Khushboo Singh | Engineering | Best Researcher Award

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Dr. Khushboo Singh | Engineering | Best Researcher Award

Research Fellow at University of Technology Sydney, Australia

Dr. Khushboo Singh 🎓🔬 is a Postdoctoral Research Fellow at the University of Technology Sydney 🇦🇺. With 10+ years of experience in academia, defence, and industry, she specializes in high-power millimetre-wave antennas 🚀📡. Her collaboration with the Defence Science and Technology Group (DSTG) has earned her national recognition, including the prestigious Eureka Prize 🏆. Passionate about cutting-edge tech, she also works on space, maritime, and mobile satellite communication systems 🌌🌊📶. A dedicated mentor and leader, Dr. Singh actively supports women in STEM 💪👩‍🔬 while advancing Australia’s research landscape through innovation and excellence 🌟.

Professional Profile:

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🔹 Education & Experience 

🎓 Education:

  • 📍 Ph.D. in Electrical & Electronics Engineering | Macquarie University, Australia | 2021

  • 📍 M.Sc. (Research) in Electronics & Communication | LNMIIT, India | 2014 | CPI: 9/10

  • 📍 B.Tech in Electronics & Communication | SHIATS, India | 2012 | CPI: 9.7/10

💼 Experience:

  • 👩‍🔬 Postdoctoral Research Fellow | UTS | Nov 2023 – Present

  • 👩‍🏫 Research Associate | UTS | Nov 2020 – Oct 2023

  • 🌏 Visiting Researcher | IIT-Kanpur | Mar – May 2023

  • 🧠 Technical Researcher | Electrotechnik Pty Ltd. | Nov 2019 – Mar 2020

  • 🎓 Casual Tutor | Macquarie University | 2017, 2024

  • 👩‍🏫 Guest Lecturer | Swami Rama Himalayan University | 2015 – 2016

  • 👩‍🏫 Assistant Professor | Pratap Institute, India | 2014 – 2015

🔹 Professional Development 

Dr. Singh is a passionate leader in research and professional mentoring 🌟. She serves as a mentor in multiple STEM programs 👩‍🔬🤝 including Women in Engineering and WiSR at UTS, encouraging female participation in science and technology 👩‍💻👩‍🔬. As award chair for the 2025 Australian Microwave Symposium 🏅 and a past session organizer for major IEEE and EuCAP conferences, she actively contributes to the global antenna research community 🌐📡. She also provides project supervision, peer reviews, and guidance to students and engineers, playing a key role in shaping future tech talent and research direction 🚀🧑‍🔬.

🔹 Research Focus 

Dr. Singh’s research centers on high-power, metasurface-based millimetre-wave antennas 📡⚡ with beam-steering and in-antenna power-combining features. Her work has major applications in defence, space, maritime, and satellite communications 🛰️🚢. She collaborates with Australia’s Defence Science and Technology Group (DSTG) to design antennas suited for compact, power-constrained environments 🛠️. Her contributions enable better surveillance, radar, and communication systems in mission-critical scenarios 🎯. She is also exploring inter-satellite link antennas and intelligent surfaces for next-gen wireless communication 🌐📶, cementing her role at the intersection of advanced electromagnetics, microwave engineering, and national security defense systems 🛡️.

🔹 Awards & Honors 

🏆 Awards & Honors:

  • 🥇 Winner – 2024 ICEAA – IEEE APWC Best Paper Award

  • 🏅 Winner – 2023 Eureka Prize for Outstanding Science for Safeguarding Australia

  • 👏 Finalist – 2025 AUS SPACE Academic Research Team of the Year

  • 👩‍🚀 Finalist – 2024 ADM Women in Defence (R&D Category)

  • 🧪 Finalist – 2022 UTS Vice-Chancellor’s Award for Research Excellence

  • ⭐ Top 200 Reviewer – IEEE Transactions on Antennas & Propagation (2023)

  • 🥇 Winner – 2019 IEEE NSW Outstanding Student Volunteer

  • 💰 Winner – CHOOSEMATHS Grant by AMSI & BHP Foundation (2017)

  • 🎓 Scholarships – iRTP (2017–2020), LNMIIT Research Stipend (2012–2014)

Publication Top Notes

📘 1. Controlling the Most Significant Grating Lobes in Two-Dimensional Beam-Steering Systems with Phase-Gradient Metasurfaces

  • Authors: K. Singh, M.U. Afzal, M. Kovaleva, K.P. Esselle

  • Journal: IEEE Transactions on Antennas and Propagation

  • Volume/Issue: 68(3), Pages 1389–1401

  • Year: 2019

  • Citations: 86

  • DOI: 10.1109/TAP.2019.2940403

  • Highlights:

    • Introduced techniques to control dominant grating lobes in 2D beam-steering.

    • Employed phase-gradient metasurfaces to steer beams without complex feed networks.

    • Achieved low sidelobe levels and improved directivity.

    • Combined analytical modeling with full-wave electromagnetic simulations.

📗 2. Designing Efficient Phase-Gradient Metasurfaces for Near-Field Meta-Steering Systems

  • Authors: K. Singh, M.U. Afzal, K.P. Esselle

  • Journal: IEEE Access

  • Volume: 9, Pages 109080–109093

  • Year: 2021

  • Citations: 34

  • DOI: 10.1109/ACCESS.2021.3102204

  • Highlights:

    • Focused on near-field applications such as wireless power transfer.

    • Proposed a method to optimize phase response for compact metasurfaces.

    • Improved phase accuracy and minimized aperture size.

    • Demonstrated via simulations and measured prototypes.

📙 3. State-of-the-Art Passive Beam-Steering Antenna Technologies: Challenges and Capabilities

  • Authors: F. Ahmed, K. Singh, K.P. Esselle

  • Journal: IEEE Access

  • Volume: 11, Pages 69101–69116

  • Year: 2023

  • Citations: 28

  • DOI: 10.1109/ACCESS.2023.3285260

  • Highlights:

    • Comprehensive review of passive beam-steering technologies.

    • Covers reconfigurable metasurfaces, mechanical rotation, and tunable materials.

    • Discusses energy efficiency, low-cost manufacturing, and practical limitations.

    • Key insight for researchers targeting 6G, IoT, and wearable tech.

📕 4. Evaluation Planning for Artificial Intelligence-Based Industry 6.0 Metaverse Integration

  • Author: K. Singh

  • Conference: Intelligent Human Systems Integration (IHSI 2023)

  • Year: 2023

  • Citations: 27

  • DOI: 10.1007/978-3-031-28032-0_40

  • Highlights:

    • Discusses AI-driven frameworks for integrating Industry 6.0 with the metaverse.

    • Addresses human-system interaction, digital twins, and smart automation.

    • Proposes an evaluation roadmap for real-time metaverse-industrial synergy.

    • Useful for future cyber-physical systems and smart manufacturing.

📒 5. Accurate Optimization Technique for Phase-Gradient Metasurfaces Used in Compact Near-Field Meta-Steering Systems

  • Authors: K. Singh, M.U. Afzal, K.P. Esselle

  • Journal: Scientific Reports (Nature Publishing Group)

  • Volume: 12, Article 4118

  • Year: 2022

  • Citations: 20

  • DOI: 10.1038/s41598-022-08057-8

  • Highlights:

    • Developed a precise numerical optimization technique for metasurface design.

    • Reduced phase errors, enabling high-accuracy near-field beam control.

    • Achieved better performance in compact and portable systems.

    • Practical for radar, medical imaging, and wireless power applications.

