Mir-Hamza Khan | Engineering | Best Researcher Award

Best Researcher Award

            Mir-Hamza Khan
Affiliation University of Warwick
Country United Kingdom
Scopus ID 57193652368
Documents 7
Citations 132 (Citations by 124 documents)
h-index 4
Subject Area Engineering
Event International Popular Scientist Awards

Mir-Hamza Khan
University of Warwick

The Best Researcher Award recognizes sustained scholarly achievement, measurable research impact, and meaningful contributions to scientific advancement. Mir-Hamza Khan, affiliated with the University of Warwick, has established a growing research profile within the field of Engineering through peer-reviewed publications, scholarly collaborations, and citation impact. The available bibliometric indicators demonstrate active engagement in engineering research and support consideration for academic recognition within international award programs.[1]

Abstract

This article presents an academic overview of Mir-Hamza Khan’s research profile for consideration under the Best Researcher Award. The assessment is based on publicly available scholarly indicators including Scopus-indexed publications, citation performance, h-index, institutional affiliation, and engineering research activities. Such indicators provide an objective foundation for evaluating research productivity, scholarly influence, and ongoing scientific engagement.[1]

Keywords

Best Researcher Award; Mir-Hamza Khan; Engineering; University of Warwick; Scientific Research; Scholarly Publications; Citation Impact; Academic Recognition; Scopus Author; International Popular Scientist Awards.

Introduction

Engineering research contributes substantially to technological progress, industrial innovation, and evidence-based problem solving. Academic recognition programs acknowledge researchers who demonstrate consistent scholarly output, collaborative engagement, and measurable research influence. Bibliometric indicators such as publication count, citation metrics, and h-index are widely used to complement qualitative peer assessment during research evaluation.[2]

Research Profile

Mir-Hamza Khan is affiliated with the University of Warwick in the United Kingdom. According to the supplied Scopus profile information, the researcher has authored seven indexed documents that have collectively received 132 citations from 124 citing documents and achieved an h-index of 4. These metrics indicate an active scholarly presence and growing influence within engineering research.[1]

Research Contributions

  • Development of peer-reviewed engineering research.
  • Contribution to internationally indexed scientific publications.
  • Participation in collaborative academic research initiatives.
  • Generation of research outputs referenced by the wider scientific community.
  • Support for innovation through engineering-based scientific investigation.

Publications

The available Scopus profile records seven indexed scholarly publications. These works collectively contribute to the engineering literature and demonstrate continued research activity. Publication quality, citation frequency, and collaborative dissemination remain important indicators for evaluating research excellence.[1]

  • Peer-reviewed engineering journal articles.
  • Internationally indexed scientific publications.
  • Research works accessible through scholarly databases.

Research Impact

Research impact is reflected through scholarly visibility, citations, and continued utilization of published findings by other researchers. Citation activity together with an established h-index demonstrates that the research has contributed to ongoing academic discussions within the engineering community. Such indicators are commonly incorporated into institutional and international research evaluations.[2]

Award Suitability

Based on the available bibliometric information, Mir-Hamza Khan demonstrates characteristics frequently considered during research award evaluations, including peer-reviewed publication activity, measurable citation performance, institutional affiliation with a recognized university, and continued engagement in engineering research. Final award decisions would normally include additional peer review, research significance, innovation, academic service, and broader societal impact.[1]

Conclusion

Mir-Hamza Khan’s academic profile reflects continued participation in engineering research supported by peer-reviewed publications, measurable citation performance, and institutional research engagement. These scholarly indicators provide an objective basis for consideration within the Best Researcher Award while emphasizing the importance of continued research excellence, innovation, and scientific contribution.[2]

References

  1. Elsevier. (n.d.). Scopus author details: Mir-Hamza Khan, Author ID 57193652368. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57193652368
  2. Research Policy. (2010). Bibliometric indicators and research evaluation.
    https://doi.org/10.1016/j.respol.2010.09.018

