Dr. Jany Shabu | Artificial Intelligence Awards | Best Researcher Award

Posted on 09/01/2025 by ScienceFather

Dr. Jany Shabu | Artificial Intelligence Awards | Best Researcher Award

Dr. Jany Shabu, Sathyabama Institute of Science & Technology, India

Dr. S.L. Jany Shabu is an accomplished Associate Professor in the Department of Computer Science Engineering at Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, India. With a Ph.D. in Image Fusion, her research focuses on multimodal image fusion using intelligent optimization techniques, particularly in the context of brain tumor detection. Dr. Shabu has a strong academic background, holding both M.Tech and MS degrees in Information Technology, and has published extensively, with 58 papers indexed in Scopus and four in WoS. She has received multiple accolades for her contributions to research and education, including cash awards for publishing in high-impact journals and the prestigious NPTEL Discipline Star Certificate. As an active member of the National Institute for Technical Training and Skill Development, Dr. Shabu is dedicated to advancing the field of computer science through her research, teaching, and professional engagement. Her innovative projects, including a Safety Stick for Elders, and her patents in smart traffic control and gesture-based systems, exemplify her commitment to leveraging technology for societal benefit. She has also authored several books on machine learning, cloud computing, and data analytics, further solidifying her reputation as a thought leader in her field. With a robust online presence, including profiles on ORCID and Scopus, Dr. Shabu continues to contribute to academic excellence and innovation in computer science.

Professional Profile:

SCOPUS

Summary of Suitability for Best Researcher Award:

Dr. S.L. Jany Shabu is a commendable candidate for the Best Researcher Award, recognized for her significant contributions to computer science engineering and her innovative research in image fusion and optimization techniques.

Education 🎓

Ph.D. in Image Fusion
Sathyabama Institute of Science and Technology
Thesis Title: Multimodal Image Fusion using Intelligent Optimization Techniques with Brain Tumor Detection
M.Tech (IT) in Information Technology
Sathyabama Institute of Science and Technology
Graduated with First Class
M.S. (IT) in Information Technology
Manonmaniam Sundaranar University
Graduated with First Class

Work Experience 💼

Current Position: Associate Professor, Computer Science Engineering
Sathyabama Institute of Science and Technology

Achievements 🌟

Seed Funding:
Project Title: Safety Stick for Elders
Amount: ₹300,000
Period: Oct 2021 – June 2022
Role: Co Principal Investigator
Patent Holder:
1. SMART TRAFFIC CONTROL SYSTEM USING IOT BASED MONITORING SYSTEM
  Application No: 201741038384 – Published
2. GARMENT STEAMER MANAGEMENT SYSTEM
  Application No: 367890-001 – Published
3. GESTURE BASED ELECTRONIC GADGET OPERATING SYSTEM
  Application No: 202341088351 A – Published
Reviewer:
- Journal of Scientific Research and Reports
- Journal of Pharmaceutical Research International
- International Conference on Computational Intelligence, Networks & Security
- Book Chapter for CRC PRESS Taylor & Francis Group

Awards and Honors 🏆

Cash Award for Publishing Paper in High Impact WOS Journal
Sathyabama Institute of Science and Technology (Teachers Day 2022 & 2024)
NPTEL Discipline Star Certificate
Disciplinarian Award
Sathyabama Institute of Science & Technology, Chennai

Publication Top Notes:

DeepExuDetectNet: Diabetic retinopathy diagnosis: Blood vessel segmentation and exudates disease detection in fundus images

A swarm intelligence optimization for lung cancer detection from RNA-seq gene expression data using convolutional neural networks

A novel framework for entertainment robots in personalized elderly care using adaptive emotional resonance technologies

An Improved Adaptive Neuro-fuzzy Inference Framework for Lung Cancer Detection and Prediction on Internet of Medical Things Platform

Rainfall prediction using machine learning techniques

Online product review using sentiment analysis

Akmal Jahan Mohamed Abdul Cader | Artificial Intelligence | Best Researcher Award

Posted on 28/12/202428/12/2024 by ScienceFather

Akmal Jahan Mohamed Abdul Cader | Artificial Intelligence | Best Researcher Award

Dr. Akmal Jahan Mohamed Abdul Cader, South Eastern University, Sri Lanka.

