Masoud DANESHTALAB | deep learning | Best Researcher Award

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Prof. Masoud DANESHTALAB | deep learning | Best Researcher Award 

Prof. Masoud DANESHTALAB, Mälardalen University, Sweden.

Masoud Daneshtalab, Ph.D., Docent, Full Professor
Masoud Daneshtalab is a globally recognized scholar and Full Professor at Mälardalen University (MDU), Sweden. With over two decades of academic and professional excellence, he has made significant contributions to computer science and engineering, specializing in dependable systems, AI, and hardware/software co-design. A prolific researcher with an H-index of 35 and over 5,100 citations, Dr. Daneshtalab is included in the prestigious World’s Top 2% Scientists Ranking. He serves as the Scientific Director of Fundamental AI at MDU and collaborates internationally, holding adjunct professorships and contributing to cutting-edge research initiatives.

Professional Profile:

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Suitability of Masoud Daneshtalab for the Best Researcher Award

Dr. Masoud Daneshtalab is a highly suitable candidate for the “Research for Best Researcher Award,” based on his exceptional academic achievements and professional contributions. Here are the key reasons

Education

🎓 Academic Journey

  • Docent (2018): Qualified in Computer Science and Electronics, Mälardalen University, Sweden.
  • Ph.D. (2008–2011): Information and Communication Technology, University of Turku, Finland. Dissertation: Adaptive Implementation of On-Chip Networks under Prof. Hannu Tenhunen.
  • M.Sc. (2004–2006): Computer Engineering, University of Tehran, Iran. Thesis: Low Power Methods in Network-on-Chips under Prof. Ali Afzali-Kusha.
  • B.Sc. (1998–2002): Computer Engineering, Shahid Bahonar University of Kerman, Iran.

Experience

💼 Professional Contributions

  • Scientific Director (2024–Present): Fundamental AI, Mälardalen University, Sweden.
  • Full Professor (2020–Present): Innovation, Design & Engineering, MDU.
  • Adjunct Professor (2019–Present): Computer Systems, Tallinn University of Technology, Estonia.
  • Previous Roles: Associate Professor at MDU (2016–2020), EU Marie Curie Fellow at KTH Royal Institute of Technology (2014–2016), Lecturer at the University of Turku (2011–2014), and Researcher at the University of Tehran (2006–2008).

Research Interests

🔬 Key Areas

  • Optimization and robustness in deep learning models.
  • HW/SW co-design and heterogeneous computing.
  • Dependable systems, memory architectures, and interconnection networks.
  • Cutting-edge projects include sustainable AI, federated learning, and reliable autonomous systems.

Awards

🏆 Recognitions

  • Best Paper Awards: IEEE ECBS (2019), IEEE MCSoC (2018), and multiple HiPEAC Paper Awards (2013–2017).
  • Research Grants: Marie Skłodowska-Curie Fellowship (2014), Nokia Foundation (2009), and others.
  • Top Reviewer: IEEE Transactions on Computers (2013).
  • Fellowships: GETA, Helsinki University of Technology (2008–2011).

Publications

A review on deep learning methods for ECG arrhythmia classification

CITIED: 490

Time-Sensitive Networking in automotive embedded systems: State of the art and research opportunities

CITIED: 147

Routing algorithms in networks-on-chip

CITIED: 136

Smart hill climbing for agile dynamic mapping in many-core systems

CITIED: 125

EDXY–A low cost congestion-aware routing algorithm for network-on-chips

CITIED: 124

Deep Maker: A multi-objective optimization framework for deep neural networks in embedded systems

CITIED: 122

 

Prof. Fabio Caldarola | Neural Network Awards | Best Paper Award

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Prof. Fabio Caldarola | Neural Network Awards | Best Paper Award 

Prof. Fabio Caldarola, Università della Calabria, Italy

Dr. Fabio Caldarola is an accomplished mathematician and researcher, currently serving as an Assistant Professor in the Department of Environmental Engineering (DIAm) at the University of Calabria, Italy, a position he has held since January 2022. He earned his Ph.D. in Mathematics and Computer Science from the University of Calabria in December 2013, specializing in Algebraic Number Theory with a focus on Iwasawa Theory. Dr. Caldarola also holds a Laurea in Mathematics, graduating cum laude in 2003 with a thesis in Algebraic Geometry. His academic career includes several postdoctoral research fellowships, contributing to projects such as “Smart Secure & Inclusive Communities” and “I-BEST,” where he applied advanced mathematical concepts to environmental and land engineering challenges. His research interests extend to the study of complex networks, including symmetries and symmetry groups in graphs and quivers. With a strong background in pure and applied mathematics, Dr. Caldarola combines theoretical expertise with practical applications in environmental and computational sciences.

