FarhanSadeek
Hi, I'm Farhan, an undergraduate at Columbia University studying Computer Science with minors in Applied Physics and Statistics in the School of Engineering and Applied Science. Previously, I spent a year at Dartmouth College, where I was advised by Peter Chin and Rahul Sarpeshkar, and completed my last two years of high school as a dual-enrolled student at The Ohio State University. I'm broadly interested in mechanistic interpretability, efficient inference and training, and reinforcement learning.
Most of the notes are written using LaTeX in Visual Studio Code with Andrew Lin's style package, with assistance from Codex or Claude Code. If you find any mistakes or have suggestions for improvement, please don't hesitate to reach out at farhan [at] farhansadeek [dot] com.
Columbia
Computer Science
COMS 6998 G AI-Native Computing* AI-Native Computing* — COMS 4995 G Competitive Programming* Competitive Programming* — COMS 4705 G Natural Language Processing* Natural Language Processing* — COMS 3261 Theory of Computation Theory of Computation — COMS 3134 Data Structures in Java Data Structures in Java —Operations Research
CSOR 4231 G Analysis of Algorithms Analysis of Algorithms —Physics & Chemistry
CHEM 1403 General Chemistry I General Chemistry —Mathematics
MATH 3901 T Putnam Seminar Putnam Seminar —History
HIST 2413 United States 1940-1975 United States 1940-1975 —Miscellaneous
ENGI 1102 The Art of Engineering The Art of Engineering —Dartmouth
Engineering and Computer Science
ENGS 109 G Compressed Sensing High-dimensional Sensing and Learning notes ENGS 106 G Machine Learning Principles of Machine Learning notes ENGS 105 G Principles of Causality Principles of Causality text ENGS 96 G Math for Machine Learning Mathematics for Machine Learning notes COSC 50 Software Design and Impl. Software Design and Implementation notes COSC 10 Data Structures Object-Oriented Programming notesMathematics
MATH 70 Statistical Learning Theory Multivariate Statistics and Statistical Learning notes MATH 63 Honors Real Analysis Honors Real Analysis notes MATH 54 Point-Set Topology Point-Set Topology notes MATH 25 Number Theory Elementary Number Theory notes MATH 23 Differential Equations Differential Equations notes MATH 22 Linear Algebra Linear Algebra notes MATH 13 Multivariable Calculus Multivariable Calculus notesPhysics
PHYS 19 Quantum Physics Relativistic and Quantum Physics — PHYS 14 Introductory Physics II Introductory Physics II — PHYS 13 Introductory Physics I Introductory Physics I —Miscellaneous
MATH 7 Analyzing Network Data Analyzing Network Data notes WRIT 5 Expository Writing Expository Writing: Word Meaning in Context —Ohio State
Mathematics
MATH 4580 Abstract Algebra Abstract Algebra notes MATH 4573 Number Theory Number Theory notes MATH 4547 Real Analysis Introductory Real Analysis notes MATH 4512 Partial Differential Eqs. Partial Differential Equations text MATH 3345 Discrete Mathematics Foundations of Higher Mathematics text MATH 2568 Linear Algebra Linear Algebra text MATH 2255 Differential Equations Ordinary Differential Equations text MATH 2153 Multivariable Calculus Multivariable Calculus textStatistics
STAT 4202 Statistical Inference Statistical Inference notes STAT 4201 Probability Theory Probability Theory text STAT 3470 Statistics for Engineers Probability and Statistics for Engineers textComputer Science
CSE 2321 Discrete Structures Discrete Structures text CSE 2231 Software Dev. and Design Software Development and Design notes CSE 2221 Software Components Software Components textPhysics
PHY 2301 Intermediate Mechanics II Intermediate Mechanics II notes PHY 2300 Intermediate Mechanics I Intermediate Mechanics I textMiscellaneous
ENG 3304 Business Writing Business and Professional Writing — ENG 1110 English Composition First-Year English Composition — BIO 1102 Human Biology Human Biology — GER 1102 Beginning German II Beginning German II — GER 1101 Beginning German I Beginning German I —G — Graduate T — Topics * — Audit
I was a TA for CSE 2231 at Ohio State — notes. Separate math & algorithms notes here. I was involved in research on link prediction in complex networks (pdf). I also wrote a short paper on signal-to-noise ratio (pdf). I also participated in the Directed Reading Program, reading Goodman's Introduction to Fourier Optics and An Introduction to Metric Geometry.