Dr. Akmal Jahan Mohamed Abdul Cader is a distinguished academic and researcher currently serving as a Senior Lecturer in Computer Science at the South Eastern University of Sri Lanka. With extensive experience in higher education, he is a Visiting Research Fellow at QUT, Australia. His research interests include artificial intelligence, data science, and document image analysis. Dr. Cader has published numerous high-impact articles and is actively involved in academic development and curriculum design. He is committed to advancing education and research in the field of computer science.

Publication Profiles

Googlescholar

Education and Experience

Visiting Research Fellow – QUT Momentum Visiting Fellow, QUT, Australia (2021 – Present)
Senior Lecturer (Computer Science) – South Eastern University of Sri Lanka (2020 – Present)
Sessional Academic – School of Electrical Engineering & Computer Science, QUT (2016 – 2019)
Lecturer (Computer Science) – South Eastern University of Sri Lanka (2012 – 2015)
Assistant Lecturer – South Eastern University of Sri Lanka (2010 – 2012)
Demonstrator in Computer Science – South Eastern University of Sri Lanka (2009 – 2010)

Suitability For The Award

Dr. Mac Akmal Jahan Mohamed Abdul Cader, Senior Lecturer in Computer Science at the South Eastern University of Sri Lanka, is a highly accomplished academic and researcher, making him an exemplary candidate for the Best Researcher Award. With a career spanning over a decade, Dr. Cader has consistently demonstrated leadership in research, teaching, and academic development, particularly in the fields of artificial intelligence, computer science, and digital technologies. His research contributions, coupled with his active involvement in academic service, professional organizations, and international collaborations, solidify his standing as a leading figure in his domain.

Professional Development

Dr. Cader has participated in several professional development programs focused on effective communication, teaching and learning, and project-based learning. He has completed various certifications at QUT, enhancing his skills in pedagogy and curriculum development. His commitment to continuous improvement in education is evident in his active engagement in workshops and training sessions aimed at promoting best practices in teaching. As a Fellow of the Higher Education Academy, he champions high standards in academic instruction and student engagement.

Research Focus

Dr. Cader’s research primarily focuses on artificial intelligence, data science, and document image analysis. He explores the synthesis and application of synthetic metals, aiming to develop innovative solutions in electronics and energy storage. His work on TCNQ chemistry has significant implications for biotechnology and medicine, including the construction of electrochemical sensors and drug delivery systems. By synthesizing novel compounds, he contributes to advancements in both theoretical and practical aspects of computer science and materials research.

Awards and Honors

Senate Honours Award for High Impact Publications – SEUSL (2022 & 2023)
Queensland University of Technology Postgraduate Award (QUTPRA) (2015)
Faculty Write Up (FWU) Scholarship – QUT, Australia (2019)
Effective Communication in Teaching and Learning – QUT, Australia (2019)
Foundation of Teaching and Learning – QUT (2018)

Publication Top Notes

Locating tables in scanned documents for reconstructing and republishing | Cited by: 46 | Year: 2014
Plagiarism Detection on Electronic Text based Assignments using Vector Space Model (ICIAfS14) | Cited by: 37 | Year: 2014
AntiPlag: Plagiarism Detection on Electronic Submissions of Text Based Assignments | Cited by: 34 | Year: 2014
Plagiarism detection tools and techniques: A comprehensive survey | Cited by: 23 | Year: 2021
Fingerprint Systems: Sensors, Image Acquisition, Interoperability and Challenges | Cited by: 11 | Year: 2023
Contactless finger recognition using invariants from higher order spectra of ridge orientation profiles | Cited by: 10 | Year: 2018
Accelerating text-based plagiarism detection using GPUs | Cited by: 10 | Year: 2015
Contactless multiple finger segments based identity verification using information fusion from higher order spectral invariants | Cited by: 9 | Year: 2018