Professional Profile:

ORCID

Summary of Suitability for the Best Paper Award: Fabio Caldarola

Research Contributions
Fabio Caldarola is a distinguished researcher in mathematics and computer science, with a strong focus on innovative applications that address contemporary challenges. His significant contributions are showcased through his research publications, especially in the areas of neural fairness, blockchain protocols, and mathematical theories. Notable works include.

Education 🎓

  • Ph.D. in Mathematics and Computer Science (December 2013)
    • Università della Calabria
    • Thesis: Capitulation and Stabilization in various aspects of Iwasawa Theory for Zp-extensions (Algebraic Number Theory)
    • Advisor: Dott. A. Bandini
  • Laurea in Mathematics (May 2003)
    • Università della Calabria
    • 110/110 cum laude
    • Thesis: Rivestimenti Abeliani di Varietà Algebriche (Algebraic Geometry)
    • Advisor: Prof. P. A. Oliverio
  • Maturità Scientifica (July 1998)
    • Liceo Scientifico G.B. Scorza, Cosenza
    • Score: 60/60

Work Experience 💼

  • Assistant Professor (SSD MAT/07)
    • Department of Environmental Engineering, Università della Calabria
    • January 2022 – December 2024
  • Postdoctoral Research Fellowships 📚
    • Smart Secure & Inclusive Communities Project (SSD MAT/02 – INF/01)
      • Department of Mathematics and Computer Science, Università della Calabria
      • August 2020 – October 2021 (15 months)
    • I-BEST Project (SSD MAT/02 – ICAR/02)
      • Department of Environmental and Land Engineering and Chemical Engineering
      • June 2019 – May 2020
    • I-BEST Project (SSD MAT/03 – ICAR/02)
      • Department of Civil Engineering, Università della Calabria
      • May 2018 – April 2019
  • Research Collaboration Contract 🔬
    • Study of complex networks, focusing on symmetries and symmetry groups in graphs and quivers emerging from real contexts
    • Department of Physics, Università della Calabria
    • March 2016 – June 2016 (4 months)

Achievements & Awards 🏆

  • Academic Excellence: Laurea in Mathematics with highest honors (110/110 cum laude) 🎖️
  • Research Impact: Contributed to advanced research in Algebraic Number Theory, Algebraic Geometry, and complex network analysis.
  • Ph.D. Scholarship: Funded by Università della Calabria for excellence in doctoral research

Publication Top Notes:

Neural Fairness Blockchain Protocol Using an Elliptic Curves Lottery

Algebraic Tools and New Local Indices for Water Networks:Some Numerical Examples

Combinatorics on n-sets: Arithmetic Properties and Numerical Results

New Approaches to Basic Calculus: An Experimentation via Numerical Computation

Numerical Experimentations for a New Set of Local Indices of a Water Network

Dr. Tesfay Gidey | Machine Learning Awards | Best Researcher Award

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Dr. Tesfay Gidey | Machine Learning Awards | Best Researcher Award 

Dr. Tesfay Gidey, Addis Ababa Science and Technology University, Ethiopia

Tesfay Gidey Hailu is a distinguished Information and Communication Engineer and data scientist with a strong foundation in computer science, software engineering, data analytics, and machine learning. Holding a Ph.D. in Information and Communication Engineering from the University of Electronic Science and Technology of China, Tesfay specializes in advanced signal processing, indoor localization, information fusion, and health datasets. His expertise spans multiple programming languages, including Python, C++, SQL, and Java, as well as advanced statistical tools like SAS and R, which he uses to derive data-driven insights and support strategic decision-making in technology projects. Tesfay’s career includes notable leadership roles, such as Associate Dean for Research and Technology Transfer at Addis Ababa Science and Technology University (AASTU) and Head of Department at Jimma University. His work in academia has focused on curriculum development, student recruitment and retention, and faculty management, showcasing his commitment to fostering educational excellence. Additionally, Tesfay holds an M.Sc. in Software Engineering and an M.Sc. in Health Informatics and Biostatistics, underscoring his multidisciplinary expertise. With a deep commitment to problem-solving and continuous learning, Tesfay is adept at leveraging data and technology to drive impactful results across both academic and industry settings.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award for Tesfay Gidey Hailu

Overview: Tesfay Gidey Hailu is an accomplished Information and Communication Engineer, specializing in computer science, data science, and software engineering with extensive experience in machine learning, data structure, algorithm analysis, and business analytics. He holds a Ph.D. in Information and Communication Engineering, has published several journal articles, and serves as a journal reviewer for prestigious journals. His broad expertise and impactful contributions make him a strong candidate for the Best Researcher Award.

