{"canonicalUrl":"https://humetric.net/p/profile-82df6553426845bc8135e6588adbf15e","profileVersion":"994a8d8f-e1d7-4aab-b472-a862c6cffcc2","lastUpdated":"2026-09-30T10:41:10.972882+00:00","profile":{"display_name":"Yu-Cheng Lin","last_updated":"2026-09-30","slug":"profile-bd18a37f94db476d","headline":"Quantum Computing and AI-Driven Drug Discovery Researcher","summary":"An interdisciplinary researcher with experience in quantum computing, deep learning, medicinal chemistry, and molecular simulation. A licensed pharmacist in Taiwan with hands-on drug discovery, synthesis, clinical pharmacy, and quantum-enhanced bioinformatics experience.","years_experience":3,"skills":["Bioinformatics","Continual Learning","CUDA","CUDA-Q","Data Science","Deep Learning","Drug Discovery","Drug Synthesis","Graph Neural Networks","High-Performance Computing","LSTM","Machine Learning","Medicinal Chemistry","Meta-Learning","Molecular Simulation","NCHC Cluster Environments","PennyLane","Pharmacy","Python","PyTorch","QAOA","Qiskit","Quantum Computing","Quantum Machine Learning","RDKit","TensorFlow","Variational Quantum Eigensolver","VQE"],"experiences":[{"id":"54ab963c-a230-41c5-b4eb-df555b029db5","person_id":"93dbe1d7-d[contact removed]-eb[contact removed]ca","title":"Research Assistant","company":"Department of Internal Medicine, Taipei Medical University","start_date":"Nov 2025","end_date":"Present","description":"Contributing to a joint Taipei Medical University–Imperial College London collaboration on the “AI-assisted real-time sensing feedback chip for immune drug toxicity analysis” program. Leading optimization of quantum-enhanced analysis pipelines for bioinformatic data and designing approaches to maintain clinical interpretability while leveraging quantum computational advantages for high-dimensional feature extraction. Bridging the medical and quantum teams on problem formulation to ensure research objectives remain clinically relevant while technically feasible with current NISQ hardware.","position":0},{"id":"c771f65b-1b0f-4be5-a2cd-7149786f501b","person_id":"93dbe1d7-d[contact removed]-eb[contact removed]ca","title":"Research Assistant","company":"Department of Electrophysics, National Yang Ming Chiao Tung University","start_date":"Oct 2023","end_date":"Present","description":"Developed GQKAE, an HQKANsformer-based generative eigensolver for QSCI-guided molecular ground-state estimation, achieving approximately 66% reduction in trainable parameters and notable wall-time speedups. Authored QK-LSTM for QAOA, accepted at QCNC 2026, outperforming classical LSTM by achieving perfect parameter transferability and faster convergence with only 43 trainable parameters. Developed LSTM-FC-VQE, published in IEEE Access, accelerating molecular ground-state energy estimation and reducing convergence iterations by a factor of 14 while achieving chemical accuracy.","position":1},{"id":"a13a0bf5-7970-47f6-91d6-7c778e62ad67","person_id":"93dbe1d7-d[contact removed]-eb[contact removed]ca","title":"Technical Director","company":"EntangleTech","start_date":"Oct 2023","end_date":"Present","description":"Directed Taiwan’s quantum education platform, officially supported by the Quantum Bear Microlearning Program. Mentored interns, managed and designed the website, and secured the 8th TSMC Udreamer Award and 8th Becoming Aces Award. Authored a comprehensive series of step-by-step quantum computing tutorials guiding learners from zero background to research-ready levels. Regularly published in-depth paper reviews and industry news.","position":2},{"id":"628fea10-ef30-4dc5-945a-373c114331ee","person_id":"93dbe1d7-d[contact removed]-eb[contact removed]ca","title":"Pharmacist","company":"Clinic","start_date":"Aug 2026","end_date":"Present","description":null,"position":3},{"id":"d5567b7d-7d72-41df-8b82-8ad02add04e2","person_id":"93dbe1d7-d[contact removed]-eb[contact removed]ca","title":"Pharmacist","company":"Pharmacy","start_date":"Mar 2023","end_date":"May 2026","description":"Managed 