Assoc. Prof. Dr. Mahmoud Bayat | Artificial intelligence Award | Best Researcher Award

Posted on 20/12/2024 by ScienceFather

Assoc. Prof. Dr. Mahmoud Bayat | Artificial intelligence Award | Best Researcher Award

Assoc. Prof. Dr. Mahmoud Bayat, Research Institute of Forests and Rangelands, Iran

Mahmoud Bayat is an Assistant Professor at the Research Institute of Forests and Rangelands, part of the Agricultural Research, Education, and Extension Organization (AREEO) in Tehran, Iran. He earned his B.A., M.Sc., and Ph.D. degrees from the University of Tehran, specializing in forestry science. Mahmoud has collaborated with renowned researchers, including Dr. Charles P.-A. Bourque, Dr. Pete Bettinger, Dr. Eric Zenner, Dr. Aaron Weiskittel, Dr. Harold Burkhart, and Dr. Timo Pukkala. His research focuses on forest modeling and inventory, with particular interest in applying artificial intelligence and machine learning techniques in forestry. Currently, he is working on projects related to growth and yield models for uneven-aged and mixed broadleaf forests using neural networks and the monitoring and mapping of tree species richness in northern Iran’s forests through symbolic regression and artificial neural networks. Mahmoud is proficient in statistical tools such as SPSS and MATLAB, and he is eager to share his expertise and discuss potential collaborations. For more information, his profiles can be found on ResearchGate, Google Scholar, and Scopus.

Professional Profile:

SCOPUS

Mahmoud Bayat’s Suitability for the Research for Best Researcher Award

Based on the provided details, Mahmoud Bayat demonstrates a strong candidacy for the Research for Best Researcher Award due to his extensive academic and professional contributions. Below is a summary supporting his suitability

Education 🎓

Ph.D. in Forestry Science
University of Tehran, Iran
M.Sc. in Forestry Science
University of Tehran, Iran
B.A. in Forestry Science
University of Tehran, Iran

Work Experience 🏢

Assistant Professor
Research Institute of Forests and Rangelands, Agricultural Research, Education and Extension Organization (AREEO)
Tehran, Iran
Year: [Specify Year] – Present
Research Collaborator
Worked with:
- Dr. Charles P.-A. Bourque
- Dr. Pete Bettinger
- Dr. Eric Zenner
- Dr. Aaron Weiskittel
- Dr. Harold Burkhart
- Dr. Timo Pukkala

Research Interests 🔍

Forest modeling and inventory
Application of artificial intelligence and machine learning in forestry

Current Projects 📊

Growth and Yield Models for Uneven-Aged and Mixed Broadleaf Forest
- Method: Neural Network
Monitoring, Mapping, and Modeling Variation in Tree Species Richness
- Method: Symbolic Regression and Artificial Neural Networks
- Location: Northern Iran Forests

Publication Top Notes:

Comparison of Random Forest Models, Support Vector Machine and Multivariate Linear Regression for Biodiversity Assessment in the Hyrcanian Forests

Projected biodiversity in the Hyrcanian Mountain Forest of Iran: an investigation based on two climate scenarios

Recreation Potential Assessment at Tamarix Forest Reserves: A Method Based on Multicriteria Evaluation Approach and Landscape Metrics

Comparison between graph theory connectivity indices and landscape connectivity metrics for modeling river water quality in the southern Caspian sea basin

Development of multiclass alternating decision trees based models for landslide susceptibility mapping

Modeling Tree Growth Responses to Climate Change: A Case Study in Natural Deciduous Mountain Forests

Prof. Dr. Shih-Lin Chang | Artificial Intelligence Awards | Best Researcher Award

Posted on 19/12/2024 by ScienceFather

Prof. Dr. Shih-Lin Chang | Artificial Intelligence Awards | Best Researcher Award