Conclusion

Dr. Khushboo Singh exemplifies the qualities of an outstanding researcher — innovative, impactful, and committed to scientific excellence. Her exceptional track record in antenna technology for defense and space applications, combined with her leadership in mentoring and research supervision, makes her a standout candidate for the Best Researcher Award. Her research is not only scientifically robust but also socially and nationally significant, particularly in safeguarding technological frontiers of Australia.

She is a role model for aspiring researchers, especially women in STEM, and a worthy recipient of such an honor.

Xiaohu Mo | Charmonium Physics | Best Researcher Award

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Prof. Xiaohu Mo | Charmonium Physics | Best Researcher Award

Professor at Institute of High Energy Physics, Chinese Academy of Sciences, China

Mo Xiaohu (born 1969) is a renowned Chinese physicist specializing in ⚛️ particle and nuclear physics. He earned his B.Sc. from Beijing Institute of Technology (1992 🎓), M.Sc. from Tsinghua University (1997 📘), and Ph.D. from the Institute of High Energy Physics (2001 📕). He completed his postdoctoral research at the China Center of Advanced Science and Technology 🌐. Since 2010, he has been a professor at the Institute of High Energy Physics. His work in charmonium physics, including detector development and τ-mass scan optimization, has advanced experimental precision at BEPCII/BESIII 🔬. He has published over 50 influential papers 📄.

Professional Profile:

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🔹 Education and Experience 

  • 🎓 B.Sc. – Beijing Institute of Technology (1992)

  • 📘 M.Sc. – Tsinghua University (1997)

  • 📕 Ph.D. – Institute of High Energy Physics (2001)

  • 🧪 Postdoc – China Center of Advanced Science and Technology (2001–2003)

  • 👨‍🏫 Professor – Institute of High Energy Physics (since 2010)

🔹 Professional Development 

Mo Xiaohu has played a pivotal role in enhancing the precision of experimental physics in China 🔬. He led the construction of a high-accuracy beam energy measurement system at BEPCII ⚙️, which significantly improved the detector and accelerator performance. His creative input in τ-mass scan strategy through the sampling and searching method 📊 led to optimized data collection techniques. Alongside Profs. Yuan Chengzheng and Wang Ping, he introduced the theory of a universal large phase between strong and electromagnetic interactions 🌌. His expertise spans data analysis, phenomenology, and hardware-software integration, contributing to both theoretical insight and experimental innovation 🧠🔧.

🔹 Research Focus 

Mo Xiaohu’s research focus lies in the domain of charmonium physics within particle and nuclear physics 🧲⚛️. He has extensive experience in both theoretical phenomenology and practical data analysis, making significant contributions to understanding the interplay of strong and electromagnetic forces in hadron structures 🔍. His work aims to uncover fundamental characteristics of quark interactions and quantum states using advanced collider experiments like BEPCII/BESIII 🚀. By integrating experimental hardware development with analytical models, he enhances the precision and scope of measurements in subatomic particle studies, helping push the boundaries of modern physics exploration 📡📈.

🔹 Awards and Honors 

  • 🏆 Beijing Science and Technology Prize (Second-Class) – 2012

  • 📄 Published 50+ research papers in domestic and international journals

  • 🔧 Led construction of high-accuracy beam energy measurement system at BEPCII

  • 💡 Co-proposed conjecture on universal large phase in charmonium physics

Publication Top Notes

1. Generic Symmetry Analysis of Charmonium Decay

  • Journal: Physics Letters B

  • Date: February 2025

  • Volume: 861

  • Article ID: 139287

  • DOI: 10.1016/j.physletb.2025.139287

  • Highlights: Provides a symmetry-based framework using SU(3) flavor analysis for charmonium decays, including symmetry breaking effects. Offers a universal parametrization scheme for binary, ternary, and radiative decay channels.

2. Symmetry Analysis Involving Meson Mixing for Charmonium Decay

  • Journal: Physical Review D

  • Date: February 28, 2024

  • Volume: 109

  • Issue: 3

  • Article ID: 036036

  • DOI: 10.1103/PhysRevD.109.036036

  • Highlights: Examines the impact of meson mixing, particularly η-η′, on charmonium decay modes. Discusses flavor symmetry breaking and interference patterns in decay amplitudes.

3. Symmetry Analysis of Charmonium Two-Body Decay

  • Journal: Physical Review D

  • Date: May 8, 2023

  • Volume: 107

  • Issue: 9

  • Article ID: 094009

  • DOI: 10.1103/PhysRevD.107.094009

  • Highlights: Focuses on two-body final states in charmonium decays. Derives amplitude relations from flavor SU(3) symmetry and investigates isospin and G-parity constraints.

4. Symmetry Analysis of Charmonium Decays to Two-Baryon Final State

  • Journal: Physics Letters B

  • Date: March 2022

  • Volume: 827

  • Article ID: 136927

  • DOI: 10.1016/j.physletb.2022.136927

  • Highlights: Analyzes decay of charmonium into baryon-antibaryon pairs using SU(3) symmetry and Wigner-Eckart theorem. Applies results to decay modes like J/ψ→ppˉJ/\psi \to p\bar{p}, ΛΛˉ\Lambda\bar{\Lambda}, etc.

5. Hadronic Cross Section of e+e−e^+e^- Annihilation at Bottomonium Energy Region

  • Journal: Chinese Physics C

  • Date: August 2020

  • Volume: 44

  • Issue: 8

  • Article ID: 083001

  • DOI: 10.1088/1674-1137/44/8/083001

  • Institution: Institute of High Energy Physics, Chinese Academy of Sciences

  • Highlights: Presents measurements of hadronic cross sections at bottomonium resonances. Useful for precision tests of QCD and extracting resonance parameters.

Conclusion:

Prof. Mo Xiaohu clearly demonstrates all the hallmarks of a Best Researcher Award recipient: originality in theoretical physics, hands-on impact in experimental system construction, innovation in methodology, and a consistent, high-quality publication record. His work has not only advanced knowledge in charmonium and τ physics but also contributed to the operational strength of China’s major experimental facilities.

Jeongho Ahn | Applied Mathematics | Best Researcher Award

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Dr. Jeongho Ahn | Applied Mathematics | Best Researcher Award

Full Professor at Arkansas State University, United States

Dr. Jeongho Ahn is a full professor in the Department of Mathematics and Statistics at Arkansas State University (ASU) since Fall 2021. He has been part of ASU since 2008, serving in various roles, including associate and assistant professor. Dr. Ahn earned his Ph.D. in Mathematics from The University of Iowa in 2003. His research focuses on applied mathematics, numerical analysis, partial differential equations, and dynamic contact problems. He is known for his work on finite element methods and complementarity problems. Dr. Ahn is dedicated to teaching and research with a strong commitment to the advancement of mathematics. 📚🧑‍🏫🔢

Professional Profile:

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Education and Experience

  • Ph.D. in Mathematics from The University of Iowa, USA (2003) 🎓

  • M.S. in Mathematics from Kyung Hee University, South Korea (1991) 🇰🇷

  • B.S. in Mathematics from Kyung Hee University, South Korea (1989) 🇰🇷

Teaching Experience:

  • Full Professor, Department of Mathematics and Statistics, ASU (2021–Present) 📚

  • Associate Professor, ASU (2015–2021) 🧑‍🏫

  • Assistant Professor, ASU (2009–2015) 🔢

  • Visiting Assistant Professor, ASU (2008–2009) 🌍

Professional Development 

Dr. Jeongho Ahn has continuously advanced his academic and professional career, establishing himself as a leader in applied mathematics. With years of experience, his teaching spans topics such as algebra, calculus, differential equations, and numerical analysis. He has worked extensively on research in dynamic contact problems and finite element methods, significantly contributing to the development of mathematical theories. Dr. Ahn remains engaged in further professional development through his active research in numerical methods, participating in conferences and workshops to share insights and innovations in applied mathematics. His work fosters collaboration in mathematical and engineering fields. 🏫🔬👨‍🔬