80 types of controlled substances and established a simplified system for controlled drug administration and inventory checking. Created and managed the pharmacy’s official LINE account, growing the membership base to 1,000+ users. Established an inventory audit mechanism to improve inventory accuracy and operational reliability. Digitized and systematically archived purchase invoices, significantly reducing the time required to retrieve historical records and troubleshoot discrepancies. Built a medication database for 2,000+ products using a dual-index system based on location codes and active ingredient classifications. Systematized the pharmacy formulary, enabling newly hired pharmacists to independently complete dispensing tasks within two weeks. Provided publicly funded PrEP dispensing services and managed oncology drug donation dispensing services.","position":4},{"id":"3bb27c9d-7356-46f1-bc6d-7fbf[contact removed]","person_id":"93dbe1d7-d[contact removed]-eb[contact removed]ca","title":"Pharmacy Intern","company":"MACKAY Memorial Hospital","start_date":"Jul 2019","end_date":"Oct 2019","description":"Dispensed prescription medications to patients. Compounded and dispensed TPN. Promoted medication-use safety. Liaised with and proactively developed relationships with a multidisciplinary team, acting as the main point of contact for medicines. Audited and reviewed prescription and repeat prescription policies to improve the quality, safety, and cost-effectiveness of prescribing.","position":5}],"educations":[{"id":"2dc56df4-f3fe-49ed-bd88-4a4710cde1e1","person_id":"93dbe1d7-d[contact removed]-eb[contact removed]ca","school":"Taipei Medical University","degree":"MS","field":"Pharmaceutical Science","start_year":2020,"end_year":2022},{"id":"b8110c42-7640-4b5e-ab8f-8f49bbc85334","person_id":"93dbe1d7-d[contact removed]-eb[contact removed]ca","school":"Tajen University","degree":"BS","field":"Pharmacy","start_year":2016,"end_year":2020}],"projects":[{"id":"7e1760e7-41c2-4f33-94aa-[contact removed]c","person_id":"93dbe1d7-d[contact removed]-eb[contact removed]ca","name":"Variational Quantum Attention for Molecular Graph Learning","description":"Publication by Y.-C. Lin, Y.-C. Hsu, T.-Y. Li, N.-Y. Chen, S. Y.-C. Chen. arXiv preprint, Sep 2026.","url":null,"technologies":["Quantum Computing","Molecular Graph Learning","Attention"],"position":0},{"id":"8b98da32-302e-469b-89a6-4c1d2331dca1","person_id":"93dbe1d7-d[contact removed]-eb[contact removed]ca","name":"Rethinking Quantum Continual Learning with Quantum Fisher Information","description":"Publication by Y.-C. Hsu, Y.-C. Lin, T.-Y. Li, N.-Y. Chen, E.-J. Kuo. arXiv preprint, Jul 2026.","url":"https://arxiv.org/abs/2607.16030","technologies":["Quantum Continual Learning","Quantum Fisher Information"],"position":1},{"id":"587c9dae-3afa-4c8f-a498-a37a333c91fc","person_id":"93dbe1d7-d[contact removed]-eb[contact removed]ca","name":"Generative Quantum-inspired Kolmogorov-Arnold Eigensolver","description":"Publication by Y.-C. Lin and Y.-C. Hsu, with equal contribution, and collaborators. QCE26, May 2026.","url":"https://arxiv.org/abs/2605.04604","technologies":["Generative quantum eigensolver","transformer","quantum chemistry","quantum machine learning","Kolmogorov– Arnold networks","High-performance computing"],"position":2},{"id":"2d13843e-[contact removed]a-[contact removed]b7","person_id":"93dbe1d7-d[contact removed]-eb[contact removed]ca","name":"Meta-Learning for Quantum Optimization via Quantum Sequence Model","description":"Publication by Y.-C. Lin, Y.-C. Hsu, and S. Y.-C. Chen. Presented at the International Conference on Quantum Communications Networking, and Computing (QCNC), April 2026.","url":"https://arxiv.org/abs/2512.05058","technologies":["Meta-Learning","Quantum Optimization","Quantum Sequence Models"],"position":3},{"id":"8aa67391-d161-44c9-8709-e1f07085f607","person_id":"93dbe1d7-d[contact removed]-eb[contact removed]ca","name":"Accelerating Parameter Initialization in Quantum Chemical Simulations via LSTM-VQE","description":"Publication by R.