Prof. Dr. Shih-Lin Chang, National Yang Ming Chiao Tung University, Taiwan

Dr. Shih-Lin Chang, is a distinguished cardiologist and academic leader in the field of cardiovascular medicine. He is currently the Chief of the Department of Experimental Examination at Taipei Veterans General Hospital and the Director of the Intelligent Medicine and Telehealth Center within the Cardiovascular Center. Dr. Chang is also a Professor of Medicine at National Yang Ming Chiao Tung University, where he has contributed significantly to research and education in cardiology. Dr. Chang completed his M.D. at China Medical University in 1998 and earned his Ph.D. from National Yang Ming Chiao Tung University in 2012. He underwent extensive training, including a residency in Internal Medicine and fellowships in cardiology and electrophysiology at Taipei Veterans General Hospital. His professional journey includes significant roles such as Staff Cardiologist and Associate Director of the Cardiovascular Research Center at National Yang Ming Chiao Tung University.

Professional Profile:

SCOPUS

Suitability for Best Researcher Award: Shih-Lin Chang, M.D., Ph.D.

Shih-Lin Chang exemplifies the qualities and achievements that make him an outstanding candidate for the Best Researcher Award. With a robust educational background, including an M.D. from China Medical University and a Ph.D. from National Yang Ming Chiao Tung University, Dr. Chang has established himself as a leading figure in cardiology and electrophysiology.

🎓 Education

M.D.: China Medical University, Taiwan (1991–1998)
Ph.D.: National Yang Ming Chiao Tung University, Institute of Clinical Medicine, Taiwan (2007–2012)

💼 Work Experience

2023.8: Chief, Department of Experimental Examination, Taipei Veterans General Hospital Healthcare and Services Center
2023.1: Director of Intelligent Medicine and Telehealth Center, Department of Cardiovascular Center
2022.7: Associate Director, Cardiovascular Research Center, National Yang Ming Chiao Tung University
2019.8: Professor of Medicine, National Yang Ming Chiao Tung University, School of Medicine
2017.10–2020.10: Director, Heart Rhythm Center, Taipei Veterans General Hospital
2016.8–2019.8: Associate Professor of Medicine, National Yang Ming Chiao Tung University
2015.3–2017.3: Secretary-General, Taiwan Heart Rhythm Society
2009.3–Present: Staff Cardiologist, Division of Cardiology, Taipei Veterans General Hospital
2006–2009.3: Staff Cardiologist, Division of Cardiology, Suao Veterans Hospital
2004–2006: Fellowship, Clinical and Basic Electrophysiology Laboratory, Taipei Veterans General Hospital
2003–2005: Fellowship, Division of Cardiology, Taipei Veterans General Hospital
2000–2003: Resident, Department of Internal Medicine, Taipei Veterans General Hospital

🏆 Awards and Honors

Poster Award: 2nd Asia-Pacific Atrial Fibrillation Symposium (2006) 🖼️
First Prize: Young Investigator Award, Taiwan Society of Cardiology (2010) 🥇
Young Investigator Award: 3rd Asia-Pacific Heart Rhythm Society (2010) 🏅
Best Oral Presentation Award: Taiwan Society of Cardiology (2011) 🎤
Best Poster Presentation Award: Taiwan Society of Cardiology (2013) 🖼️
Best Teacher Award: National Yang Ming University (2014, 2016, 2019) 🎓
Best Paper Award: Veterans General Hospitals and University System of Taiwan Joint Research Program (2015, 2018, 2019, 2021) 📝
PBL Tutor Award: National Yang Ming University (2017) 👩‍🏫
Outstanding Journal Paper Special Excellence Award: Taiwan Society for Simulation in Healthcare (2021) 🌟
Gold Award: Outstanding Academic Research Paper in Medical Education, Taipei Veterans General Hospital (2022) 🥇
National Healthcare Quality Award: Smart Services Category (2022) 🏥
Clinical Teaching Excellence Award: Taipei Veterans General Hospital (2023) 📚

🌟 Achievements

Active roles as editor for Acta Cardiologica Sinica (2015–Present) and Clinical Medicine (2014–Present).
Member of APHRS EP Ablation and Digital Health Committees (2024).
Numerous oral and poster presentations at international cardiology conferences.
Invited faculty/speaker at prestigious global cardiology events, including the European Society of Cardiology Congress and Heart Rhythm Society Annual Scientific Sessions.