Research Focus 

Dr. Jeongho Ahn’s research primarily revolves around applied mathematics, where he explores numerical analysis, partial differential equations (PDEs), and dynamic contact problems. His expertise includes the development of finite element methods used to solve complex equations in various applications. He works on complementarity problems and differential variational inequalities, addressing real-world challenges in engineering, physics, and economics. By advancing computational techniques, Dr. Ahn aims to improve mathematical models in diverse fields, making significant strides in mathematical modeling and problem-solving methodologies that have broad implications in science and technology. 📊⚙️💻🧮

Awards and Honors

  • Full Professor, Department of Mathematics and Statistics, ASU (2021–Present) 🏅

  • Associate Professor, ASU (2015–2021) 🌟

  • Assistant Professor, ASU (2009–2015) 🎓

Publication Top Notes

  • Detachment Waves in Frictional Contact: Analysis and Simulations of a Two-Mass System

    • Citation: Ahn, J. (2024). Detachment waves in frictional contact: analysis and simulations of a two-mass system. Nonsmooth Problems with Publications in Mathematics, Banach Center Publications.

    • Year: 2024

    • Details: This paper likely explores detachment waves in frictional contact between two masses. It may involve the modeling and simulation of how one mass separates from another due to dynamic forces and friction.

  • A Generalized Duffing Equation with the Coulomb’s Friction Law and Signorini-Type Contact Conditions

    • Citation: Ahn, J. (2023). A generalized Duffing equation with the Coulomb’s friction law and Signorini-type contact conditions. Nonlinear Analysis: Real World Applications.

    • Year: 2023

    • Details: This paper generalizes the Duffing oscillator equation by including Coulomb friction and Signorini contact conditions, both of which introduce nonsmooth behaviors into the system. It explores how these factors influence nonlinear oscillations and stability.

  • A Spring-Beam System with Signorini’s Condition and the Normal Compliance Condition

    • Citation: Ahn, J. (2023). A spring-beam system with Signorini’s condition and the normal compliance condition. International Journal of Numerical Analysis and Modeling.

    • Year: 2023

    • Details: This study investigates a spring-beam system under Signorini’s non-penetration condition and normal compliance, examining how these boundary conditions affect the system’s deformation and response to applied forces.

  • Nonlinear Thermoviscoelastic Timoshenko Beams with Dynamic Frictional Contact

    • Citation: Ahn, J. (2022). Nonlinear thermoviscoelastic Timoshenko beams with dynamic frictional contact. Applied Analysis.

    • Year: 2022

    • Details: The paper addresses Timoshenko beams that exhibit nonlinear thermoviscoelastic behavior and experience dynamic frictional contact. The study likely combines thermal, mechanical, and viscoelastic effects to model beam deformations under various dynamic conditions.

  • A Rod-Beam System with Dynamic Contact and Thermal Exchange Condition

    • Citation: Ahn, J. (2021). A rod-beam system with dynamic contact and thermal exchange condition. Applied Mathematics and Computation.

    • Year: 2021

    • Details: This paper discusses the interaction between a rod and a beam, incorporating dynamic contact and thermal exchange conditions. The study likely explores how thermal effects influence the mechanical response of the system when subject to contact forces.

Conclusion 

Dr. Jeongho Ahn’s career is defined by a remarkable blend of academic leadership, cutting-edge research, and teaching excellence. His work in numerical methods, finite element analysis, and applied mathematics has had a broad impact across multiple domains, including engineering, materials science, and economics. He is not only advancing mathematical theory but also developing practical tools that are shaping the future of these fields.

Given his long-standing academic contributions, innovative research, and commitment to excellence in education, Dr. Jeongho Ahn is exceptionally well-qualified for the Best Researcher Award. His work continues to influence both the academic world and the practical, real-world application of mathematical methods, marking him as a leading figure in his field.

Ehsan Adibnia | Engineering | Best Academic Researcher Award

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Dr. Ehsan Adibnia | Engineering | Best Academic Researcher Award

Dr. Ehsan Adibnia at University of Sistan and Baluchestan, Iran

Dr. Ehsan Adibnia 🎓 is a dedicated academic researcher in electrical engineering ⚡, specializing in cutting-edge fields such as artificial intelligence 🤖, machine learning 📊, deep learning 🧠, nanophotonics 💡, optics 🔬, and plasmonics ✨. He is proficient in Python 🐍, MATLAB 🧮, and Visual Basic, and utilizes simulation tools like Lumerical 📈, COMSOL 🧪, and RSoft 🔧 to drive innovative research. Fluent in English 🇬🇧 and Persian 🇮🇷, Dr. Adibnia contributes to academic conferences and peer-reviewed journals 📚. He is currently pursuing his Ph.D. and actively engaged in interdisciplinary scientific exploration 🌐.

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🔹 Education & Experience 

🎓 Ph.D. in Electrical Engineering – University of Sistan and Baluchestan, Zahedan, Iran (Expected 2025)
🎓 B.S. in Electrical Engineering – University of Sistan and Baluchestan, Zahedan, Iran (2014)
🧑‍💼 Executive Committee Member – 27th Iranian Conference on Optics and Photonics & 13th Conference on Photonic Engineering and Technology
🖋️ Assistant Editor – International Journal (Name not specified)
🔍 Researcher – Actively engaged in interdisciplinary AI & photonics research projects

🔹 Professional Development 

Dr. Ehsan Adibnia continually enhances his professional growth through active participation in conferences 🧑‍🏫, committee leadership 🗂️, and editorial work 📑. He develops algorithms and conducts simulations using advanced tools such as Lumerical 🔬, COMSOL 🧪, and RSoft 💻. His expertise in AI and photonics drives innovative research and collaboration 🌍. He also hones his programming skills in MATLAB 🧮, Python 🐍, and VBA 🧠, ensuring precision in modeling and data analysis. His hands-on knowledge in PLC systems 🤖 and industrial automation makes him versatile across both academic and applied research settings 🏭.

🔹 Research Focus 

Dr. Adibnia’s research focuses on the fusion of artificial intelligence 🤖 and photonics 💡. His work explores machine learning 📊, deep learning 🧠, nanophotonics 🔬, plasmonics ✨, optical switching 🔁, and slow light 🐢 technologies. He is particularly interested in leveraging these technologies in biosensors 🧫, metamaterials 🔷, and quantum optics ⚛️. Through simulation and algorithm development, he aims to optimize performance in optoelectronic and photonic systems 🔍. His interdisciplinary research bridges electrical engineering with physics and AI, creating advanced systems for diagnostics, sensing, and smart environments 🌐.

🔹 Awards & Honors 

🏅 Executive Committee Role – 27th Iranian Conference on Optics and Photonics
🏅 Executive Committee Role – 13th Iranian Conference on Photonic Engineering and Technology
📜 Assistant Editor – International scientific journal (name not specified)
🧠 Scopus-indexed Researcher – Scopus ID: 58485414000

Publication Top Notes

🔹 High-performance and compact photonic crystal channel drop filter using P-shaped ring resonator

  • Journal: Results in Optics

  • Date: Dec 2025

  • DOI: 10.1016/j.rio.2025.100817

  • Summary: Proposes a novel P-shaped ring resonator design for channel drop filters in photonic crystal structures. Focuses on achieving high performance in terms of compactness and spectral selectivity for integrated optical circuits.