-Y. Chang and Y.-C. Lin, with equal contribution, and collaborators. IEEE Access, Nov 2025.","url":"https://ieeexplore.ieee.org/document/11224826/","technologies":["LSTM","VQE","Quantum Chemical Simulation"],"position":4},{"id":"86c30765-22b4-4db7-8797-cee79cfdf0b9","person_id":"93dbe1d7-d[contact removed]-eb[contact removed]ca","name":"Entropy Analysis of Spatial Entanglement in Quantum Random Walks","description":"Publication by R.-Y. Chang, Y.-C. Lin, and collaborators. Presented at the 28th Annual Quantum Information Processing Conference (QIP), Jan 2025.","url":null,"technologies":["Quantum Random Walks","Spatial Entanglement","Entropy Analysis"],"position":5},{"id":"b61441a8-a87a-4a87-9fa9-d7f806ae0dd0","person_id":"93dbe1d7-d[contact removed]-eb[contact removed]ca","name":"NISQ algorithm for simulating open-quantum systems","description":"QHack Hackathon project that achieved third rank in the world in Mar 2024. Developed a variational quantum state preparation (VQSP) algorithm to transform classical to quantum states efficiently. The algorithm increased circuit depth linearly with the number of qubits, compared with exponential growth in the conventional method. Applied VQSP in open quantum system simulation to prepare an approximate non-Hermitian operator as a linear combination of unitary operators and evaluate and calculate its expectation.","url":"https://github.com/Hirmay/Qhack","technologies":["Variational Quantum State Preparation","Open Quantum Systems","Quantum Circuits"],"position":6}]},"chunksVersion":"profile-chunks-v4","approvedDiscoveryQueries":[],"evidence":[{"id":"identity:0","type":"identity","ordinal":0,"locale":"en","text":"Yu-Cheng Lin. Quantum Computing and AI-Driven Drug Discovery Researcher. 3 years experience","fieldKeys":["display_name","headline","years_experience"]},{"id":"summary:0","type":"summary","ordinal":0,"locale":"en","text":"Yu-Cheng Lin. Quantum Computing and AI-Driven Drug Discovery Researcher. Summary / 簡介: An interdisciplinary researcher with experience in quantum computing, deep learning, medicinal chemistry, and molecular simulation. A licensed pharmacist in Taiwan with hands-on drug discovery, synthesis, clinical pharmacy, and quantum-enhanced bioinformatics experience.","fieldKeys":["summary"]},{"id":"skills:0","type":"skills","ordinal":0,"locale":"en","text":"Yu-Cheng Lin. Quantum Computing and AI-Driven Drug Discovery Researcher. Skills / 技能: Bioinformatics, Continual Learning, CUDA, CUDA-Q, Data Science, Deep Learning, Drug Discovery, Drug Synthesis, Graph Neural Networks, High-Performance Computing, LSTM, Machine Learning, Medicinal Chemistry, Meta-Learning, Molecular Simulation, NCHC Cluster Environments, PennyLane, Pharmacy, Python, PyTorch, QAOA, Qiskit, Quantum Computing, Quantum Machine Learning, RDKit, TensorFlow, Variational Quantum Eigensolver, VQE","fieldKeys":["skills"]},{"id":"discovery:0","type":"discovery","ordinal":0,"locale":"en","text":"Yu-Cheng Lin. Quantum Computing and AI-Driven Drug Discovery Researcher. Role / 職稱: Quantum Computing and AI-Driven Drug Discovery Researcher. Experience / 年資: 3 years experience. Expertise / 專長: Bioinformatics, Continual Learning, CUDA, CUDA-Q, Data Science, Deep Learning, Drug Discovery, Drug Synthesis, Graph Neural Networks, High-Performance Computing, LSTM, Machine Learning","fieldKeys":["display_name","headline","years_experience","skills"]},{"id":"experience:0","type":"experience","ordinal":0,"locale":"en","text":"Yu-Cheng Lin. Quantum Computing and AI-Driven Drug Discovery Researcher. Experience / 經歷: Research Assistant at Department of Internal Medicine, Taipei Medical University. Nov 2025 to Present. Contributing to a joint Taipei Medical University–Imperial College London collaboration on the “AI-assisted real-time sensing feedback chip for immune drug toxicity analysis” program. Leading optimization of quantum-enhanced analysis pipelines for bioinformatic