Publication Top Notes:

Performance of the novel ANTWERP score in predicting heart function improvement after atrial fibrillation ablation in Asian patients with heart failure

Three-dimensional mapping and superior approach for catheter ablation in patients without inferior vena cava access

Effectiveness and safety of non-vitamin K antagonist oral anticoagulants in low-weight patients with atrial fibrillation

Multistep Algorithm to Predict RVOT PVC Site of Origin for Successful Ablation Using Available Criteria: A Two-Center Cross-Validation Study

Frailty and Its Associated Factors in Patients With Atrial Fibrillation: A Cross-Sectional Study

Mr. Zhongwen Hao | Deep learning Award | Best Researcher Award

Posted on 09/09/2024 by ScienceFather

Mr. Zhongwen Hao | Deep learning Award | Best Researcher Award

Mr. Zhongwen Hao, Cranfield University, China

Zhongwen Hao is a Master’s candidate in Aerospace Manufacturing at Cranfield University, UK, and concurrently pursuing a Master of Mechanical Engineering at Nanjing University of Aeronautics and Astronautics, China. He completed his Bachelor’s degree in Electronic Information with a focus on Image Processing from China University of Mining and Technology. His research interests include robot control, visual servoing, image processing, and deep learning. Zhongwen has led notable projects such as visual servoing of robotic arms using deep learning techniques and galaxy image classification. His proficiency in programming with C++, Python, and MATLAB, coupled with his skills in deep learning and image processing, underscores his technical expertise. He has published research on motion prediction and object detection in visual servoing systems. Zhongwen is known for his strong project execution abilities, team spirit, and resilience.

Professional Profile:

ORCID

Summary of Suitability:

Hao’s research direction aligns well with cutting-edge fields such as robot control, visual servoing, image processing, and deep learning. These areas are highly relevant and significant in contemporary technological advancements. Hao has a solid educational foundation with advanced studies in Aerospace Manufacturing and Mechanical Engineering, complemented by a bachelor’s degree in Electronic Information with a focus on Image Processing. This diverse yet interconnected educational background enhances his research capabilities.

Education

Cranfield University, Bedford, UK
Master’s Candidate of Aerospace Manufacturing
Major: Deep Learning and Image Processing
September 2023 – September 2024
Nanjing University of Aeronautics and Astronautics, Nanjing, China
Master of Mechanical Engineering
Major: Mechanical
September 2022 – June 2025 (Expected)
China University of Mining and Technology, Xuzhou, China
Bachelor of Electronic Information
Major: Image Processing
September 2017 – June 2021

Work Experience

Project Leader
Research on Visual Servoing of Robotic Arms Based on Deep Learning
June 2024 – September 2024
- Led research on target detection using the DETR model, trajectory planning with the PSO algorithm, and motion prediction using BiLSTM and KAN neural networks.
- Integrated and simulated algorithms in ROS using Gazebo to validate their effectiveness.
Participator
Galaxy Image Classification Based on Deep Learning
February 2024 – March 2024
- Handled image preprocessing and reconstruction, and implemented galaxy image classification using the VIT model, achieving a classification accuracy of 90%.

Publication top Notes:

Motion Prediction and Object Detection for Image-Based Visual Servoing Systems Using Deep Learning