🔹 Optimizing Few-Mode Erbium-Doped Fiber Amplifiers for high-capacity optical networks using a multi-objective optimization algorithm

  • Journal: Optical Fiber Technology

  • Date: Sep 2025

  • DOI: 10.1016/j.yofte.2025.104186

  • Summary: Introduces a multi-objective optimization approach for designing few-mode EDFAs, targeting performance improvements in next-gen high-capacity optical networks.

🔹 Inverse design of octagonal plasmonic structure for switching using deep learning

  • Journal: Results in Physics

  • Date: Apr 2025

  • DOI: 10.1016/j.rinp.2025.108197

  • Summary: Utilizes deep learning for the inverse design of an octagonal plasmonic structure used in optical switching, demonstrating enhanced precision and compact design capability.

🔹 Chirped apodized fiber Bragg gratings inverse design via deep learning

  • Journal: Optics & Laser Technology

  • Date: 2025

  • DOI: 10.1016/J.OPTLASTEC.2024.111766

  • WOS UID: WOS:001311493000001

  • Summary: Applies deep learning to the inverse design of chirped apodized fiber Bragg gratings, optimizing the spectral characteristics for filtering and sensing applications.

🔹 Inverse Design of FBG-Based Optical Filters Using Deep Learning: A Hybrid CNN-MLP Approach

  • Journal: Journal of Lightwave Technology

  • Date: 2025

  • DOI: 10.1109/JLT.2025.3534275

  • Summary: Proposes a hybrid CNN-MLP architecture to design fiber Bragg grating (FBG) optical filters, improving accuracy and speed in the inverse design process using deep learning techniques.

Conclusion

Dr. Adibnia is still in the process of completing his Ph.D., his broad technical expertise, multidisciplinary research focus, early academic leadership roles, and active participation in both national and international platforms make him a highly promising candidate for the Best Academic Researcher Award in the early-career researcher or emerging researcher category.

Ambachew Alemu | Atmospheric Physics| Excellence in Research

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Dr. Ambachew Alemu | Atmospheric Physics| Excellence in Research

Assisstant Professor at Debre Tabor University, Ethiopia

Dr. Ambachew Abeje Alemu 🇪🇹 is an Assistant Professor of Atmospheric Physics at Debre Tabor University 🌦️📚. With over 15 years of teaching and research experience, he is known for his commitment to academic excellence and atmospheric science innovation 🚀🛰️. He earned his PhD from Bahir Dar University, specializing in aerosol variability using satellite data 📡. Fluent in English and Amharic 🗣️, Dr. Alemu is also skilled in numerous computational tools 💻. His professional mission is to uplift future scientists and expand our understanding of atmospheric phenomena 🌍. He also plays leadership roles in faculty and national associations 🏛️.

Professional Profile:

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🎓 Education & Experience 

📘 Education

  • 🎓 PhD in Atmospheric Physics – Bahir Dar University (2019–2025)

  • 🧑‍🔬 MSc in Physics (Atmospheric Physics) – Addis Ababa University (2009–2011)

  • 🧑‍🏫 BEd in Physics Education – Arba Minch University (2005–2008)

  • 🎒 Ethiopian Education Entrance Certificate – Arba Minch University (2003–2005)

  • 🏫 Secondary Education – Addis Zemen Secondary & Preparatory School (2001–2003)

👨‍🏫 Experience

  • 📍 Assistant Professor – Debre Tabor University (2015–Present)

  • 📍 Lecturer – Arba Minch University (2008–2015)

  • 📚 Teaches diverse undergraduate/postgraduate physics courses including Quantum Mechanics, Fluid Mechanics, and Environmental Physics

  • 👨‍🔧 Member and Chair of various university and faculty-level committees since 2011

📈 Professional Development 

Dr. Ambachew Abeje Alemu has consistently pursued professional growth through various training programs and certifications 🧑‍💼📜. He holds a Higher Diploma Programme in teaching methodology and has received training in SAS/SPSS, QGIS, ArcGIS, and basic computing 💾🖥️. His proficiency in programming languages like Python, R, C++, and MATLAB enhances his ability to engage in computational physics and environmental modeling 👨‍💻📊. He actively contributes to institutional quality, curriculum, and capacity-building committees 🏗️📘. Dr. Alemu is also a key member of national academic associations, helping uplift higher education standards in Ethiopia 🇪🇹✨.

🔬 Research Focus 

Dr. Alemu’s research focuses on atmospheric and environmental physics 🌬️🌍, particularly the spatio-temporal variability of aerosols using satellite data like MODIS 🛰️. His PhD work investigates air quality trends in East Africa, aiming to support environmental policy and health outcomes 📈🌱. Past studies include spectroscopic measurements of tropospheric gases like HCN and C2H6, and educational physics research 📘🔬. Dr. Alemu is deeply interested in using computational tools to analyze complex atmospheric systems, combining physics theory with data science 📊💡. His work contributes to climate science and education development in Ethiopia and beyond 🌦️📚.

🏅 Awards and Honors 

  • 🏆 President – Debre Tabor University Teachers Association

  • 🏅 Chairperson – Amhara Universities Teachers Associations

  • 🎖️ Certificate of Excellence in Higher Diploma Program – Arba Minch University

  • 🥇 Recognized Contributor – Space Science Forum, Amhara Universities (2016)

  • 📜 Published 3+ articles from PhD research (1 in progress)

Publication Top Notes

  1. Correlation of aerosol particles with clouds and radiation budget over the Horn of Africa–Ethiopia using MODIS satellite data: Part 02

    • Author: Ambachew Abeje Alemu

    • Journal: Journal of Quantitative Spectroscopy and Radiative Transfer

    • Publication Date: January 2025

    • DOI: 10.1016/j.jqsrt.2024.109261

    • Summary: This part of the study discusses the correlation between aerosol particles and various atmospheric parameters, including cloud properties and radiation budget over Ethiopia and the Horn of Africa, analyzed using MODIS satellite data.

  2. Temporal distributions of aerosols over the Horn of Africa–Ethiopia using MODIS satellite data: Part 01

    • Author: Ambachew Abeje Alemu

    • Journal: Journal of Quantitative Spectroscopy and Radiative Transfer

    • Publication Date: October 2024

    • DOI: 10.1016/j.jqsrt.2024.109085

    • Summary: This paper focuses on the temporal distribution patterns of aerosol particles in the Horn of Africa, with a particular emphasis on Ethiopia, using satellite observations from MODIS, and aims to understand the seasonal and geographical variations in aerosol concentrations.

  3. Effects of aerosol particles on precipitation and cloud parameters over East Africa-Ethiopia using MODIS satellite data: Part 01

    • Author: Ambachew Abeje Alemu

    • Journal: Ethiopian Journal of Science and Technology

    • Publication Date: May 21, 2024

    • Summary: This paper explores how aerosol particles impact precipitation patterns and cloud formation in Ethiopia and East Africa, with insights based on MODIS satellite data analysis. The research delves into how aerosol concentrations influence regional climate dynamics.

Conclusion

Dr. Ambachew Abeje Alemu demonstrates strong potential and impactful contributions in the fields of Atmospheric Physics and Environmental Science, specifically in climate and aerosol research using satellite data. His teaching excellence, technical competence, and research productivity, combined with a clear commitment to societal development, make him a highly suitable nominee for the Excellence in Research Award.

Dhanpat Sharma | Nuclear Physics | Best Researcher Award

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Dr. Dhanpat Sharma | Nuclear Physics| Best Researcher Award

Reserch Scholar at Central University of Haryana, India

Dhanpat Sharma 🎓, a passionate physicist from Haryana, India 🇮🇳, recently submitted his Ph.D. thesis in Physics at the Central University of Haryana 📚. His research focuses on the simulation of magnetic field generation during heavy ion collisions 💥, and the impact of low-intensity magnetic fields on environmental systems 🌱. Skilled in nanoparticle synthesis 🧪 and material integration 🔬, he bridges theoretical and experimental physics with ease. With academic roots from Delhi University 🏛️ and MDU Rohtak, Dhanpat is on a journey to contribute significantly to nuclear and environmental physics 🌍.

