Gautam Varma Datla

I am a Msc Data Science graduate from the New Jersey Institute of Technology (NJIT), with a Bachelor’s degree in Electronics and Communication Engineering from Shiv Nadar University. My research background has been primarily centered around interpretability, particularly in the domain of solar physics, where I worked on developing interpretable deep learning models for forecasting solar flares.

In addition to my academic pursuits, I have gained practical experience working in industry at companies like Audible, Faire, Precise Software Solutions, and AxiomIO. My primary research interests are centered around LLM robustness, safety, and alignment, with a strong focus on mechanistic interpretability.

Email  /  Google Scholar  /  Github  /  LinkedIn  

profile photo

Publications
An interpretable lstm network for solar flare prediction
IEEE International Conference on Tools with Artificial Intelligence (ICTAI), 2023  
Gautam Datla, Haodi Jiang, Jason TL Wang
Towards Explainable CME Forecasting with Attention-based Sequential Network
arXiv preprint - Under review  
Gautam Datla, Jason TL Wang

Research Experience
Design and Optimization of Power- and Area-Efficient Memristor-Based Leaky Integrate-and-Fire (LIF) Neurons for Neuromorphic Computing
Shiv Nadar University
Datla, G.V.*, Vidhip V.*, & Amitabh C.
Comprehensive Performance Analysis of IoT-Based Smart Devices: Exploring Compression and Routing Protocols Using the COOJA Network Simulator
Shiv Nadar University
Chandra H.*, Datla, G.V.*, & Rohit Singh

Work Experience
    Faire
    Data science intern | May 2024 - August 2024
    Audible, an Amazon company
    Data science research intern | September 2023 - December 2023
    Precise Software Solutions
    Machine learning intern | June 2023 - August 2023
    New Jersey Institute of Technology (NJIT) & NSF
    Graduate research assistant | January 2023 - May 2023
    New Jersey Institute of Technology (NJIT)
    Graduate teaching assistant | Jan 2022 - May 2022
    AxiomIO IT Services
    Data analyst intern | July 2021 - December 2021