Prof Dr. Gulnihal Ozbay | Machine Learning Award | Best Researcher Award

Posted on 04/09/2024 by ScienceFather

Prof Dr. Gulnihal Ozbay | Machine Learning Award | Best Researcher Award

Prof Dr. Gulnihal Ozbay, Delaware State University, United States

Dr. Gulnihal Ozbay is a distinguished Professor and Extension Specialist in Natural Resources at Delaware State University, where she also serves as Director of the Environmental Health & Seafood Safety Lab and the Integrative Ph.D. Program in Agriculture, Food, and Environmental Sciences. Her career is marked by significant achievements in diverse fields, including aquaculture, fisheries, water chemistry, and aquatic ecology. Dr. Ozbay is highly regarded for her expertise in program development, grant writing, and student mentorship. She has built and managed several research labs, including the Mariculture Lab and GIS Lab, and has a strong record of collaboration with various institutions and agencies. Dr. Ozbay holds multiple degrees in relevant fields, including a Ph.D. in Fisheries & Allied Aquacultures from Auburn University and an M.Sc. in Food Science & Biotechnology from Delaware State University. Her leadership extends beyond teaching and research to include roles such as Vice President of DSU AAUP and Chair of the DSU Faculty Research Committee. Her commitment to environmental science is evident in her active participation in programs addressing sustainability, climate change, and seafood safety.

Professional Profile:

GOOGLE SCHOLAR

Suitability for the Best Researcher Award

Dr. Gulnihal Ozbay’s extensive career demonstrates exceptional proficiency in various fields related to natural resources, including aquaculture, fisheries, water chemistry, aquatic ecology, climate science, seafood chemistry, and microbiology. His role as a Professor and Extension Specialist, combined with his leadership positions, showcases his strong research background and administrative capabilities.

🎓 Professional Preparation

Ph.D., Fisheries & Allied Aquacultures (Water Quality)
Auburn University, 2002
Ph.D. Credits, Food Science & Technology
Dalhousie University, 1999
M.Sc., Bio-Resource Engineering (Marine Bio-Resources)
University of Maine, 1996
M.Sc., Food Science & Biotechnology
Delaware State University, 2016
B.Sc., Fisheries & Aquaculture Engineering
University of Ondokuzmayis, 1991

🏆 Professional Appointments

Professor & Extension Specialist, Natural Resources
Delaware State University, 2012 – Present
Adjunct Faculty, Food Science & Biotechnology Graduate Program
DSU, 2008 – Present
Adjunct Faculty, Applied Chemistry Graduate Program
DSU, 2018 – Present
Director, Environmental Health & Seafood Safety Lab
DSU, 2009 – Present
Director, Integrative Ph.D. Program in Agriculture, Food and Environmental Sciences (IAFES)
DSU, 2021 – Present
Vice President, DSU AAUP
2021 – Present

📚 Teaching Experience

Environmental Toxicology
DSU, 2020-Present
Climatology
DSU, 2012-Present
Introduction to Environmental Science
DSU, 2011-Present
Special Problems (Sustainability & Climate Change)
DSU, 2004-Present
Graduate Seminar
DSU, 2010

Publication top Notes:

Design and operation of effective landfills with minimal effects on the environment and human health

CITED: 78

A comparison of the macrofaunal communities inhabiting a Crassostrea virginica oyster reef and oyster aquaculture gear in Indian River Bay, Delaware

CITED: 74

Hemocytes are sites of enteric virus persistence within oysters

CITED: 68

Valorization of food loss and wastes: Feedstocks for biofuels and valuable chemicals

CITED:56

An analysis of refractometry as a method of determining blood total protein concentration in the American lobster Homarus americanus (Milne Edwards)

CITED: 53

Antimicrobial activity of vinegar on bacterial species isolated from retails and local channel catfish (Ictalurus punctatus). J. food Process Technol, S11-001

CITED: 51

Mr. Omer Tariq | Artificial Intelligence Award | Best Researcher Award

Posted on 14/08/2024 by ScienceFather

Mr. Omer Tariq | Artificial Intelligence Award | Best Researcher Award

Mr. Omer Tariq, Korea Advanced Institute of Science and Technology, KAIST, South Korea