Xiaoying Liu | Engineering | Best Researcher Award

Best Researcher Award

                 Xiaoying Liu
Affiliation Karlsruhe Institute of Technology
Country Germany
Scopus ID 56148583100
Documents 10
Citation 63 citations by 59 documents
h-index 4
Subject Area Engineering
Event International Popular Scientist Awards
ORCID 0000-0003-4552-3967

Xiaoying Liu

Karlsruhe Institute of Technology, Germany

Xiaoying Liu  the Best Researcher Award recognizes researchers whose scholarly activities demonstrate sustained scientific contribution, professional integrity, and measurable academic impact. Xiaoying Liu, affiliated with Karlsruhe Institute of Technology, has established a documented research profile in engineering supported by indexed scholarly publications, citation performance, and international visibility. The academic profile summarized below provides a neutral overview of research achievements and professional qualifications relevant to consideration for academic recognition.[1]

Abstract

This article presents an academic overview of Xiaoying Liu in relation to eligibility for the Best Researcher Award. The summary considers institutional affiliation, publication activity, citation metrics, engineering research specialization, and scholarly visibility based on publicly indexed academic information. The purpose is to provide a structured and objective profile using a format consistent with encyclopedic academic documentation.[1]

Keywords

Best Researcher Award, Xiaoying Liu, Karlsruhe Institute of Technology, Engineering Research, Scopus Author, Scientific Publications, Citation Analysis, Academic Recognition, Research Excellence, International Popular Scientist Awards.

Introduction

Engineering research contributes substantially to technological advancement through innovation, experimentation, and interdisciplinary collaboration. Researchers working within this discipline are evaluated using scholarly publications, citation metrics, institutional engagement, and scientific contributions. Xiaoying Liu’s research profile reflects participation in internationally indexed research activities documented through recognized bibliographic databases.[1]

Research Profile

  • Researcher: Xiaoying Liu
  • Institution: Karlsruhe Institute of Technology
  • Country: Germany
  • Primary Subject Area: Engineering
  • Scopus Indexed Documents: 10
  • Total Citations: 63
  • h-index: 4
  • Scopus Author ID: 56148583100

Research Contributions

The available publication record indicates scholarly contributions within engineering, demonstrating participation in peer-reviewed scientific communication. Indexed publications and associated citation performance indicate that the research has been referenced by subsequent scholarly work, reflecting measurable academic engagement. Citation metrics alone do not fully determine scientific quality but provide one quantitative indicator of research visibility.[1]

  • Peer-reviewed engineering publications.
  • International research dissemination.
  • Documented citation impact.
  • Contribution to scientific knowledge through indexed literature.

Publications

The Scopus author profile lists ten indexed scholarly documents covering engineering-related research topics. These publications contribute to international scientific literature through peer-reviewed journals and conference proceedings where applicable. Numerous scholarly articles include Digital Object Identifiers (DOIs), providing persistent identification and reliable academic referencing.[1][2]

  • Indexed research articles.
  • Peer-reviewed engineering publications.
  • Articles assigned DOI identifiers where applicable.

Research Impact

Research influence may be evaluated through scholarly citations, publication consistency, institutional collaboration, and visibility within international indexing systems. Xiaoying Liu’s documented citation record of sixty-three citations across fifty-nine citing documents, together with an h-index of four, demonstrates measurable engagement with the broader research community while reflecting ongoing scholarly activity.[1]

Award Suitability

Based on publicly available scholarly indicators, Xiaoying Liu presents qualifications commonly considered during academic recognition processes. Relevant factors include an established institutional affiliation, peer-reviewed publications, indexed scholarly output, documented citation performance, and continued contribution to engineering research. Final award decisions remain subject to the official evaluation procedures, eligibility criteria, and peer-review standards established by the International Popular Scientist Awards committee.[3]

Conclusion

Xiaoying Liu maintains a documented academic profile supported by internationally indexed publications, measurable citation performance, and engineering research activities. The available evidence indicates continued participation in scholarly communication and scientific dissemination. This overview serves as a structured academic profile intended for informational and recognition purposes within a professional award framework.[1]

