Etash Guha

Overall GPA: 3.97/4.00, Threads in Intelligence and Theory

Working on the Reliability of Large Language Models

Developed Learned Cost Model using Graph Neural Networks to predict quality of chip placement, beating several man-made heuristics

Implemented Pipeline for analyzing slippage data and Neural Net strategy for Price prediction with NLP data

Integrated Bidirectional Encoder Representations from Transformers NLP Model into SAS Products using PyTorch

Using Python with libraries such as SciKit and OpenCV for Data and Video Analysis

Advisor: Jacob Abernethy, Xiaoming Huo

Developped Generalization Bounds for Magnitude-Based Pruning. Proved that Sparse and Wide Neural Networks Forget Less. Developped an No-Regret Framework to solve Robust Markov Decision Processes.

Advisor: Jacob Abernethy, Vidya Muthukumar, Ashwin Pananjady

Working on designing general class of frameworks for two player Fenchel Games to model perceptron algorithms. Tested a Hebbian Plasticity based learning system and analyzed its computational capacity. Analyzing Efficient Algorithm for generating Conformal Prediction Sets. Developed an Inverse Reinforcement Learning algorithm for Linear Stochastic Bandits. Developed a learned methodology to efficiently and accurately generate solutions to NP-Hard problems.

Advisor: Patricio Vela

Developed a more efficient autonomous exploration method for robots with 9.8% increased accuracy over standard Frontier Based Exploration using ROS and C++

Full-Ride Merit Scholarship given to 40 Freshman at Georgia Tech

An International Mentorship Program for Aspiring Researchers in Computer Science given to 40 students

Awarded to students with 4.0 GPA