ Texas Tech University,Ā United States

Farshad Bolouri is an accomplished researcher with a Master’s degree in Electrical Engineering from Texas Tech University, specializing in Computer Vision, Machine Learning, Robotic Perception, and Remote Sensing. His research interests focus on Agricultural Robotics, Precision Farming, and Machine Learning in Digital Agriculture.

šŸŒ Professional Profiles:

šŸŽ“ Education :Ā 

Farshad Bolouri, a mastermind in Electrical Engineering, graduated with a Master of Science from Texas Tech University in August ’23 šŸŽ“. His stellar GPA of 3.86 reflects his dedication to his studies, with a focus on cutting-edge fields like Computer Vision, Machine Learning, Robotic Perception, and Remote Sensing šŸŒšŸ¤–.

Prior to his master’s journey, Farshad excelled in his Bachelor’s in Computer Engineering, graduating Summa Cum Laude with a perfect GPA of 4.0 in May ’21 šŸ†. He added a touch of diversity with a minor in Mathematics and Computer Science, earning accolades such as the Highest Ranking Graduate from the College of Engineering and the ‘Outstanding Design Project’ award from ECE šŸ…šŸ”§.

Farshad’s academic journey is not just about grades; it’s a testament to his passion for pushing boundaries and achieving excellence in the realm of technology and engineering šŸš€.

šŸ” Research Interests :Ā 

Farshad Bolouri’s research interests are a captivating blend of technology and agriculture šŸŒ¾. In the realm of Agricultural Robotics and Precision Farming, he’s delving into the development of custom robotic solutions. His focus lies on intelligent multi-sensor integration, aiming to optimize in-field plant phenotyping specifically for specialty crops šŸ¤–šŸŒ±. Venturing into the realm of Machine Learning in Digital Agriculture, Farshad applies cutting-edge AI/ML techniques for data interpretation. His goal is to enable accurate high-throughput phenotyping and precise yield estimation, revolutionizing the way we approach modern farming practices šŸ“ŠšŸŒ¾. In the domain of 3D Computer Vision for Field Mapping, Farshad employs advanced techniques for accurate and real-time field mapping. By integrating 3D computer vision, he aims to enhance the precision and efficiency of agricultural decision-making processes šŸŒšŸšœ.

Research Focus:

Farshad Bolouri’s research focus spans across Agricultural Robotics and Precision Farming šŸŒ¾, as evident in his groundbreaking work on “CottonSense.” This High-Throughput Field Phenotyping System leverages intelligent multi-sensor integration for optimized cotton fruit segmentation and enumeration on edge devices, revolutionizing cotton farming practices šŸ¤–šŸŒ±. Additionally, his contribution to improving short-term multiphase production forecasts in unconventional tight oil reservoirs showcases a keen interest in merging technology with geoenergy science and engineering ā›½šŸ”. Farshad’s commitment to advancing phenotyping for flower abortion in soybeans through image analysis and machine learning demonstrates a versatile expertise in the intersection of agriculture, computer vision, and AI šŸŒŗšŸ”¬.

Publications Top NotesĀ  :
  • CottonSense: A high-throughput field phenotyping system for cotton fruit segmentation and enumeration on edge devices