Professional Profile:

Orcid

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🔹 Education & Experience 

  • 🎓 Ph.D. (Physics) – Central University of Haryana (2019–2025)
    🧠 Thesis: Nuclear Flow, Nuclear Stopping, Magnetic Field & their Correlations

  • 📘 M.Sc. (Physics) – Maharishi Dayanand University, Rohtak (2016–2018)

  • 📗 B.Sc. (PCM) – Kirori Mal College, University of Delhi (2012–2016)

  • 🔬 Research Experience – Theoretical modeling & experimental work in magnetism, heavy ion collisions, and nanomaterials.

🔹 Professional Development 

Throughout his academic journey 📘, Dhanpat Sharma has developed a robust skill set in both theoretical physics 🧠 and experimental techniques 🔬. His Ph.D. work equipped him with simulation tools to explore nuclear matter behavior during heavy ion collisions 💥. On the experimental side, he explored the applications of low-intensity magnetic fields 🌌 in environmental setups 🌱. He has synthesized various nanoparticles 🧪 and studied their multifunctional integration with other materials. His interdisciplinary outlook, from nuclear physics to nanoscience, reflects his commitment to scientific growth 🚀 and collaborative innovation 🤝.

🔹 Research Focus Area 

Dhanpat Sharma’s research focus lies at the intersection of nuclear physics ⚛️ and magneto-environmental applications 🌍. He investigates the generation and role of magnetic fields in heavy ion collisions 💥 using theoretical simulation frameworks. Additionally, he has a hands-on background in applying low-intensity magnetic fields in experimental setups related to environmental science 🌿. His material science expertise includes synthesizing nanoparticles 🧪 and integrating them into multi-material systems 🔗. This dual approach, bridging fundamental particle interactions and real-world environmental impacts, defines his unique research identity 🔬.

🔹 Awards and Honors 

  • 🏅 Ph.D. Research Fellowship – Central University of Haryana

  • 🎖️ Merit-based Selection – M.Sc. Physics at MDU, Rohtak

  • 🏆 Consistent Academic Performer – B.Sc. at Kirori Mal College, Delhi University

Publication Top Notes

1. Magnetic field and dissolved oxygen assisted ultra-high photocatalytic activity of α-γ-Fe₂O₃ heterophase wrapped with rGO sheets for the removal of rifampicin

Journal: Applied Materials Today
Publication Date: June 2025
DOI: 10.1016/j.apmt.2025.102706
Highlights:

  • Focus on environmental remediation.

  • Enhanced photocatalysis using α-γ-Fe₂O₃/rGO.

  • Magnetic field and dissolved O₂ boost efficiency for antibiotic degradation.

2. Waste toner derived Fe₃O₄ nanoparticles embedment into PANI matrix as an advanced electrode for supercapacitor

Journal: Physica Scripta
Publication Date: April 2, 2025
DOI: 10.1088/1402-4896/adc844
Author: Dhanpat Sharma
Highlights:

  • Recycling waste toner to synthesize Fe₃O₄ NPs.

  • Polyaniline (PANI) matrix improves electrochemical performance.

  • Potential application in high-performance supercapacitors.

3. Probing the contribution of various mass fragments in the production of magnetic field during heavy ion collisions

Journal: Nuclear Physics A
Publication Date: March 2025
DOI: 10.1016/j.nuclphysa.2024.123005
Author: Dhanpat Sharma
Highlights:

  • Theoretical investigation of magnetic field generation in heavy-ion collisions.

  • Role of mass fragments in field strength and dynamics.

4. Influence of symmetry energy on electromagnetic field during heavy-ion collisions

Journal: Pramana – Journal of Physics
Publication Date: December 13, 2024
DOI: 10.1007/s12043-024-02860-w
Author: Dhanpat Sharma
Highlights:

  • Analysis of the symmetry energy term in nuclear matter.

  • Effects on electromagnetic field during nuclear collisions.

5. Correlation between magnetic field and nuclear stopping in different rapidity segments during heavy ion collisions

Journal: Journal of Physics G: Nuclear and Particle Physics
Publication Date: May 1, 2024
DOI: 10.1088/1361-6471/ad2e33
Author: Dhanpat Sharma
Highlights:

  • Study of nuclear stopping and magnetic field correlation.

  • Insights into rapidity-dependent nuclear dynamics.

Conclusion

Dhanpat Sharma’s interdisciplinary research combining nuclear physics, simulation techniques, magnetic field studies, and nanotechnology positions him as an emerging and promising researcher. His dual focus on fundamental physics and real-world applications is highly commendable.

 

Mr. Qing Li | Precision measurement | Best Researcher Award

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Mr. Qing Li | Precision measurement | Best Researcher Award

Professor at Huazhong University of Science and Technology, China

Qing Li (李青), born in 1984 👨‍🎓, is a professor and doctoral supervisor at the School of Physics, Huazhong University of Science and Technology 🏫. As a rising star in precision measurement and gravitational physics 🌌, he has earned prestigious recognition including the National “Chang Jiang Scholars Program” 🌟 and Hubei’s “Young Top-Notch Talent” award 🏅. His groundbreaking work includes one of the most precise measurements of the gravitational constant G (Nature, 2018) 📏 and pioneering systems for gravitational wave detection 🌠. He leads national research projects and continues to push boundaries in physics through innovative experiments and theoretical breakthroughs 🔬.

Professional Profile:

Orcid

Scopus

Google Scholar

📘 Education & Experience 

  • 🎓 Ph.D. in Physics – Huazhong University of Science and Technology

  • 🎓 Bachelor’s Degree – Likely in Physics (Institution not specified)

  • 🧑‍🏫 Professor – School of Physics, Huazhong University of Science and Technology

  • 🧑‍🔬 Doctoral Supervisor – Mentoring Ph.D. candidates in precision measurement

  • 🌐 Project Leader – Leads R&D programs under China’s Ministry of Science & Technology

  • 🔬 Researcher – Specializes in gravity experiments and fundamental physics

  • 📈 Innovator – Developed a complex pendulum thrust test system for space missions

🚀 Professional Development 

Prof. Qing Li has steadily advanced through China’s premier talent programs 🏆, being recognized as a Chang Jiang Young Scholar and a Top-Notch Young Talent in Hubei 🌟. He has taken the lead on several national and ministerial-level projects, including key R&D initiatives and NSF-funded studies 📊. His professional journey reflects a blend of experimental innovation and theoretical insight 🔍, especially in gravitational physics, where he has collaborated on internationally visible research. From building ultra-sensitive thrust test systems to advancing G measurement precision 📏, his work contributes directly to space exploration and fundamental constants of physics 🌌.

🧪 Research Focus 

Prof. Qing Li’s research centers around precision measurement physics and gravitational experiments 🌍. He focuses on quantifying gravitational interactions with exceptional accuracy using pendulum-based techniques 🎛️. His renowned work in measuring the gravitational constant G (Nature, 2018) with just 11.6 ppm uncertainty has set a global benchmark 📉. His research extends to gravitational wave detection, where he developed a micro-thrust test system with a 0.09 μN resolution 🚀. He also contributed to gravitational field traceability systems with 0.2 μGal resolution, reinforcing standards for gravity measurements 🌐. His work bridges laboratory physics and space mission technology 🌠.