data and designing approaches to maintain clinical interpretability while leveraging quantum computational advantages for high-dimensional feature extraction. Bridging the medical and quantum teams on problem formulation to ensure research objectives remain clinically relevant while technically feasible with current NISQ hardware.","fieldKeys":["experiences"]},{"id":"experience:1","type":"experience","ordinal":1,"locale":"en","text":"Yu-Cheng Lin. Quantum Computing and AI-Driven Drug Discovery Researcher. Experience / 經歷: Research Assistant at Department of Electrophysics, National Yang Ming Chiao Tung University. Oct 2023 to Present. Developed GQKAE, an HQKANsformer-based generative eigensolver for QSCI-guided molecular ground-state estimation, achieving approximately 66% reduction in trainable parameters and notable wall-time speedups. Authored QK-LSTM for QAOA, accepted at QCNC 2026, outperforming classical LSTM by achieving perfect parameter transferability and faster convergence with only 43 trainable parameters. Developed LSTM-FC-VQE, published in IEEE Access, accelerating molecular ground-state energy estimation and reducing convergence iterations by a factor of 14 while achieving chemical accuracy.","fieldKeys":["experiences"]},{"id":"experience:2","type":"experience","ordinal":2,"locale":"en","text":"Yu-Cheng Lin. Quantum Computing and AI-Driven Drug Discovery Researcher. Experience / 經歷: Technical Director at EntangleTech. Oct 2023 to Present. Directed Taiwan’s quantum education platform, officially supported by the Quantum Bear Microlearning Program. Mentored interns, managed and designed the website, and secured the 8th TSMC Udreamer Award and 8th Becoming Aces Award. Authored a comprehensive series of step-by-step quantum computing tutorials guiding learners from zero background to research-ready levels. Regularly published in-depth paper reviews and industry news.","fieldKeys":["experiences"]},{"id":"experience:3","type":"experience","ordinal":3,"locale":"en","text":"Yu-Cheng Lin. Quantum Computing and AI-Driven Drug Discovery Researcher. Experience / 經歷: Pharmacist at Clinic. Aug 2026 to Present","fieldKeys":["experiences"]},{"id":"experience:4","type":"experience","ordinal":4,"locale":"en","text":"Yu-Cheng Lin. Quantum Computing and AI-Driven Drug Discovery Researcher. Experience / 經歷: Pharmacist at Pharmacy. Mar 2023 to May 2026. Managed 80 types of controlled substances and established a simplified system for controlled drug administration and inventory checking. Created and managed the pharmacy’s official LINE account, growing the membership base to 1,000+ users. Established an inventory audit mechanism to improve inventory accuracy and operational reliability. Digitized and systematically archived purchase invoices, significantly reducing the time required to retrieve historical records and troubleshoot discrepancies. Built a medication database for 2,000+ products using a dual-index system based on location codes and active ingredient classifications. Systematized the pharmacy formulary, enabling newly hired pharmacists to independently complete dispensing tasks within two weeks. Provided publicly funded PrEP dispensing services and managed oncology drug donation dispensing services.","fieldKeys":["experiences"]},{"id":"experience:5","type":"experience","ordinal":5,"locale":"en","text":"Yu-Cheng Lin. Quantum Computing and AI-Driven Drug Discovery Researcher. Experience / 經歷: Pharmacy Intern at MACKAY Memorial Hospital. Jul 2019 to Oct 2019. Dispensed prescription medications to patients. Compounded and dispensed TPN. Promoted medication-use safety. Liaised with and proactively developed relationships with a multidisciplinary team, acting as the main point of contact for medicines. Audited and reviewed prescription and repeat prescription policies to improve the quality, safety, and cost-effectiveness of prescribing.","fieldKeys":["experiences"]},{"id":"education:0","type":"education","ordinal":0,"locale":"en","text":"Yu-Cheng