Xin Cao

Xin Cao

The Chinese University of Hong Kong Shenzhen

Hey there! This is Xin Cao, a Master of Philosophy in Computational Biology at The Chinese University of Hong Kong, Shenzhen (CUHKSZ) I also aquired my Bachelor of Science in Data Science (Computing Stream) degree at CUHKSZ.

I am currently under the supervision of Prof. Hsien-Da HUANG in the Warshel Institute for Computational Biology, focusing on Deep Learning for transcriptomics and proteomics. I’ve also worked with Prof. Gang CAO at the Shenzhen University of Advanced Technology, where I led a project on Protein Protein Interaction Prediction (PPI) using Graph Neural Networks (GNNs). In the past, I also followed Prof. Zhizheng Wu of CUHKSZ in topics on Music Tracks Generation via Latent Diffusion Models (LDM) and Audio Enhancement. My first research experience was supervised by Prof. Feng ZHENG at SUSTech and contributed some works on Multimodal Computer Vision (CV) Adversarial Robustness, and did surveys on AI music.

Growing up in Cold Spring Harbor (CSHL), my interests and instincts for Biological Sciences have been cultivated greatly to combine with my backgrounds in Data Science and CS:

  • DL transcriptomics & AI Virtual Cells: Artificial Intelligence can and should be utilized to explore Biological Data Patterns and Large Models has shown progress to fit cells.
  • PepPI / DTI / AIDD: Building on my PepPI paper, I seek to explore Drug Discovery from target interaction perspectives.
  • AI Music (Non-generative): Tracks Seperation, Audio Enhancement, Arrangements Assisting.

I am actively seeking interesting research opportunities and Ph.D. positions in the future. If you are looking for a dedicated and self-motivated candidate, please DO contact me at xincao@link.cuhk.edu.cn !

For the final part I’d love to talk about achievements aside of academics. I’m the core player / captain of the CUHKSZ / Harmonia College Soccer Team ⚽️, 2023 champion 🏆 of Shenzhen City, and also formed bands writing original songs covering Hardcore Punk, Blues Rock, R&B, Jazz-Hiphop, Post Rock, etc. As guitarist 🎸 keyboard 🎹 and lead singer 🎤, Led Zeppelin and Guns’n’Roses are among my favorites. Additionally, I attained ABRSM Grade 5 in Piano & Music Theory in Los Angeles by the age of 10, and also am the Top10 singers (1st place duet) of CUHKSZ 🏆. As team captain & mid, I also won the 2026 CUHKSZ League of Legends 🎮 Championship 🏆. Though extracurricular, I firmly believe these experiences link and help my academic works both subjectively & technically, also fostering open-mindedness and creativity in research.

🔥 News

  • 2026.10:  🎤 Will present at the Single Cell Asia & Spatial Biology Asia Congress my MIRCID poster at the Nanyang Technological University.
  • 2026.09  📄 Submitted 1-st Author Paper to Advanced Science, now available on Arxiv.
  • 2026.04  🎉 My Paper on Deep Learning miRNA Inference ACCEPTED by Advanced Science!
  • 2026.03  🏆 Attained Annual Top10 Singers in CUHKSZ TheVoice Fianls 🎤 & CUHKSZ League of Legends Championship 🎮!
  • 2025.09  🎉 1-st Author Paper ACCEPTED by Briefings in Bioinformatics!!!
  • 2024.09:  🎉 4th Place in the ICSR 2024 Robot Design Competition: presented PASIR, a multimodal emtion prediction robot using BCI-driven emotion models.
  • 2024.08:  🎤 Delivered Speech at the 2024 Opening Ceremony as the Student Representative of Harmonia College, awarded a scholarship of ¥10,000 RMB.
  • 2024.04:  🏅 Ranked Global Top 10 in the 2024 Bremen Big Data Challenge, led the project under supervision of Prof. Haizhou LI
  • 2023.10:  🏆 Champion of 2023 Shenzhen Soccer League, Runner-up of 2024 League, Core Player of school team.
  • 2024.11:  🎸 Performance at HOULIVE, Shenzhen’s No.1 livehouse.

📜 Publications

[1] X. Cao, J. Li, F. Meng, B. Yang, Y. Zou. Enhancing Cross-Domain Protein and Peptide Interaction with Re-trained Deep Learning Models. (Briefings in Bioinformatics 2026).

[2] X. Cai, Y. Pang, J. Liao, J. Ma, S. Cui, Y. Chen, Y. Lin, X. Cao, T. Xu, Y. Chen, J. Xu, J. Wan, T. Lee, S. Huang, H. Huang. SiCmiR Atlas: Single-Cell miRNA Landscape Reveals Hub-miRNA and Network Signatures in Human Cancers. (Advanced Science 2026).

[3] X. Cao, Y. Chen, J. Xu, Z. Zhang, X. Cheng, Z. Zhu, Y. Zhang, X. Cai, X. Huang, Y. Lin, H. Huang. MIRCID: MiRNA Features Drive Cross-Task Improvements in Drug Mechanistic Modeling. (Advanced Science 2026, Under Review).

