Introduction to Computational Biomedicin

INTRO TO COMP BIOMED & HE

This course offers a comprehensive introduction to the core computational methods driving modern biomedical research and health data science. As biological and clinical datasets grow in scale and complexity—from genomic sequences and molecular profiles to electronic health records (EHRs) and consumer health data—this course equips students with the essential computational foundations to model, analyze, and interpret high-dimensional biomedical data.

Organized around key algorithmic challenges spanning Clinical Informatics, Consumer Health Informatics, and Bioinformatics, the course focuses on the design and application of algorithms and statistical models to solve real-world biomedical problems. Lectures emphasize practical techniques and showcase their use across diverse biomedical data types.

Designed for advanced undergraduates and graduate students in biomedical informatics, computer science, biomedical engineering, applied mathematics, and related fields, this course builds a rigorous understanding of computational biomedicine. It serves as a core requirement for the Biomedical Informatics PhD and master’s programs and is cross-listed with Computer Science. Students interested in careers in bioinformatics, health data science, computational biology, or biomedical AI will find this course especially valuable.

As biomedical data continue to expand in size, diversity, and impact, this course provides a critical foundation in the algorithmic, statistical, and computational tools needed to advance the future of research at the intersection of computation and human health.

• MW 4:10 p.m.-5:25 p.m.
• Instructor: Harry Jr. Reyes
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• 3 points

SYMBOLIC AI IN HEALTH CARE

This course is customized for 1st-year PhD and MA students in the biomedical informatics graduate program and also

open to other interested students at Columbia. It provides a detailed overview of symbolic methods.

• TR 9 a.m.-10:15 a.m.
• Instructor: Chunhua Weng
  h-index: 37 Info
• 3 points

Special Topics in Biomedical Informatics

Real World Evidence inMed

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• T 2:10 p.m.-4 p.m.
• Instructor: Tara V Anand
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• 3 points

Projects in Mathematical Genomics

Projects Math Genomics

Mathematical genomics synthesizes between high resolution quantitative research and molecular measurements in the context of clinical or biological analysis. This course will provide independent research experience in this field for interested students under the direction of a faculty advisor. This course is suitable for students with background in the subject matter (e.g., biology, chemistry) who wish to learn quantitative data analysis and methods development, as well as for those with technical background (e.g., biomedical informatics) who wish to apply their skills to biological research. Instructor permission is required for registration.

• Instructor: Tal Korem
  h-index: 18 Info
• 1-6 points

The Future of Personal Health Assistant:

This course integrates the principles of database systems, AI agents, and health informatics. Students will gain expertise in the following areas:


Multimodal Data Engineering:
Ingesting, cleaning, and normalizing heterogeneous data (time-series sensor data, unstructured clinical notes, structured FHIR records)

Agentic Architectures:
Designing LLM-based agents capable of tool use (function calling), planning, and memory management (LangChain, LlamaIndex).

Retrieval-Augmented Generation (RAG):
Implementing vector databases and semantic search strategies optimized for personal health contexts.

Privacy and Ethics:
Understanding HIPAA compliance, differential privacy, and the ethical implications of AI "hallucinations" in health advice.

HCI for Health:
Designing applications and interfaces that foster trust, explainability, and engagement in self-tracking and patient-provider communication.

Domain Knowledge:
Understanding the basics of chronic disease management, personal health monitoring, and clinical decision support.

• F 8:40 a.m.-11:40 a.m.
• 3 points

RES SEM IN BIOMED INFORMATICS

Prerequisite: open to public. Presentations by medical informatics faculty and invited international speakers in medical informatics, computer science, nursing informatics, library science, and related fields.

• M 1 p.m.-2 p.m.
• Instructor: Sarah A Rossetti
  Info
• 1 points

Fieldwork: Bridging Theory and Practice

The Fieldwork: Bridging Theory and Practice elective is designed to provide students with the opportunity to integrate theoretical knowledge gained in their academic program with hands-on, real-world experience. This elective aims to enhance students' practical skills, professionalism, and industry readiness.

