Nicholas Asker
MS in Computer Science, Columbia University
Machine Learning track
nga2120@columbia.edu
My current research interest is in LLM-powered autonomous agents.
I am especially excited by the prospect of improving model performance and decision-making through
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retrieval-augmented generation (RAG): providing relevant information as context using intelligent search techniques (using vector- or embedding-indexed databases), and
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self-improvement and automatic feedback mechanisms such as self-refine.
I like coding because it lets me find flow, be curious, and create. I'm interested in machine learning in particular because of its potential to solve otherwise intractable problems.
I recently graduated with a masters in computer science from Columbia University (May 2024). I chose the Machine Learning track as my specialization and am especially passionate about Large Language Models (LLMs) and deep learning.
My first exposure to coding came while I was a cybersecurity consultant (2017 - 2021), where I had the opportunity to pick up Python. I felt great joy learning to program for the first time and suddenly realized how much constructive power a programmer has – literally at their fingertips – with the capacity to create highly useful and beautiful things through code. So, I committed to going back to school to study computer science – to build a firm engineering foundation and pivot my career into something I loved.
The first half of my graduate program consisted of fundamental coursework in data structures, algorithms, systems programming, and mathematics. Through this portion of the program, I became a proficient programmer in C, Python, and Java and developed strong problem-solving skills. In the latter half, I shifted focus to topics in Artificial Intelligence