Arjun L.


Arjun is a PhD candidate in Computer Science at Carnegie Mellon University. His research interests primarily span robotics and computer graphics, with secondary interests in computer vision, computational imaging, and machine learning. Prior to moving to Pittsburgh, he spent multiple years at UCLA earning his MS and BS in Computer Science, Computer Engineering, and Math Economics, where he graduated cum laude as a member of Upsilon Pi Epsilon, Tau Beta Pi, and (most proudly) Sigma Eta Pi. 

Arjun has also spent a number of years as a full-time software engineer at small to mid-sized companies. Most recently, he was the first full-time hire at an LA-based startup that went on to secure $1.5 million of funding. In addition to research interests, he has experience architecting and building production-grade systems from the ground up. He hopes to leverage both these skills in building his own company after completing his PhD. 

Arjun has served as a university teaching assistant for multiple classes at UCLA, including upper division undergraduate classes in computer graphics and network hardware. He has additionally worked as an undergraduate learning assistant in introductory programming, data structures, algorithms, and AI courses. He prefers to work with small numbers of students at a time, and has consistently received highly positive reviews from student evaluations.

Outside of academic activities, Arjun enjoys swimming, cooking, musical theater, flying, and making copious amounts of unwarranted movie and book references. These references, unfortunately, do not usually land, but he loves it when they do.


Education & Qualifications
  • Carnegie Mellon University, PhD candidate in Computer Science
  • University of California, MS in Computer Science
  • University of California, BS in Computer Science and Engineering
  • University of California, BS in Mathematics Economics


  • Computer Science (Python, C/C++, Java, JavaScript, HTML/CSS)
  • Software Development 
  • AP
  • Algorithms 
  • Machine Learning
  • Circuit Design (Analog, Digital)
  • Analytical and Numerical Optimization Techniques
  • Artificial Life in Computer Graphics and Vision
  • Game Development (Augmented Reality, Virtual Reality)
  • Fundamentals of Artificial Intelligence
  • Mathematical Statistics
  • Operating Systems
  • Shared Economy Systems and Optimization
  • Statistical Financial Models, Systems and Signals