📝 Research Experience

Nov 2024
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MIRCID: miRNA prediction for Cross-task Drug Mechanisms

The Chinese University of Hong Kong, Shenzhen, Supervised by Hsiend-Da Huang

  • miRNA Inference Model Development: Developed HubmiRNet to map 977 L1000 genes to 1298/414 hub-miRNAs, outperforming Transformer, KAN, and DenseNet baselines with 87% Pearson correlation.
  • Mechanistic Pathway Analysis: Constructed DL framework for cancer pathways and showed that miRNA features improved drug MoA & drug perturbation pathway classification.
  • Statistical/Ablational & Rescue Case Analyses: For HubmiRNet outputs, performed ablation experiments, regularized CCA, CKA, ridge reconstruction trials. Also biologically analyzed rescue cases where gene-only predictions failed
June 2024
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Protein Interaction Prediction: Short Protein Dataset Investigation and Peptide Analysis

Shenzhen University of Advanced Technology, Supervised by Prof. Gang Cao

  • Summary: Investigated protein-protein interaction (PPI) prediction model architecture and datasets, proposing the use of short protein sequences to optimize feature learning & computational efficiency. Built a cross-species, non-redundant protein and peptide database and visualized PPI features.
  • Methods and Tools: Utilized PyTorch, Tensorflow for model construction (GIN, GAT, VQ-VAE, etc.) and finetuning; CDHIT, MatPlotLib, Linux awk for data processing; AlphaFold2, seqvec, LSTM for protein structure information construction.
  • Key Outcomes: Found out training on short protein datasets could improve novel PPI prediction, and finetuning on long+short datasets could improve model performance. Achieved 99.94% accuracy and 98.85% F1 score, establishing a high-performance benchmark for future research.
Sep 2022
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Multimodal CV Adversarial Robustness and AI Music Survey

SUSTech, Supervised by Prof. Feng ZHENG

  • Evaluation of System Robustness: Investigated and organized various metrics to assess and enhance the robustness of image-text retrieval systems. Participated in data preprocessing, model debugging, and evaluating model performance, focusing on the impact of preprocessing techniques on evaluation results.
  • Research and Model Re-implementation: Independently researched the fields of Optical Music Recognition (OMR) and AI music generation. Re-implemented and adjusted codes from recent papers, optimizing label data to improve model accuracy. Delivered technical analyses and summaries during team meetings.

🎖 Honors and Awards

  • 2024.09 : 4th Place, ICSR 2024 Robot Design Competition
  • 2024.08 : Outstanding Leader (¥10,000 RMB), 2023 Chinese University of Hong Kong, Shenzhen Harmonia Annual Scholarship
  • 2024.04 : Global Top10 Ranking, 2024 Bremen Big Data Challenge
  • 2024.03 : Silver, 7th Aunual Sports Festival of Chinese University of Hong Kong, Shenzhen (Team Captain)
  • 2023.01 : Champion, 2022 Shenzhen Annual Soccer League (Team Core Player)

🎓 Educations

  • 2020.09 - 2024.12 (now) : The Chinese Uiversity of Hong Kong, Shenzhen; Shenzhen China
    • B.Sc., Data Science & Big Data Technology, School of Data Science
    • Related Courses : Advanced Machine Learning, Reinforcement Learning, Deep Learning and Applications, Speech and Natural Language Processing, Data Mining, Database Systems, Bioinformatics, Bayesian Statistics, Stochastic Simulation, Stochastic Processes, Optimization, Operations Management, C/C++
  • 2008.09 - 2012.12 : Doyle & Southgrove; CA, United States & NY, United States
    • Honors: Project Beyond Class (school Top 10% students)

🎤 Invited Talks

  • 2024.09 : 16th International Conference on Social Robotics (ICSR 2024)
  • 2021.03 : Harmonia College Opening Ceremony, Student Representative of 2024

💻 Proffesional Experiences

  • 2021.06 - 2021.09 : Algorithm Engineer, Kunyu Biotechnology Co., Ltd., Wuhan, China.
    • Gene Alignment Program Development: Developed gene alignment program using Python and BLAST in two rounds to identify uniquely high-repeating DNA fragments in telomere and centromere regions of target chromosone. Quantitatively analyzed and optimized the threshold changes on final results, obtained high quality probes and an Invention Patent.
    • Program Optimization: Assessed and reformed algorithm logic, comparatively experimented different toolkits. Reduced execution time from 48h to under 10h, memory usage by threefold.
    • Data Processing and Report Writing: Processed and analyzed output data in Linux, integrated biological information to select detectable sequences without fold spatial structures. Compiled final sequences and wrote user-friendly manual.

🚀 Additional Skills

  • 🛠️ Technical : Python, Linux, PyTorch, Tensorflow, SQL, Spark, RegEx, LaTeX, C/C++, Java, Stable Diffusion, Ollama
  • 📖 English : Five years of school in America (Native Speaker)
  • 🎵 Music : Experienced in Logic Pro, Reaper, Lumafusion; Lead vocal, lead guitar, keyboard, captain of original band; 1st place in University Singing Competition (Duet); University choir Tenor; ABRSM Grade 5 in piano
  • ⚽️ Soccer : Captain of college team; Core player of university team; Champion of Shenzhen University soccer League