🎓 Education:

  • Ph.D. in Information and Communication Engineering (2023)
    University of Electronic Science and Technology of China
    Specialized in digital signal processing and information systems, with research in indoor positioning using machine learning algorithms.
  • MSc in Software Engineering (2018)
    HILCOE School of Computer Science and Information Technology
    Completed advanced courses in requirement engineering, project management, and software security.
  • MSc in Health Informatics and Biostatistics (2013)
    College of Health Sciences, Mekelle University
    Focused on health informatics, biostatistics, epidemiology, and public health project management.

Work Experience

  1. Associate Dean for Research and Technology Transfer
    • Institution: AASTU, Addis Ababa, College of Natural and Social Sciences
    • Duration: 2017-2019
    • Responsibilities: Initiated quality improvement initiatives for manufacturing industries, faculty recruitment, supervised admissions, student recruitment, and conducted industry-related research.
  2. Associate Dean, Interdisciplinary Programs Directorate
    • Institution: AASTU, Addis Ababa
    • Duration: 2015-2016
    • Responsibilities: Managed student services and retention, supervised curriculum quality initiatives, admissions, and presented research findings.
  3. Head of Department
    • Institution: Jimma University, Jimma
    • Duration: 2008-2009
    • Responsibilities: Led department meetings, evaluated performance, streamlined operations to enhance student satisfaction.
  4. Coordinator, Community-Based Training Program (CBTP)
    • Institution: Jimma University, Faculty of Natural and Information Sciences Extension Division
    • Duration: 2007-2008
    • Responsibilities: Oversaw the CBTP initiative, focusing on community-based training programs.

Publication top Notes:

Theories and Methods for Indoor Positioning Systems: A Comparative Analysis, Challenges, and Prospective Measures

Ada-LT IP: Functional Discriminant Analysis of Feature Extraction for Adaptive Long-Term Wi-Fi Indoor Localization in Evolving Environments

MultiDMet: Designing a Hybrid Multidimensional Metrics Framework to Predictive Modeling for Performance Evaluation and Feature Selection

Mr. Lianfa Li | Artificial Intelligence Award | Top Researcher Award

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Mr. Lianfa Li | Artificial Intelligence Award | Top Researcher Award 

Mr. Lianfa Li, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, China 

Dr. Lianfa Li is a distinguished Senior Research Associate and Lead Data Scientist at the University of Southern California’s Department of Population and Public Health Sciences. Since August 2017, he has been at the forefront of innovations in data science and machine learning, with a particular focus on remote sensing and air pollution modeling to study exposure and health effects. Dr. Li’s academic journey began with a Bachelor of Science in Resources, Planning, and Management from Nanjing University in 1998, followed by a Ph.D. in Geographical Information Science from the Institute of Geographical Sciences and Natural Resources Research at the Chinese Academy of Sciences in 2005. His career includes significant roles such as Associate Professor at the Chinese Academy of Sciences, Postdoctoral Scholar and Associate Specialist at the University of California, Irvine, and Research Associate at USC’s Department of Preventive Medicine.

Professional Profile:

 

ORCID

 

Summary of Suitability for the Top Researcher Award

Lianfa Li, PhD, currently a Senior Research Associate and Lead Data Scientist at the University of Southern California’s Department of Population and Public Health Sciences, is an exemplary candidate for the Top Researcher Award. His extensive background in data science and machine learning, particularly in the realm of remote sensing and air pollution exposure, positions him as a leader in his field. Below are the reasons why Dr. Li is suitable for this prestigious award:

EDUCATION 🎓📚

  • PhD in Geographical Information Science (June 2005)
    Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
    Advisor: Prof. Jinfeng Wang
  • Bachelor of Science in Resources, Planning and Management (Aug 1998)
    Nanjing University, Nanjing, Jiangsu Province, China
    Advisor: Prof. Yunliang Shi

ACADEMIC EMPLOYMENT 🏛️💼

  • Senior Research Associate, Lead Data Scientist (Aug 2017-Present)
    Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA
    Leading innovations in data science and machine learning, and the modeling efforts in remote sensing and air pollution (exposure and health effects)
  • Research Associate (Aug 2017-July 2014)
    Department of Preventive Medicine, University of Southern California, Los Angeles, CA
  • Associate Specialist (June 2013-June 2014)
    Program in Public Health, University of California, Irvine, CA

HONORS AND AWARDS 🏆🎖️

  1. 2010.6
    The paper about Bayesian risk modeling (Risk Analysis, 30(7), 1157-1175) selected for a media outreach campaign in 2010 by Society for Risk Analysis
  2. 2007.5
    Chinese Academy of Sciences KC Wong Work Incentive Fund
  3. 2004.3
    The Excellent Presidential Scholarship of Chinese Academy of Sciences, 2004

