teaching

Teaching experience and graduate student mentorship in computational biology, AI/ML, and clinical research.

Graduate Research Mentorship

Carnegie Mellon University Capstone Project

Icahn School of Medicine at Mount Sinai | Sep 2024 - Dec 2024

Mentored 6 Carnegie Mellon University graduate students on a CAR-T therapy monitoring capstone project focused on early detection of Cytokine Release Syndrome (CRS).

Project Scope:

  • Guided experiment design, baselining, and reporting for CRS prediction using wearable data and cytokine biomarkers
  • Students developed ML models using time-lagged features from wearable devices (skin temperature, SpO2) and 92-biomarker Olink panel
  • Evaluated 5 classifiers (Random Forest, Gradient Boosting, SVM, Logistic Regression, k-NN) via StratifiedKFold CV
  • Final models achieved 84.62% accuracy for ide-cel and 80.62% for cilta-cel within a 6-hour prediction window
  • Coordinated with clinical team on project scope, data access, IRB compliance, and deliverables

Skills Developed by Students:

  • Clinical ML pipeline development
  • Time-series feature engineering from wearable data
  • Biomarker analysis and SHAP interpretation
  • Healthcare data handling and HIPAA compliance

AI/ML Integration Mentorship

Icahn School of Medicine at Mount Sinai | Oct 2023 - Present

Ongoing mentorship of clinical research staff and junior team members on AI/ML integration in precision oncology workflows.

Activities:

  • Trained clinical research staff on RAG system usage and interpretation for multiple myeloma research
  • Developed documentation and tutorials for AI tools in clinical workflows
  • Guided team members on production ML system development and deployment
  • Mentored on LLM fine-tuning, inference optimization, and multi-agent system design
  • Established best practices for model evaluation, validation, and clinical deployment

Teaching Experience

Data Structures & Algorithms for Bioinformatics

New York University, Tandon School of Engineering | Spring 2022 - Spring 2023

Teaching Assistant for graduate-level course under Prof. Manpreet S. Katari for 3 semesters.

Course Details:

  • Semesters: Spring 2022, Fall 2022, Spring 2023
  • Students: 130+ master’s students across all semesters
  • Focus: Bridging computer science fundamentals with bioinformatics applications

Responsibilities:

Instruction:

  • Taught data structures, algorithms, and genomic algorithms in recitation sessions
  • Covered sequence alignment algorithms (Smith-Waterman, Needleman-Wunsch)
  • Explained graph algorithms for biological networks (shortest paths, MST, network flow)
  • Demonstrated dynamic programming applications in genomics

Curriculum Development:

  • Created assignments bridging CS fundamentals with real bioinformatics problems
  • Developed course materials on genomic data structures:
    • Suffix trees and suffix arrays
    • Burrows-Wheeler Transform (BWT)
    • FM-index for sequence alignment
  • Designed problem sets applying algorithms to real genomic datasets

Student Support:

  • Held weekly office hours for one-on-one support on complex algorithmic concepts
  • Graded assignments and provided detailed feedback on algorithm design and implementation
  • Assisted students with final projects applying algorithms to real genomic datasets
  • Provided guidance on computational complexity analysis and optimization

Conference Presentations & Engagement

I actively participate in academic conferences to share research and stay connected with the broader scientific community.

ACL 2023 (BEA Workshop) - Association for Computational Linguistics, Toronto, Canada

  • Presented work on detecting LLM-generated text in computing education
  • Engaged with the NLP research community on AI-generated content detection

IMS 2024 (International Myeloma Society) - Rio de Janeiro, Brazil

  • Presented multi-omics integration research for multiple myeloma risk stratification
  • Connected with clinicians and researchers in precision oncology

ASH 2025 (American Society of Hematology) - San Diego, CA

  • Presenting PRIME model for myeloma relapse prediction
  • Poster on OncoCITE multi-agent system for genomic evidence extraction

Speaking & Collaboration

I’m interested in giving talks, guest lectures, and workshops on:

  • Multi-agent AI systems for scientific discovery
  • LLM applications in clinical research
  • Production ML systems in healthcare
  • RAG architectures for clinical decision support
  • GPU-accelerated genomic pipelines

If you’re interested in having me speak at your institution, conference, or event, please reach out at quidwaiali@gmail.com.