Prof. Xing Huang | Electronic Design Automation | Best Researcher Award

Prof. Xing Huang , Northwestern Polytechnical University , China.

Prof. Xing Huang  is a Full Professor and Ph.D. advisor at the School of Computer Science, Northwestern Polytechnical University, China 🇨🇳. A nationally recognized young talent 🌟 and a prestigious Humboldt Scholar 🇩🇪, he brings global research experience from Germany 🇩🇪, Hong Kong 🇭🇰, Taiwan 🇹🇼, and the USA 🇺🇸. His cutting-edge work spans electronic design automation, microfluidic biochips, VLSI circuits, and AI 🧠. With a strong track record of impactful publications 📚, Prof. Huang is shaping the future of computer-aided design and intelligent systems. He is committed to advancing interdisciplinary innovations for next-generation technologies 🚀.

Professional Profile

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Education & Experience 

🎓 Education:

• 🏛️ PhD in Intelligent Information Processing, Fuzhou University (2013–2018)

• 📚 Visiting PhD in Computer Science, Duke University, USA (2016–2017)

• 🎓 Bachelor’s in Computer Science and Technology, Fuzhou University (2009–2013)

💼 Experience:

• 👨‍🏫 Full Professor, Northwestern Polytechnical University (Dec 2022–Present)

• 🔬 Postdoc Fellow, The Chinese University of Hong Kong (Aug–Nov 2022)

• 🇩🇪 Humboldt & TUFF Postdoc Fellow, Technical University of Munich (2019–2022)

• 🌏 MOST Postdoc Fellow, National Tsing Hua University, Taiwan (2018–2019)

Summary Suitability

Professor.  Xing Huang , as Professor and doctoral supervisor at the School of Computer Science, Northwestern Polytechnical University, stands out as a highly deserving recipient of the Best Researcher Award. With a distinguished academic and research trajectory across globally renowned institutions, Professor Huang has made pioneering contributions in electronic design automation, microfluidic biochips, and intelligent information processing. His outstanding achievements, coupled with national and international recognition, affirm his suitability for this prestigious honor.

Professional Development 

Prof. Huang’s academic journey is a stellar model of international collaboration 🌐. He has participated in advanced research programs supported by prestigious fellowships including the Humboldt Fellowship 🇩🇪 and Taiwan’s MOST Fellowship 🇹🇼. His commitment to excellence is demonstrated by his extensive postdoctoral experience across Asia and Europe 🧪. Through consistent interdisciplinary work, he has mastered both the theoretical and practical dimensions of intelligent systems 🤖. He actively contributes to academic publishing, mentorship 👨‍🔬, and cross-cultural innovation exchange. Prof. Huang’s professional path highlights his vision for impactful research and global academic integration 🌍.

Research Focus 

Prof. Huang’s research is deeply rooted in electronic design automation 🧩 and computer-aided design of microfluidic biochips 💧 and VLSI circuits ⚙️. He innovates in AI and machine learning 🧠 for system optimization and control-logic synthesis, with particular emphasis on reinforcement learning and algorithmic intelligence 🧮. His work facilitates automation in biomedical and semiconductor domains, bridging hardware and AI in cutting-edge applications 🧬. His integrated approach extends from theory to implementation, ensuring real-world impact across computing, biotechnology, and IC design 🔬. With numerous top-tier publications, Prof. Huang is a leader in advancing smart, adaptive systems 🚀.

🔹 Awards & Honors 

🏅 Awards & Honors:

• 🇨🇳 National-Level Young Talent Program Awardee

• 🇩🇪 Humboldt Research Fellowship, Germany

• 🎓 TUFF Fellowship, Technical University of Munich

• 🌏 MOST Fellowship, Taiwan

• 🧠 Invited Book Chapter Author, Springer Nature

• 📖 Top Journal Publications, IEEE TCAD & Microsystems & Nanoengineering

Publication Top Notes

1. FTCD: Fault-Tolerant Co-Design of Flow and Control Layers for Fully Programmable Valve Array Biochips
   📰 IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD)
   📅 2025 | 🔗 DOI: 10.1109/TCAD.2025.3525615
   👥 Contributors: Yuhan Zhu, Genggeng Liu, Wenzhong Guo, Xing Huang

2. Hierarchical Partitioning-Based Inter-Chip Redistribution Layer Routing for Fan-Out Wafer-Level Packaging
   📰 IEEE TCAD
   📅 2025 | 🔗 DOI: 10.1109/TCAD.2025.3558145
   👥 Contributors: Haoyang Xu, Xing Huang, Zhen Zhuang, et al.

3. SlimPort: Port-Driven High-Level Synthesis for Continuous-Flow Microfluidic Biochips
   📰 Micromachines
   📅 2025-05-14 | 🔗 DOI: 10.3390/mi16050577
   👥 Contributors: Youlin Pan, Yanbo Xu, Ziyang Chen, Xing Huang, Genggeng Liu

4. SPTA 2.0: Enhanced Scalable Parallel Track Assignment Algorithm with Two-Stage Partition Considering Timing Delay
   📰 ACM Transactions on Design Automation of Electronic Systems (TODAES)
   📅 2025-03-31 | 🔗 DOI: 10.1145/3712009
   👥 Contributors: Huayang Cai, Pengcheng Huang, Genggeng Liu, Xing Huang, et al.

5. A Robust Multilayer X-Architecture Global Routing System Based on Particle Swarm Optimization
   📰 IEEE Transactions on Systems, Man, and Cybernetics: Systems (TSMC)
   📅 2024 | 🔗 DOI: 10.1109/TSMC.2024.3407960
   👥 Contributors: Genggeng Liu, Yuhan Zhu, Zhen Zhuang, Xing Huang, et al.

6. A Unified Deep Reinforcement Learning Approach for Constructing Rectilinear and Octilinear Steiner Minimum Tree
   📰 IEEE TCAD
   📅 2024 | 🔗 DOI: 10.1109/TCAD.2024.3523429
   👥 Contributors: Zhenkun Lin, Genggeng Liu, Xing Huang, et al.

7. Timing-Driven Obstacle-Avoiding X-Architecture Steiner Minimum Tree Algorithm With Slack Constraints
   📰 IEEE TSMC
   📅 2024 | 🔗 DOI: 10.1109/TSMC.2024.3353534
   👥 Contributors: Yuhan Zhu, Genggeng Liu, Ren Lu, Xing Huang, et al.

📊 Publication Highlights

• ✅ Indexed Journals: IEEE TCAD, IEEE TSMC, ACM TODAES, Micromachines

• 🧠 Technical Strengths: EDA tools, fault-tolerant systems, AI-enhanced synthesis, routing algorithms

• 🌐 Collaborative Network: Co-authorship with top international researchers from CUHK, TUM, Duke, and NTHU

• 📈 Impact Areas: Biochip design, chip packaging, global routing, and design automation algorithms

Conclusion

Prof. Xing Huang exemplifies the qualities of an outstanding researcher: deep technical expertise, global engagement, and a consistent record of high-impact contributions. His research not only advances the frontiers of electronic design and AI-enhanced microfluidics but also cultivates cross-disciplinary innovation. As such, he is exceptionally qualified to receive the Best Researcher Award in recognition of his groundbreaking work, international leadership, and continued contributions to science and engineering.