WORKSHOP AND PRESENTATION 🎤📅

  1. Biweekly workshop: “Air pollution and exposure modeling” (2015-present, University of Southern California, California, USA)
  2. Invited presentation: “GCN-assisted U-Net for segmentation of OCT images” (Bay area data science workshop, Mar. 27, 2021)
  3. Invited presentation: “Enhancing semantic segmentation with contextual information” (Bay area data science workshop, Dec. 07, 2019)

Publication top Notes:

Geocomplexity Statistical Indicator to Enhance Multiclass Semantic Segmentation of Remotely Sensed Data with Less Sampling Bias

Multiscale Entropy-Based Surface Complexity Analysis for Land Cover Image Semantic Segmentation

Generating Fine-Scale Aerosol Data through Downscaling with an Artificial Neural Network Enhanced with Transfer Learning

Encoder–Decoder Full Residual Deep Networks for Robust Regression and Spatiotemporal Estimation

Multi-Scale Residual Deep Network for Semantic Segmentation of Buildings with Regularizer of Shape Representation

Optimal Inversion of Conversion Parameters from Satellite AOD to Ground Aerosol Extinction Coefficient Using Automatic Differentiation

Dr. Yunfei Feng | Machine learning | Best Researcher Award

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Dr. Yunfei Feng | Machine learning | Best Researcher Award 

Dr. Yunfei Feng, Department of Computer Science, United States

Dr. Yunfei Philip Feng is an accomplished professional in the field of computer science, currently serving as a Staff Machine Learning Engineer at Walmart Inc.’s Global Tech division. With a Ph.D. in Computer Science from Iowa State University, where his dissertation focused on the recognition of Activities of Daily Living, Dr. Feng has a robust academic background complemented by visiting scholar positions at prestigious institutions such as Peking University, Northeastern University, National Central University, and Nihon University. His research interests include system simulation, robotics, edge computing, computer vision, sensor fusion, machine learning, and wireless communication.Dr. Feng has significantly contributed to Walmart’s technology advancements, notably developing and optimizing systems for job application processing, mentor match recommendations, and internal chatbot functionalities. His expertise extends to building CI/CD pipelines, deploying machine learning models, and enhancing real-time streaming APIs’ performance. Prior to his tenure at Walmart, he held key roles in digital experience and analytics at Sam’s Club Technology, where he led innovative projects in indoor localization, inventory management with AGVs, and mobile app development. Dr. Feng’s early career at China Electronics Corporation involved designing central control rooms for smart buildings and integrating various systems for complex environments. His extensive experience and innovative contributions position him as a leading expert in leveraging technology to improve productivity and user experiences in diverse settings.

Professional Profile:

SCOPUS

Education

Iowa State University, Ames, IA, USA
Ph.D., Computer Science
August 2012 – May 2018

  • Dissertation: Recognition of Activities of Daily Living
  • Committee members: Carl K. Chang, Johnny S. Wong, Peter Martin, Jin Tian, Simanta Mitra

Communication University of China, Beijing, China
Master of Engineering, Communication and Information System
September 2007 – June 2009

  • Overall Ranking: 2/140
  • Focus: Wireless Communication and 3G/4G Cellular Communication, Error Correction Code, Digital Audio Broadcasting
  • Solo PI, 10,000 CNY. Coded Modulation Scheme with CPPC Codes for Digital Television Broadcasting, Beijing, China 2008-2009

Shenyang University of Technology, Shenyang, China
Bachelor’s Degree, Major in Communications Engineering
September 2003 – July 2007

  • Overall Ranking: 3/130
  • Minor in Computer Science

Academic Work

Peking University, Beijing, China
Visiting Scholar, Department of Computer Science
July 2017 – July 2017

Northeastern University, Shenyang, China
Visiting Scholar, Department of Computer Science
June 2017 – June 2017

National Central University, Taoyuan, Taiwan
Visiting Scholar, Department of Computer Science & Information Engineering
June 2016 – July 2016

Nihon University, Koriyama, Fukushima, Japan
Visiting Scholar, Department of Computer Science
June 2016 – June 2016

Research Interests

  • System Simulation
  • Robotics
  • Edge Computing
  • Computer Vision
  • Computer Audition
  • Sensor Fusion on Smart Devices and Smart Systems
  • Machine Learning
  • Deep Learning
  • Wireless Communication
  • Indoor Localization

Publication top Notes:

Sound of Daily Living Identification Based on Hierarchical Situation Audition

LiLo: ADL Localization with Conventional Luminaries and Ambient Light Sensor

A multi-objective decomposition-based ant colony optimisation algorithm with negative pheromone

Overview of cashier-free stores and a virtual simulator

A computer-aided detection system for the detection of lung nodules based on 3D-ResNet