Omer Tariq is a Ph.D. candidate at the Korea Advanced Institute of Science and Technology (KAIST), specializing in efficient and privacy-preserving deep learning for AIoT and autonomous systems. With a strong foundation in digital ASIC design, embedded systems, and hardware design, Omer has over seven years of experience in developing and deploying innovative machine learning solutions using TensorFlow, TensorRT, and PyTorch. His research includes advanced robotics software systems, autonomous navigation, and state-of-the-art motion planning algorithms. He has led teams in high-performance SoC/RTL design and verification at the National Electronics Complex, Pakistan, and contributed to satellite imaging systems at SUPARCO. Omer holds a BSc in Electrical Engineering from the University of Engineering and Technology, Taxila, and has published several papers in prominent journals. His technical skills are complemented by a range of certifications in machine learning, data science, and digital signal processing.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award

Omer Tariq is a Ph.D. candidate specializing in efficient and privacy-preserving deep learning for AIoT and Autonomous Systems. His work is highly relevant to current technological advancements and addresses significant challenges in machine learning, robotics, and autonomous systems. His research includes:

Education

Korea Advanced Institute of Science and Technology (KAIST)
Doctor of Philosophy (Ph.D.) in Computer Science
May 2021 – July 2025

Majors: Machine Learning & AI
CGPA: 3.74/4.3
Coursework: Programming for AI, Introduction to Artificial Intelligence, Design and Analysis of Algorithms, Intelligent Robotics, Human-Computer Interaction, Artificial Intelligence and Machine Learning, Technical Writing for Computer Science, Advanced Machine Learning, IoT Datascience

University of Engineering and Technology (UET), Taxila
Bachelor of Science in Electrical Engineering
Nov 2010 – July 2014

CGPA: 3.25/4.0
Thesis: Computer Vision-Assisted Object Detection and Control Framework for 3-DoF Robotic Arm
Area: Microelectronics, Control Systems, and Advanced Computer Architecture

Work Experience

Department of Industrial & Systems Engineering (ISysE), KAIST
Research Assistant
Nov. 2023 – March 2024

Designed and developed the electronics and power management module for the DAIM-Autonomous Mobile Robot, enhancing operational efficiency and reliability.
Engineered advanced robotics software systems for autonomous navigation and task execution.
Implemented state-of-the-art robot motion planning, mapping, and localization (SLAM) algorithms to improve real-time navigation accuracy.

National Electronics Complex, Pakistan (NECOP)
Engineering Manager & Team Lead
Apr. 2019 – Sep. 2022

Led verification and validation of high-performance SoC/RTL designs, ensuring system performance and reliability.
Spearheaded RTL development and optimization for high-performance IC designs, including logic synthesis, DFT, scan chain insertion, formal verification, and static timing analysis.
Managed the use of Synopsys and Cadence EDA tools for front-end and back-end digital IC design processes.

National Space Agency, Pakistan (SUPARCO)
Assistant Manager
Oct. 2014 – Apr. 2019

Designed and developed satellite imaging payload systems for national satellite missions.
Engineered high-speed, multi-layer PCB designs and conducted signal/power integrity simulations for satellite systems.
Developed embedded systems for the Satellite Ku-Band Positioning Unit, enhancing communication and positioning capabilities.

Publication top Notes:

2D Particle Filter Accelerator for Mobile Robot Indoor Localization and Pose Estimation

TabCLR: Contrastive Learning Representation of Tabular Data Classification for Indoor-Outdoor Detection

Compact Walsh–Hadamard Transform-Driven S-Box Design for ASIC Implementations

DeepIOD: Towards A Context-Aware Indoor–Outdoor Detection Framework Using Smartphone Sensors

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

Posted on 06/08/2024 by ScienceFather

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 🏆🎖️

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
2007.5
Chinese Academy of Sciences KC Wong Work Incentive Fund
2004.3
The Excellent Presidential Scholarship of Chinese Academy of Sciences, 2004

WORKSHOP AND PRESENTATION 🎤📅

Biweekly workshop: “Air pollution and exposure modeling” (2015-present, University of Southern California, California, USA)
Invited presentation: “GCN-assisted U-Net for segmentation of OCT images” (Bay area data science workshop, Mar. 27, 2021)
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

