Skills

AI/ML & Data Science Skills:

• AI & Machine Learning: Equivariant GraphNNs, Deep Learning, Generative Autoencoders & Adversarial Network (GAN), Diffusion Models, LLMs, Clustering, SVM, Random Forest.
• Python Tools & Modules: PyTorch, Tensorflow, Pandas, NumPy, Keras,, Sklearn, Seaborn, Matplotlib, SciPy.

Computer Enthusiast:

• Scientific Programming: Python, bash, tcl/tk, slurm/pbs scripts.
• Highlighted Skills: AWS and HPC computing, GIT, DVC; Data Version Control (Iterative AI)
• Linux architecture (Networking, Security and File server): Admin role in troubleshooting system-related issues in PhD research group: Designed LDAP-based client-server protocol (400 TB file server+10 clients) •

Simulation Packages:

• APIs: Atomic Simulation Environment (ASE), BioSimSpace, OpenMM, BioPython, MDTraj, AlphaFold
• Schrödinger Suite: Potentially explored backend workflow of various packages during the summer internship.
• Cheminformatics: OpeneyeKit, RDKit, OpenBabel, PaDel, Balloon, and Confab
• Simulation Packages: MD: NAMD, AMBER, DL-POLY, Gromacs, Desmond • QM: Siesta, Gaussian16, Orca, Terachem, GAMESS, VASP, USPEX, Quantum-Espresso • Docking: Autodock, Glide, Gold, OEDocking.
• Visualization: VMD, Pymol, Chimera, Molden, Gabedit, Gaussview, VESTA, Avogadro, Mercury.
• Biophysics skills: Protein purification, X-ray crystallography, and CyroEM