References

  1. Elsevier. (n.d.). Scopus author details: Xiaoying Liu, Author ID 56148583100. Scopus.https://www.scopus.com/authid/detail.uri?authorId=56148583100
  2. International DOI Foundation. (n.d.). Digital Object Identifier (DOI) Handbook.https://doi.org/
  3. International Popular Scientist Awards. (n.d.). Best Researcher Award Information.https://popularscientist.com/

You Zhang | Engineering | Best Researcher Award

Mr. You Zhang | Engineering | Best Researcher Award

University of Rochester, United States

Dr. You (Neil) Zhang is a Ph.D. candidate in Electrical and Computer Engineering at the University of Rochester, specializing in machine learning for speech, acoustics, and audio signal processing. His research focuses on spatial audio (HRTF personalization), speech anti-spoofing, singing voice deepfake detection, and audio-visual learning. He has held research roles at Dolby, Meta, Microsoft, Tencent, and Bytedance, contributing significantly to areas like perceptual HRTF modeling and audio-visual deepfake detection.

Profile:

🎓 Education:

  • Ph.D. in Electrical & Computer Engineering (Expected 2025)
    University of Rochester

  • M.S., University of Rochester

  • B.Eng., University of Electronic Science & Technology of China

  • Exchange Program, UC Berkeley

🧠 Research Interests:

  • Spatial Audio & HRTF Personalization 🎧

  • Speech Deepfake Detection & Audio Security 🔐

  • Multimodal Learning: Audio-Visual & Emotional Speech Synthesis 🎥🗣️

🏆 Honors & Fellowships:

  • IEEE SPS Scholarship (2024)

  • NIJ Graduate Research Fellowship (2023)

  • ICASSP Rising Star in Signal Processing (2023)

  • Open Scholarship Award @ UR (2025)

🧪 Research & Industry Experience:

  • Dolby Labs 🎶 – Sr. Researcher, Multimodal Spatial Audio

  • Meta Reality Labs 🧠 – HRTF Perceptual Learning

  • Microsoft, Tencent, ByteDance, IngenID 💼 – AI R&D Internships

  • Audio Information Research Lab, UR 🎙️ – Deepfake Detection, AV Speech, HRTF Neural Fields

📚 Selected Publications:

  • IEEE T-MM, SPL, ICASSP, Interspeech, NAACL

  • Co-organizer of SVDD Challenge at SLT 2024 & MIREX 2024

  • Contributor to Handbook of Biometric Anti-spoofing (Springer)

🎤 Talks & Tutorials:

  • Invited speaker at CMU, NII Japan, ISCA SPSC

  • Tutorials @ ASA, ICME, AES (Topics: HRTF, Deepfakes, ML for Acoustics)

🎓 Teaching & Mentorship:

  • TA for Machine Learning, Audio Signal Processing, Random Processes

  • Mentored 10+ undergrad and graduate students in UR, Tsinghua, UESTC

💼 Professional Service:

  • Reviewer for IEEE TASLP, TPAMI, ICASSP, Interspeech, CVPR Workshops

  • Member: IEEE, ASA, ACM, AES

  • DEI Committee @ UR ECE | Organizer of AR/VR Events

💻 Skills:

  • Programming: Python, MATLAB, C, Java

  • Tools: Git, Linux, PyTorch, Slurm

  • Languages: English 🇺🇸, Mandarin 🇨🇳

🏃 Hobbies & More:

  • Half-Marathon Finisher 🏅

  • Loves stand-up paddleboarding, travel, badminton 🌊✈️🏸

Google Scholar Citation Metrics:

  • Citations: 751 (All time) | 751 (Since 2020)

  • h-index: 12 (All time) | 12 (Since 2020)

  • i10-index: 14 (All time) | 14 (Since 2020)

Publication Top Notes:

  1. One-class Learning Towards Synthetic Voice Spoofing Detection
    Y. Zhang, F. Jiang, Z. Duan
    IEEE Signal Processing Letters, vol. 28, pp. 937–941, 2021.

  2. Speech Driven Talking Face Generation from a Single Image and an Emotion Condition
    S.E. Eskimez, Y. Zhang, Z. Duan
    IEEE Transactions on Multimedia, vol. 24, pp. 3480–3490, 2021.