🏅 Awards and Honors 

  • 🏆 Chang Jiang Scholars Program (Young Scholar) – Ministry of Education, China

  • 🏅 Hubei Province “Young Top-Notch Talent Cultivation Program”

  • 📖 Published in Nature (2018) – Among the most precise measurements of G

  • 📡 Leader of National Key R&D Projects – Ministry of Science and Technology

  • 📊 Recipient of NSFC Youth and General Program Grants – National Natural Science Foundation of China

Publication Top Notes

1. Atomically Dispersed Fe-N<sub>x</sub>/C Electrocatalyst Boosts Oxygen Catalysis via a New Metal-Organic Polymer Supramolecule Strategy

  • Authors: Zhengpei Miao, Xiaoming Wang, Meng−Che Tsai, Shaojun Guo, Qing Li, et al.

  • Journal: Advanced Energy Materials

  • Year: 2018

  • Citations: 229

  • DOI: 10.1002/aenm.201703030

  • Highlights:

    • Developed a metal-organic polymer (MOP) supramolecule strategy for catalyst design.

    • Created an atomically dispersed Fe-N<sub>x</sub>/C electrocatalyst with exceptional ORR/OER performance.

    • Demonstrated enhanced oxygen catalysis due to tailored local coordination environments.

2. Hierarchical Cu-Doped SnSe Nanoclusters as High-Performance Anode for Sodium-Ion Batteries

  • Authors: Rusong Chen, Shenzhou Li, Jianyun Liu, Tanyuan Wang, Qing Li, et al.

  • Journal: Electrochimica Acta

  • Year: 2018

  • Citations: 54

  • DOI: 10.1016/j.electacta.2018.07.092

  • Highlights:

    • Synthesized hierarchical Cu-doped SnSe nanoclusters.

    • Demonstrated high specific capacity and cycle stability as anodes for sodium-ion batteries.

    • Structural design promotes fast Na<sup>+</sup> diffusion and electronic conductivity.

3. Facile Synthesis of Bimodal Porous Graphitic Carbon Nitride Nanosheets as Efficient Photocatalysts for Hydrogen Evolution

  • Authors: Pei Hu, Chaoji Chen, Rui Zeng, Qing Li, Yunhui Huang, et al.

  • Journal: Nano Energy

  • Year: 2018

  • Citations: 61

  • DOI: 10.1016/j.nanoen.2018.06.048

  • Highlights:

    • Developed bimodal porous g-C<sub>3</sub>N<sub>4</sub> nanosheets with improved visible-light absorption.

    • Achieved enhanced hydrogen evolution reaction (HER) efficiency.

    • The dual porosity improves mass transport and surface area.

4. Cu-Based Nanocatalysts for Electrochemical Reduction of CO₂ (Review Article)

  • Authors: Huan Xie, Tanyuan Wang, Jiashun Liang, Qing Li, Shouheng Sun

  • Journal: Nano Today (likely based on topic and citation)

  • Year: 2018

  • Citations: 444

  • DOI: 10.1016/j.nantod.2018.04.009

  • Highlights:

    • Reviewed recent advances in Cu-based catalysts for CO₂ electroreduction.

    • Discussed design strategies, reaction mechanisms, and structure-activity relationships.

    • Served as a key reference in the field of CO₂ utilization and catalysis.

5. NiFe (Oxy)Hydroxides Derived from NiFe Disulfides as an Efficient Oxygen Evolution Catalyst for Rechargeable Zn–Air Batteries: The Effect of Surface S Residues

  • Authors: Tanyuan Wang, Gyutae Nam, Yue Jin, Qing Li, Jaephil Cho, et al.

  • Journal: Advanced Materials

  • Year: 2018

  • Citations: 278

  • DOI: 10.1002/adma.201803470

  • Highlights:

    • Converted NiFe disulfides into NiFe (oxy)hydroxides for oxygen evolution reaction (OER).

    • Investigated how surface sulfur residues enhance catalytic activity.

    • Applied in rechargeable Zn–air batteries, showing excellent charge-discharge performance.

Conclusion

Prof. Qing Li is a clear and compelling candidate for the Best Researcher Award. His breakthrough contributions to gravity research, space instrumentation, and precision metrology not only push the boundaries of fundamental physics but also have strategic implications for space exploration and national scientific capabilities. His high-impact publication in Nature and recognition by national talent programs further affirm his academic excellence and leadership.

Ali Darvish Falehi | Engineering | Excellence in Researcher Award

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Assoc. Prof. Dr. Ali Darvish Falehi | Engineering | Excellence in Researcher Award

Dr. Darvish Falehi at Islamic Azad University, Iran

Ali Darvish Falehi is a distinguished academic and professional in the field of Electrical Power Engineering. With a Ph.D. and Post-Ph.D. from Shahid Beheshti University, he ranks among the world’s top 2% scientists as listed by Stanford University in 2020. He is currently an Assistant Professor at Iran Islamic Azad University, a technical expert at Iran North Drilling Company, and the Chairman of the R&D Board at HICOBI Company. He has delivered keynote speeches at several international conferences and holds numerous patents. His contributions extend to supervising over 50 theses and reviewing for prestigious journals. 🌟🔬📚

Professional Profile:

Google Scholar

Education and Experience:

  • Post-Ph.D. & Ph.D. in Electrical Power Engineering, Shahid Beheshti University (First Class Honors) 🎓

  • Ranked among the world’s top 2% scientists by Stanford University in 2020 🌍

  • Chairman of R&D Board at HICOBI Company 🏢

  • Assistant Professor at Iran Islamic Azad University 👨‍🏫

  • Technical Expert at Iran North Drilling Company ⚙️

  • Main Speaker at national and international conferences 🎤

  • Reviewer for prestigious journals (IEEE, Elsevier, Springer) 📖

  • Supervisor & Adviser for 50+ M.Sc. and Ph.D. theses 📝

  • TOEFL-PBT score: 630 (Writing Score: 6) 🏆

  • Patents and medals at invention festivals in Iran, South Korea, and Romania 🏅

Professional Development: 

Ali Darvish Falehi has continuously developed his professional expertise by participating in global conferences and providing thought leadership as a main speaker and reviewer for high-impact journals such as IEEE and Elsevier. His dedication to research has led him to supervise over 50 graduate and doctoral theses, contributing to the academic growth of the next generation of engineers. He is also deeply involved in the industrial sector, where he serves as a technical expert for Iran North Drilling Company and leads the R&D board at HICOBI Company, driving innovation and technology forward. His work bridges academia and industry, enhancing both fields. 🔧🌐📊

Research Focus:

Ali Darvish Falehi’s research is centered around Electrical Power Engineering, with particular attention to energy systems, power distribution, and renewable energy solutions. His work aims to optimize power engineering technologies, focusing on improving energy efficiency and sustainability. He is known for his contributions to the development of advanced electrical systems and has been actively involved in creating patented innovations. His expertise in power engineering is complemented by his role as a technical expert, where he advises on industrial applications of electrical power systems. His research seeks to solve complex energy challenges, aligning with global sustainability goals. ⚡🌱🔋

Awards and Honors:

  • Ranked among the world’s top 2% scientists by Stanford University (2020) 🌍

  • Chairman of the R&D Board at HICOBI Company 🏢

  • Main Speaker at several international conferences 🎤

  • Reviewer for leading ISI journals like IEEE, Elsevier, Springer 📚

  • Supervisor & Adviser for 50+ M.Sc. and Ph.D. theses 📝

  • TOEFL-PBT Score: 630 🏆

  • Patents and medals from invention festivals in Iran, South Korea, and Romania 🏅

Publication Top Notes

  1. “An innovative optimal RPO-FOSMC based on multi-objective grasshopper optimization algorithm for DFIG-based wind turbine to augment MPPT and FRT capabilities” (2020)

    • Authors: A.D. Falehi

    • Journal: Chaos, Solitons & Fractals

    • Summary: This paper proposes an innovative control strategy using a multi-objective Grasshopper Optimization Algorithm (GOA) to enhance the MPPT and Fault Ride Through (FRT) capabilities of DFIG-based wind turbines. The use of Fractional-Order Sliding Mode Control (FOSMC) is central to this work.

