Introduction to Computational Biomedicin

INTRO COMPUTAT BIOMED & H

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.

• TR 4:10 p.m.-5:25 p.m.
• Instructor: Gamze Gursoy
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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.

• F 10 a.m.-11:15 a.m.
• Instructor: Chunhua Weng
  h-index: 37 Info
• 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
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• 1 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: Rita Kukafka
  h-index: 28 Info
• Instructor: George M Hripcsak
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• Instructor: Herbert S Jr Chase
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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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• Instructor: Richard A Friedman
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• 1-12 points

PROJECTS-BIOMEDICAL INFORMATCS

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

• Instructor: Harris Wang
  h-index: 32 Info
• Instructor: Soojin Park
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• Instructor: Tal Korem
  h-index: 18 Info
• Instructor: Shalmali Joshi
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• Instructor: Pierre Elias
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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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• 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: Chunhua Weng
  h-index: 37 Info
• Instructor: Gamze Gursoy
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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: Chunhua Weng
  h-index: 37 Info
• Instructor: Raul Rabadan
  Wikipedia h-index: 72 Info
• Instructor: Olena Mamykina
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• Instructor: Nicholas Tatonetti
  Wikipedia h-index: 36 Info
• Instructor: Sarah A Rossetti
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• Instructor: Harris Wang
  h-index: 32 Info
• Instructor: George M Hripcsak
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• Instructor: Gamze Gursoy
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• 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: Olena Mamykina
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• Instructor: Nicholas Tatonetti
  Wikipedia h-index: 36 Info
• Instructor: George M Hripcsak
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• Instructor: Harris Wang
  h-index: 32 Info
• Instructor: Gamze Gursoy
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• 0 points