  3. UR Channel-Robust Synthetic Speech Detection System for ASVspoof 2021
    X. Chen, Y. Zhang*, G. Zhu*, Z. Duan
    ASVspoof 2021 Workshop, 2021.

  4. SingFake: Singing Voice Deepfake Detection
    Y. Zang, Y. Zhang*, M. Heydari, Z. Duan
    IEEE ICASSP, 2024.

  5. An Empirical Study on Channel Effects for Synthetic Voice Spoofing Countermeasure Systems
    Y. Zhang, G. Zhu, F. Jiang, Z. Duan
    Interspeech, pp. 4309–4313, 2021.

  6. SAMO: Speaker Attractor Multi-Center One-Class Learning for Voice Anti-Spoofing
    S. Ding, Y. Zhang, Z. Duan
    IEEE ICASSP, 2023.

  7. A Probabilistic Fusion Framework for Spoofing Aware Speaker Verification
    Y. Zhang, G. Zhu, Z. Duan
    Odyssey: The Speaker and Language Recognition Workshop, pp. 77–84, 2022.

  8. Global HRTF Personalization Using Anthropometric Measures
    Y. Wang, Y. Zhang, Z. Duan, M. Bocko
    Audio Engineering Society (AES) 150th Convention, 2021.

  9. Rethinking Audio-Visual Synchronization for Active Speaker Detection
    A. Wuerkaixi, Y. Zhang, Z. Duan, C. Zhang
    IEEE MLSP, 2022.

  10. CtrSVDD: A Benchmark Dataset and Baseline Analysis for Controlled Singing Voice Deepfake Detection
    Y. Zang, J. Shi, Y. Zhang, et al.
    Interspeech, pp. 4783–4787, 2024.

  11. VERSA: A Versatile Evaluation Toolkit for Speech, Audio, and Music
    J. Shi, H. Shim, J. Tian, Y. Zhang, et al.
    NAACL (Demo Track), 2025.

  12. HRTF Field: Unifying Measured HRTF Magnitude Representation with Neural Fields
    Y. Zhang, Y. Wang, Z. Duan
    IEEE ICASSP, 2023.

  13. SVDD 2024: The Inaugural Singing Voice Deepfake Detection Challenge
    Y. Zhang, Y. Zang, J. Shi, R. Yamamoto, T. Toda, Z. Duan
    IEEE SLT, pp. 782–787, 2024.

  14. DyViSE: Dynamic Vision-Guided Speaker Embedding for Audio-Visual Speaker Diarization
    A. Wuerkaixi, K. Yan, Y. Zhang, Z. Duan, C. Zhang
    IEEE MMSP, 2022.

  15. Predicting Global Head-Related Transfer Functions from Scanned Head Geometry Using Deep Learning and Compact Representations
    Y. Wang, Y. Zhang, Z. Duan, M. Bocko
    arXiv preprint, arXiv:2207.14352, 2022.

  16. Learning Arousal-Valence Representation from Categorical Emotion Labels of Speech
    E. Zhou, Y. Zhang, Z. Duan
    IEEE ICASSP, 2024.

  17. SVDD Challenge 2024: A Singing Voice Deepfake Detection Challenge Evaluation Plan
    Y. Zhang, Y. Zang, J. Shi, et al.
    arXiv preprint, arXiv:2405.05244, 2024.

  18. ASVspoof 5: Design, Collection and Validation of Resources for Spoofing, Deepfake, and Adversarial Attack Detection Using Crowdsourced Speech
    X. Wang, H. Delgado, Y. Zhang, et al.
    Computer Speech & Language, 2025.

  19. Emotional Dimension Control in Language Model-Based Text-to-Speech: Spanning a Broad Spectrum of Human Emotions
    K. Zhou, Y. Zhang, S. Zhao, et al.
    arXiv preprint, arXiv:2409.16681, 2024.

  20. Mitigating Cross-Database Differences for Learning Unified HRTF Representation
    Y. Wen, Y. Zhang, Z. Duan
    IEEE WASPAA, 2023.