  2. “Promoted supercapacitor control scheme based on robust fractional-order super-twisting sliding mode control for dynamic voltage restorer to enhance FRT and PQ capabilities of DFIG-based wind turbines” (2021)

    • Authors: A.D. Falehi, H. Torkaman

    • Journal: Journal of Energy Storage

    • Summary: This paper focuses on enhancing the FRT and Power Quality (PQ) capabilities of DFIG-based wind turbines. The authors propose a robust fractional-order control scheme for supercapacitors integrated with a Dynamic Voltage Restorer (DVR).

  3. “LVRT/HVRT capability enhancement of DFIG wind turbine using optimal design and control of novel PIλDμ-AMLI based DVR” (2018)

    • Authors: A.D. Falehi, M. Rafiee

    • Journal: Sustainable Energy, Grids and Networks

    • Summary: This work aims to enhance the Low Voltage Ride Through (LVRT) and High Voltage Ride Through (HVRT) capabilities of DFIG wind turbines by optimizing the design and control of a novel DVR based on a PIλDμ-AMLI (Proportional-Integral-Derivative) controller.

  4. “Enhancement of DFIG-wind turbine’s LVRT capability using novel DVR based odd-nary cascaded asymmetric multi-level inverter” (2017)

    • Authors: A.D. Falehi, M. Rafiee

    • Journal: Engineering Science and Technology, an International Journal

    • Summary: This paper explores improving the LVRT capability of DFIG wind turbines by integrating a novel Dynamic Voltage Restorer (DVR) system with an odd-nary cascaded asymmetric multi-level inverter.

  5. “Neoteric HANFISC–SSSC based on MOPSO technique aimed at oscillation suppression of interconnected multi-source power systems” (2016)

    • Authors: A.D. Falehi, A. Mosallanejad

    • Journal: IET Generation, Transmission & Distribution

    • Summary: This paper addresses the oscillation suppression in interconnected multi-source power systems using a Hybrid Active Networked Flexible Integrated Supply Chain (HANFISC)-Static Synchronous Series Compensator (SSSC) controlled by the Multi-Objective Particle Swarm Optimization (MOPSO) technique.

Conclusion:

Ali Darvish Falehi is undoubtedly a deserving candidate for the Excellence in Researcher Award. His combination of academic excellence, significant contributions to electrical power engineering, leadership in both academia and industry, and his global recognition positions him as a standout figure in his field. His ability to balance research with innovation, along with his dedication to mentoring future researchers, makes him an exemplary choice for this prestigious award.

Huawen Liu | Machine Learning | Distinguished Scientist Award

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Prof. Dr. Huawen Liu | Machine Learning | Distinguished Scientist Award

Professor at Shaoxing University, China

Prof. Huawen Liu 👨‍🏫, a distinguished academic at Shaoxing University 🇨🇳 since 2010, holds a Ph.D. and Ms.D. in Computer Science from Jilin University 🧠💻. He expanded his research globally as a postdoc at the University of South Australia 🇦🇺 (2012–2013) and a visiting fellow at the University of Texas at San Antonio 🇺🇸 (2018–2019). His work spans hash learning, AI, big data, and machine learning 🤖📊. With over 50 publications 📚 in top-tier journals, he actively contributes as an editor and conference organizer. He holds an H-index of 17 📈 and continues to shape intelligent computing worldwide 🌐.

Professional Profile:

Google Scholar

Scopus

🎓 Education & Experience 

  • 🎓 Ph.D. & Ms.D. in Computer Science from Jilin University, China 🇨🇳 (Top-10 university)

  • 🧑‍🔬 Postdoctoral Researcher at University of South Australia 🇦🇺 (2012–2013)

  • 🌍 Visiting Fellow at University of Texas at San Antonio, USA 🇺🇸 (2018–2019)

  • 👨‍🏫 Professor at Shaoxing University since July 2010 🏫

  • 📝 Over 50 peer-reviewed publications in high-impact journals and conferences 📚

🌱 Professional Development 

Prof. Liu has actively participated in shaping the research community 🌐. He serves as the Editor-in-Chief (EIC) of the International Journal of Intelligence and Sustainable Computing 🧠💡, Associate Editor for International Journal of Artificial Intelligence and Tools 🛠️, and Editor for Mathematics ➗📘. He has also led special issues as Guest Editor in Neural Computing and Applications 🧮 and Computing and Informatics 💻. His involvement extends to organizing national and international conferences 🎤📅 and acting as a program committee member for IJCAI, AAAI, CVPR, and others 🤝📊, reflecting his strong engagement with the global AI and computing community.

🔍 Research Focus Category 

Prof. Liu’s research lies at the intersection of artificial intelligence 🤖, machine learning 📚, and data science 📊. He specializes in hash learning, outlier detection, feature selection, and multimedia systems 🎥. His focus extends to practical applications in big data analytics 🗃️ and intelligent systems 💡. With a keen interest in mining patterns from complex datasets, his work contributes significantly to pattern recognition 🧠 and cybernetics 🛡️. He aims to bridge theory and real-world implementation through intelligent algorithms that enhance automated decision-making systems 🧮. His interdisciplinary approach empowers robust AI models with scalable and sustainable solutions 🌍.

🏆 Awards & Honors 

  • 📈 H-index of 17 according to Google Scholar 🧠

  • 📝 Over 50 publications in leading journals such as IEEE TKDE, TNNLS, TMM, TSMC, and more 📚

  • 🧑‍💼 Editor-in-Chief, Int. J. of Intelligence and Sustainable Computing

  • 🛠️ Associate Editor, Int. J. of Artificial Intelligence and Tools

  • ➗ Editor, Mathematics

  • 🧮 Lead Guest Editor for Neural Computing and Applications (NCAA)

  • 💻 Lead Guest Editor for Computing and Informatics (CAI)

  • 🎤 Organising Chair for 2015 National Conf. of Theoretical Computer Science

  • 📊 Organising Chair for 2014 China Conference on Data Mining

  • 🎓 Program Committee Member for top AI conferences: IJCAI, AAAI, CVPR, ADMA, ICBK, KSEM

Publication Top Notes

🔍 1. Outlier Detection Using Local Density and Global Structure

  • Authors: H. Liu, Huawen; S. Zhang, Shichao; Z. Wu, Zongda; X. Li, Xuelong

  • Journal: Pattern Recognition, 2025

  • Citations: 7

  • Summary: This article proposes a novel outlier detection method combining local density estimation with global structural features. It’s likely useful for anomaly detection in high-dimensional or graph-structured data.

🧠 2. Select Your Own Counterparts: Self-Supervised Graph Contrastive Learning With Positive Sampling

  • Authors: Z. Wang, Zehong; D. Yu, Donghua; S. Shen, Shigen; S. Yao, Shuang; M. Guo, Maozu

  • Journal: IEEE Transactions on Neural Networks and Learning Systems, 2025

  • Citations: 2

  • Summary: Focuses on self-supervised learning with graph contrastive methods, improving representation learning by selecting reliable positive samples for contrastive training.

🗣️ 3. Amharic Spoken Digits Recognition Using Convolutional Neural Network

  • Authors: T.A. Ayall, Tewodros Alemu; C. Zhou, Chuangjun; H. Liu, Huawen; S.T. Abate, Solomon Teferra; M. Adjeisah, Michael

  • Journal: Journal of Big Data, 2024 (Open Access)

  • Citations: 3

  • Summary: Presents a CNN-based model for recognizing spoken digits in Amharic, an under-resourced African language — showcasing multilingual AI applications.