Lin. Quantum Computing and AI-Driven Drug Discovery Researcher. Education / 學歷: MS. Pharmaceutical Science. Taipei Medical University","fieldKeys":["educations"]},{"id":"education:1","type":"education","ordinal":1,"locale":"en","text":"Yu-Cheng Lin. Quantum Computing and AI-Driven Drug Discovery Researcher. Education / 學歷: BS. Pharmacy. Tajen University","fieldKeys":["educations"]},{"id":"project:0","type":"project","ordinal":0,"locale":"en","text":"Yu-Cheng Lin. Quantum Computing and AI-Driven Drug Discovery Researcher. Project / 專案: Variational Quantum Attention for Molecular Graph Learning. Built with / 使用技術: Quantum Computing, Molecular Graph Learning, Attention. Publication by Y.-C. Lin, Y.-C. Hsu, T.-Y. Li, N.-Y. Chen, S. Y.-C. Chen. arXiv preprint, Sep 2026.","fieldKeys":["projects"]},{"id":"project:1","type":"project","ordinal":1,"locale":"en","text":"Yu-Cheng Lin. Quantum Computing and AI-Driven Drug Discovery Researcher. Project / 專案: Rethinking Quantum Continual Learning with Quantum Fisher Information. Built with / 使用技術: Quantum Continual Learning, Quantum Fisher Information. Publication by Y.-C. Hsu, Y.-C. Lin, T.-Y. Li, N.-Y. Chen, E.-J. Kuo. arXiv preprint, Jul 2026.","fieldKeys":["projects"]},{"id":"project:2","type":"project","ordinal":2,"locale":"en","text":"Yu-Cheng Lin. Quantum Computing and AI-Driven Drug Discovery Researcher. Project / 專案: Generative Quantum-inspired Kolmogorov-Arnold Eigensolver. Built with / 使用技術: Generative quantum eigensolver, transformer, quantum chemistry, quantum machine learning, Kolmogorov– Arnold networks, High-performance computing. Publication by Y.-C. Lin and Y.-C. Hsu, with equal contribution, and collaborators. QCE26, May 2026.","fieldKeys":["projects"]},{"id":"project:3","type":"project","ordinal":3,"locale":"en","text":"Yu-Cheng Lin. Quantum Computing and AI-Driven Drug Discovery Researcher. Project / 專案: Meta-Learning for Quantum Optimization via Quantum Sequence Model. Built with / 使用技術: Meta-Learning, Quantum Optimization, Quantum Sequence Models. Publication by Y.-C. Lin, Y.-C. Hsu, and S. Y.-C. Chen. Presented at the International Conference on Quantum Communications Networking, and Computing (QCNC), April 2026.","fieldKeys":["projects"]},{"id":"project:4","type":"project","ordinal":4,"locale":"en","text":"Yu-Cheng Lin. Quantum Computing and AI-Driven Drug Discovery Researcher. Project / 專案: Accelerating Parameter Initialization in Quantum Chemical Simulations via LSTM-VQE. Built with / 使用技術: LSTM, VQE, Quantum Chemical Simulation. Publication by R.-Y. Chang and Y.-C. Lin, with equal contribution, and collaborators. IEEE Access, Nov 2025.","fieldKeys":["projects"]},{"id":"project:5","type":"project","ordinal":5,"locale":"en","text":"Yu-Cheng Lin. Quantum Computing and AI-Driven Drug Discovery Researcher. Project / 專案: Entropy Analysis of Spatial Entanglement in Quantum Random Walks. Built with / 使用技術: Quantum Random Walks, Spatial Entanglement, Entropy Analysis. Publication by R.-Y. Chang, Y.-C. Lin, and collaborators. Presented at the 28th Annual Quantum Information Processing Conference (QIP), Jan 2025.","fieldKeys":["projects"]},{"id":"project:6","type":"project","ordinal":6,"locale":"en","text":"Yu-Cheng Lin. Quantum Computing and AI-Driven Drug Discovery Researcher. Project / 專案: NISQ algorithm for simulating open-quantum systems. Built with / 使用技術: Variational Quantum State Preparation, Open Quantum Systems, Quantum Circuits. QHack Hackathon project that achieved third rank in the world in Mar 2024. Developed a variational quantum state preparation (VQSP) algorithm to transform classical to quantum states efficiently. The algorithm increased circuit depth linearly with the number of qubits, compared with exponential growth in the conventional method. Applied VQSP in open quantum system simulation to prepare an approximate non-Hermitian operator as a linear combination of unitary operators and evaluate and calculate its expectation.","fieldKeys":["projects"]}]}