About Me
Hi there, I’m Neel! I’m 22 and live in San Francisco, California.
I’m a graduate student in the EECS department at UC Berkeley finishing my master’s degree in May 2022 and an alumnus of Johns Hopkins University Class of 2020.
My current research is really cool! I’m managing a team that is applying deep learning to build knowledge graphs for applications in the DeFi space–an exciting hybrid project at the intersection of AI and crypto. Feel free to contact me to talk more about it!
I am an aspiring machine learning engineer and data scientist with 2 years of industry experience working on end-to-end projects, including leadership and project management roles.
I’m also a musician on the side!
Projects
This is the project that inspired my career in Machine Learning!
Sponsored by the Johns Hopkins Applied Physics Laboratory (APL) for the VA hospital system of the DMV area, our team worked full-time to build an autonomous hospital disinfection robot.
As project manager, I led our diverse team working between numerous disciplines: computer vision, robotics, hardware, and microbiology.
I worked hands-on as a machine learning engineer, creating a Faster R-CNN model for object detection using PyTorch and CUDA. This model was run on an NVIDIA Jetson TX2. Additionally, I programmed our robot’s arm movement by writing Python ROS scripts and successfully integrated all ROS nodes into a single system.
Experience
I worked as a graduate intern on the Operations Technology & Advanced Analytics team and built deployment infrastructure for time series models to be used in Seagate manufacturing sensors via NVIDIA’s EGX edge computing platform.
I led an intern cohort of Micron’s yield analysis team in building deep learning models for failure probability as part of Micron’s AI & Smart Manufacturing initiative.
I created a multithreaded parsing script for design rule checking GF’s 180 nm process and streamlined chip test case generation using NLP methods and a K-means clustering algorithm.
Education
University of California, Berkeley
MEng Electrical Engineering & Computer Science
2021 - 2022
I am a graduate student in UC Berkeley’s EECS department focused on Machine Learning and Data Systems. For my research capstone advised by Dr. Dawn Song, I am the project manager of a team working on building knowledge graphs (KGs) using deep learning with applications focused in the decentralized finance (DeFi) space.
Johns Hopkins University
BS Electrical Engineering
2018 - 2020
As an undergraduate at Johns Hopkins, I was a researcher in photonics under Dr. Amy Foster and focused my coursework on VLSI. Thanks to my hardware background, I now understand computers from software to silicon. I graduated a year early with honors and a 3.95 GPA.
Music
I am a singer and songwriter on the side!
To accompany my vocals, I play the ukulele, guitar, piano, and harmonica.
While I am currently on TikTok (@neelk99), I plan to release my first Spotify EP in 2022.
I also love going to concerts, and I have a wide music taste encompassing R&B, EDM, pop, hip-hop, rap, jazz and soul.
I collect vinyls, and my favorite records are bossa nova albums featuring Antonio Carlos Jobim, João Gilberto, Stan Getz, and Elis Regina. Going along with the Brazilian theme, I love to samba!
Other Interests
Other than music, there is nothing more therapeutic to me than cooking. I’m an improvisational chef. Hand me anything and I’ll whip something up, no recipe needed!
I am very outgoing and extroverted, and I always love meeting new people!
I’m a travel hacker! Best deal I’ve booked so far: Oakland to Barcelona for $150.
At least 90% of my clothes are thrifted, second-hand clothing is the sustainable way to go!
I’m a proud gay man and an ardent advocate for LGBTQ+ youth. Previously a member of oSTEM during my undergrad, I would love to connect about any new mentorship opportunities!