🧠 4. An Improved Deep Hashing Model for Image Retrieval With Binary Code Similarities

  • Authors: H. Liu, Huawen; Z. Wu, Zongda; M. Yin, Minghao; X. Zhu, Xinzhong; J. Lou, Jungang

  • Access: Open Access

  • Citations: 0

  • Summary: Describes a deep hashing method that optimizes binary similarity in hash code space for more effective image retrieval.

🧠 5. LGAD: Local and Global Attention Distillation for Efficient Semantic Segmentation

  • Authors: C. Wang, Chen; Y. Qi, Yafei; Q. Li, Qi; H. Liu, Huawen

  • Type: Conference Paper (Open Access)

  • Citations: 1

  • Summary: Proposes an attention distillation method combining local and global context for lightweight semantic segmentation, improving performance while keeping models efficient.

Conclusion:

Dr. Huawen Liu’s exceptional research contributions, leadership in academic organizations, and active engagement in the scientific community make him a strong candidate for the Distinguished Scientist Award. His sustained impact on the field of machine learning and AI, along with his contributions to both theoretical and applied research, exemplify the qualities deserving of such an esteemed recognition.

Mingjun Xiang | Terahertz | Best Researcher Award

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Mrs. Mingjun Xiang | Terahertz | Best Researcher Award

PhD student at Frankfurt Institute for Advanced Studies, Germany

Mingjun Xiang 📡 is a passionate researcher in terahertz imaging and deep learning, currently based at the Frankfurt Institute for Advanced Studies 🇩🇪. With a strong academic background in Information and Communication Engineering and hands-on experience in optical systems, Mingjun bridges theoretical innovation with practical applications. He’s contributed to multiple international conferences 🎤 and has worked on advanced topics like phase retrieval, depth reconstruction, and semi-supervised learning. Fluent in English 🇬🇧 and Mandarin 🇨🇳, he brings a global perspective to his research. In his spare time, he enjoys swimming 🏊, playing traditional Chinese instruments 🎶, and photography 📷.

Professional Profile:

Orcid

Scopus

🔹 Education & Experience 

🎓 Education:

  • 📘 Ph.D. in AI for Terahertz Imaging – Frankfurt Institute for Advanced Studies (2021–Present), Germany

  • 📗 M.Sc. in Information and Communication Engineering – Technische Universität Darmstadt (2017–2020), Germany

  • 📙 B.Sc. in Electronics Information Science and Technology – Harbin Institute of Technology (2013–2017), China

💼 Work Experience:

  • 🔧 Electronic Engineer Intern – Inspur Group (2016): Worked on fiber coupling modules using VirtualLab

  • 📡 Communication Engineer Intern – China Mobile (2018): Developed optical fault location system with LabView & Matlab

  • 🧪 Research Assistant – TU Darmstadt (2019): Developed GUI for Zurich Instruments’ devices in Matlab

  • 🧫 Microfabrication Projects – Cleanroom experience in antenna design & THz waveguide fabrication

🔹 Professional Development 

Mingjun Xiang is deeply committed to continuous learning and professional growth 📘. During his academic journey, he has mastered a diverse set of tools including Python 🐍, Matlab 📊, LabView ⚙️, and CST Microwave Studio 📡, along with cleanroom fabrication skills 🧼. He has presented in renowned global conferences such as IRMMW-THz 🌍 and Digital Holography & 3D Imaging 📸, often as a keynote or session speaker 🎙️. His hands-on engineering internships in China gave him practical insights into fiber optics and telecom systems 🔌. By combining advanced theory with real-world skills, he actively advances in the terahertz research community 🚀.

🔹 Research Focus Category 

Mingjun Xiang’s research focuses on AI-enhanced Terahertz Imaging 📶, where he applies deep learning techniques to overcome challenges in phase retrieval, image denoising, and occluded object reconstruction 🧠. His work integrates physics-informed neural networks 🧬 with holographic data for superior image accuracy and depth perception 🧊. His current interest lies in using both supervised and unsupervised models to extract meaningful features from complex terahertz datasets 📂. This intersection of optics 🔍, machine learning 🤖, and microwave technology 📡 positions him at the forefront of the next-generation imaging systems for biomedical, industrial, and security applications 🔬🛡️.

🔹 Awards & Honors 

  • 🏅 Keynote Speaker – IRMMW-THz 2023, Canada

  • 🗣️ Invited Speaker – IRMMW-THz 2022, Netherlands

  • 🧠 Speaker – Digital Holography & 3D Imaging 2022, UK

  • 📢 Speaker – Face2Phase 2022, Netherlands

  • 🖼️ Poster Presenter – 10th Intl. Workshop on THz Tech & Applications, Germany

  • 🥇 Master Thesis Achievement – Achieved -5 dB coupling loss in 0.67–1.37 THz range

Publication Top Notes

1. Amplitude/Phase Retrieval for Terahertz Holography With Supervised and Unsupervised Physics-Informed Deep Learning

  • Journal: IEEE Transactions on Terahertz Science and Technology

  • Publication Date: March 2024

  • DOI: 10.1109/TTHZ.2024.3349482

  • Type: Journal Article

  • Summary:
    Combines supervised and unsupervised physics-informed deep learning (PIDL) methods for amplitude and phase retrieval in THz holography, enhancing accuracy and generalization without requiring a reference beam.

2. Depth Reconstruction for Reference-Free THz Holography Based on Physics-Informed Deep Learning

  • Conference: 48th International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz)

  • Date: September 17, 2023

  • DOI: 10.1109/irmmw-thz57677.2023.10298937

  • Type: Conference Paper

  • Summary:
    Proposes a PIDL-based method for depth reconstruction in reference-free THz holography. Demonstrates the capability of neural networks to learn physical laws and produce 3D profiles from 2D holograms.

3. Phase Retrieval for Fourier THz Imaging with Physics-Informed Deep Learning

  • Conference: 47th IRMMW-THz

  • Date: August 28, 2022

  • DOI: 10.1109/irmmw-thz50927.2022.9895691

  • Type: Conference Paper

  • Summary:
    Applies PIDL to Fourier domain imaging in the THz range, aiming at robust phase retrieval by embedding physical constraints in the training loss.

4. Phase Retrieval for Terahertz Holography with Physics-Informed Deep Learning

  • Conference: Digital Holography and 3-D Imaging 2022 (OSA)

  • Date: 2022

  • DOI: 10.1364/dh.2022.tu4a.4

  • Type: Conference Paper

  • Summary:
    Earlier work demonstrating PIDL for phase retrieval in THz holography setups, potentially eliminating the need for phase-shifting or interferometric measurements.

5. Broadband Terahertz Photonic Integrated Circuit with Integrated Active Photonic Devices

  • Journal: Photonics

  • Publication Date: November 3, 2021

  • DOI: 10.3390/photonics8110492

  • Type: Journal Article

  • Summary:
    Focuses on the development of a broadband THz photonic integrated circuit (PIC) with embedded active photonic components, marking progress toward compact, tunable THz systems.

Conclusion: 

Mingjun xiang is a highly suitable and deserving nominee for the Best Researcher Award, particularly in areas that value cross-disciplinary innovation, high-frequency imaging, and AI integration in physical sciences.

His work advances both theoretical frameworks and practical implementations of next-generation THz systems, showcasing real-world applications and scientific impact. His combination of technical rigor, innovation, international presence, and AI-driven breakthroughs clearly sets him apart as a next-generation leader in his field.