Ms. Hind MEZIANE | Artificial Intelligence | Best Scholar Award

Posted on 01/08/2024 by ScienceFather

Ms. Hind MEZIANE | Artificial Intelligence | Best Scholar Award

Ms. Hind MEZIANE, ACSA Lab, Faculty of Sciences, University Mohammed First, Oujda, Morocco

Hind Meziane is a dedicated researcher and Ph.D. candidate in Computer Science at the ACSA Laboratory, Department of Mathematics, Faculty of Sciences, Mohammed Premier University, Oujda, Morocco. Her academic journey began with a Baccalaureate in Science (Science Mathematics Option B) from Mehdi Ben Berka High School in Oujda in 2012. She then pursued higher education at Mohammed Premier University, obtaining a DEUG in Mathematics and Computer Science (2012-2014), a LICENSE in Mathematics and Computer Science (2014-2016), and a Specialized Master’s in Computer Engineering with Honors (2017-2019).

Professional Profile:

ORCID

SCOPUS

GOOGLE SCHOLAR

Summary of Suitability for Best Scholar Award

Hind Meziane is a highly accomplished researcher whose work primarily focuses on the security of Internet of Things (IoT) systems. She is currently pursuing a Ph.D. in Computer Science at Mohammed Premier University and has an impressive academic background, including a specialized master’s degree in Computer Engineering and a bachelor’s degree in Mathematics and Computer Science. Her research contributions are well-documented through various publications in reputable international journals and conference proceedings.

🎓 Education:

2019-Present: Doctorate (PhD) in Computer Science at Mohammed Premier University, Faculty of Sciences, Oujda.
2017-2019: Specialized Master in Computer Engineering, with Honors, at Mohammed Premier University, Faculty of Sciences, Oujda.
2014-2016: LICENSE in Mathematics and Computer Science from Mohammed Premier University, Faculty of Sciences, Oujda.
2012-2014: DEUG in Mathematics and Computer Science from Mohammed Premier University, Faculty of Sciences, Oujda.
2011-2012: Baccalaureate in Science, Mathematics Option B from Mehdi Ben Berka High School, Oujda.

Publication top Notes:

A survey on performance evaluation of artificial intelligence algorithms for improving IoT security systems

A Comparative Study for Modeling IoT Security Systems

Modeling IoT based Forest Fire Detection System with IoTsec

A Study of Modelling IoT Security Systems with Unified Modelling Language (UML)

Classifying security attacks in iot using ctm method

Internet of Things: Classification of attacks using CTM method

Prof. Changgyun Kim | Artificial Intelligence Award | Best Researcher Award

Posted on 25/07/2024 by ScienceFather

Prof. Changgyun Kim | Artificial Intelligence Award | Best Researcher Award

Prof. Changgyun Kim, Department of Artificial Intelligence & Software/Samcheok,South Korea

Changgyun Kim is an esteemed academic and researcher associated with Kangwon National University, Department of Artificial Intelligence & Software, and Dongguk University’s Industrial Engineering department in South Korea. His research expertise spans deep learning, healthcare, and data mining. He has made significant contributions to the field, including developing AI-based systems for detecting betting anomalies in sports, diagnosing tooth-related diseases using panoramic images, and creating models for obesity diagnosis using 3D body information. His work is published in renowned journals such as Scientific Reports, Annals of Applied Sport Science, JMIR Medical Informatics, Sensors, Sustainability, the International Journal of Distributed Sensor Networks, and Applied Sciences. Dr. Kim’s notable projects include establishing IoT-based smart factories for SMEs in Korea and developing web applications for obesity diagnosis using data mining methodologies. His extensive research portfolio underscores his commitment to advancing AI applications in various domains

Professional Profile:

ORCID

Education

No specific details about Changgyun Kim’s educational background are provided in the provided information. To give a more comprehensive overview, details such as degrees obtained, institutions attended, and fields of study would be needed.

Work Experience

Dongguk University: Jung-gu, Seoul, KR
- Department: Industrial Engineering
- Position: Not specified in the provided information.
Kangwon National University
- Department: Artificial Intelligence & Software
- Position: Not specified in the provided information.