Scholar
Yinkai Wang
Google Scholar ID: PfRyo6EAAAAJ
Tufts University
Citations & Impact
Citations
239
H-index
7
i10-index
5
Publications
12
Co-authors
14
list available
Publications
Resume (English only)
Academic Achievements
- Publications:
- - “Large Language Model is Secretly a Protein Sequence Optimizer” accepted by ICLR LMRL 2025
- - “MADGEN: Mass-Spec attends to De Novo Molecular generation” accepted by ICLR 2025
- - “On Separate Normalization in Self-supervised Transformers” accepted by NeurIPS 2023
- - “Multi-objective Deep Data Generation with Correlated Property Control” accepted by NeurIPS 2022
- - “Property-Controllable Generation of Quaternary Ammounium Compounds” accepted by DLG-KDD 2022
- - “Small Molecule Generation via Disentangled Representation Learning” accepted by Bioinformatics
- - “Dataset Geography: Mapping Language Data to Language Users” accepted by ACL 2022
- - “Graph-based Ensemble Machine Learning for Student Performance Prediction” accepted by AAAI (AI4EDU, DLG’22)
- - “Deep Latent-Variable Models for Controllable Molecule Generation” accepted by BIBM 2021
- - “Ensemble Machine Learning System for Student Academic Performance Prediction” accepted by W4U workshop @EDM 2021
- Other Achievements:
- - Served as a reviewer for BIOKDD 2022
- - Served as a reviewer for AAAI-DLG’22
- - Selected to participate in the CCI Scholars program
- - Ranked in the top 20% in the Kaggle competition ‘Google Smartphone Decimeter Challenge’
Research Experience
- Conducted research at Tufts University, collaborating with multiple advisors including Dr. Antonios Anastasopoulos, Dr. Liang Zhao, and Dr. Amarda Shehu. Participated in the CCI Scholars program with Dr. Daniel Barbará. Interned at Peking University VDIG lab with Dr. Yongtao Wang. Worked on text generation at JD.com with Dr. Lingfei Wu and Dr. Xiaojie Guo.
Education
- PhD Student, Tufts University, Advisor: Dr. Soha Hassoun
Background
- Research Interests: Protein Structure Prediction, Molecule Generation, Named Entity Recognition, and Educational Data Mining. Areas of expertise include bioinformatics, data mining, machine learning, multilingual natural language processing, computer vision, and deep graph learning.
Miscellany
- Personal Interests: Open to opportunities in paper review, tutorial, and workshop organization in areas related to bioinformatics, data mining, machine learning, multilingual natural language processing, computer vision, and deep graph learning.