MA students are eligible to register for this course up to 3 times after completing 2 full semesters of courses 

·        Full time (40 hours per week) in the Summer (after completing 2 full semesters) and part-time (up to 20h per week) in Fall and Spring (also after completing 2 full semesters)

·         This course can only be taken as part of degree requirements. Students who have already completed all the degree requirements (required courses and 30 credits) are not eligible

            o    Students who wish to take it in the Spring of their 2nd year, need to make sure they still have course/credits that need to be completed in the same semester

·         Students cannot take the fieldwork course pass/fail and must receive a standard letter grade.

• Instructor: Olena Mamykina
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• 1-12 points

PROJECTS-BIOMEDICAL INFORMATCS

Research in medical informatics under the direction of a faculty adviser.

• Instructor: Noemie Elhadad
  Wikipedia h-index: 46 Info
• Instructor: Chunhua Weng
  h-index: 37 Info
• Instructor: Mohammed Alquraishi
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• Instructor: Andrea Califano
  h-index: 77 Info
• Instructor: Dennis Vitkup
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• Instructor: Raul Rabadan
  Wikipedia h-index: 72 Info
• Instructor: George M Hripcsak
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• Instructor: Olena Mamykina
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• Instructor: Yufeng Shen
  h-index: 47 Info
• Instructor: Karthik Natarajan
  h-index: 17 Info
• Instructor: Gamze Gursoy
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• Instructor: Sarah A Rossetti
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• 1-12 points

PROJECTS-BIOMEDICAL INFORMATCS

Research in medical informatics under the direction of a faculty adviser.

• Instructor: Soojin Park
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• Instructor: Tal Korem
  h-index: 18 Info
• Instructor: Shalmali Joshi
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• Instructor: Matthew McDermott
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• Instructor: Bianca Dumitrascu
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• Instructor: Tarjinder Singh
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• Instructor: Orson Xu
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• Instructor: Aziz Alkattan
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• 1-12 points

READINGS IN BIOMED INFORMATICS

Prerequisite: approval of adviser. Readings on topics in medical informatics under the direction of a faculty adviser.

• Instructor: Virginia G Lorenzi
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• 1-12 points

M.PHIL TEACHING EXPERIENCE

Prerequisite: instructors permission. Participation in medical informatics educational activities under the direction of a faculty adviser.

• Instructor: Harry Jr. Reyes
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• Instructor: Chunhua Weng
  h-index: 37 Info
• Instructor: Tara V Anand
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• 2 points

DOCTORAL RESEARCH

Prerequisite: completion of all M.Phil. requirements, and approval of a research proposal by the supervising faculty adviser.

• Instructor: Noemie Elhadad
  Wikipedia h-index: 46 Info
• Instructor: Chunhua Weng
  h-index: 37 Info
• Instructor: Raul Rabadan
  Wikipedia h-index: 72 Info
• Instructor: Olena Mamykina
  Info
• Instructor: Soojin Park
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• Instructor: Nicholas Tatonetti
  Wikipedia h-index: 36 Info
• Instructor: Yufeng Shen
  h-index: 47 Info
• Instructor: Sarah A Rossetti
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• Instructor: Shalmali Joshi
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• Instructor: George M Hripcsak
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• Instructor: Gamze Gursoy
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• Instructor: Tal Korem
  h-index: 18 Info
• Instructor: Mohammed Alquraishi
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• Instructor: Bianca Dumitrascu
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• Instructor: Tarjinder Singh
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• Instructor: Karthik Natarajan
  h-index: 17 Info
• 1-12 points

DOCTORAL DISSERTATION

Prerequisite: completion of all M.Phil. requirements. Ph.D. candidates may be required to register for this course every term during the preparation of the dissertation.

• Instructor: Raul Rabadan
  Wikipedia h-index: 72 Info
• Instructor: Nicholas Tatonetti
  Wikipedia h-index: 36 Info
• Instructor: Sarah A Rossetti
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• Instructor: Gamze Gursoy
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• 0 points