Gautam Galada

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About

👋 Hi, I'm Gautam Galada.

I'm an innovative computer science graduate with extensive interest and practical knowledge in Natural Language Processing and Pattern Recognition. I practice making latent spaces interpretable and optimizing them through internal and external understanding. I ask a lot of questions — questions with answers and questions without answers, and then I try to find the answers to the questions that don't have one.

Currently, I'm working on designing probing strategies for Explainable AI (XAI) as a Ph.D. student at the University of North Texas.

I also write occasionally on Medium: https://medium.com/@gautamgalada1105.

Gautam Galada

Quick info:

  • Email: gautamgalada1105@gmail.com
  • Location: Denton, TX

My current focus areas include LLM interpretability research examining refusal mechanisms in privacy-sensitive contexts, FAISS-based information retrieval systems, human-in-the-loop prompt auditing for LLMs, and passwordless authentication with FIDO2-compliant biometrics. I'm also deeply interested in physics-informed ML, edge AI, quantum machine learning, and memory-based learning systems.

Skills

Core technical stack from research + production projects.

Python 90%
PyTorch / Lightning 85%
NLP (Transformers / HuggingFace) 85%
CUDA / Parallel Compute 75%
Java / C++ / Systems 75%
Security / Cryptography 80%
Data & ML Tooling (NumPy, Pandas, scikit-learn) 85%
LLM Ops (LangChain, OpenAI, Ollama) 80%

Resume

Summary

Gautam Galada

Innovative computer science graduate with extensive interest and practical knowledge in Natural Language Processing and Pattern Recognition, seeking opportunities with focus on core neural network functionalities. I practice making latent spaces interpretable and optimizing them through internal and external understanding. Also, I ask questions. A lot of questions. Questions with answers and questions without answers, and then I try to find the answers to the questions that don't have one. Currently working on designing probing strategies for Explainable AI (XAI).

Education

Ph.D. in Computer Science and Engineering

Aug 2025 – Present

University of North Texas · Smart Electronics System Lab

GPA: 4.0

M.S. in Artificial Intelligence

Aug 2023 – Dec 2024

University at Buffalo

GPA: 3.12

B.Tech in Computer Science and Engineering

Jul 2019 – May 2023

VIT-AP University · AI Specialization

CGPA: 8.51

Research Interests

  • Latent Space Interpretability
  • Language Modelling & Natural Language Processing
  • Scaling and Optimization Models
  • Reinforcement Learning
  • Edge AI and Embedded Intelligence
  • Physics Informed Machine Learning
  • Systems and Philosophy
  • Quantum Machine Learning

Experience

AI & ML Intern

Mar 2025 – Jul 2025

Buffalo Niagara Medical Campus, Inc.

  • Built CV systems for anomaly detection and feature extraction, implementing physics-informed ML models (SINDy - SHRED) for fluid dynamics using sparse neural networks.
  • Engineered MCP framework integrations with prompt engineering and evaluation protocols, delivering scalable AI agents and knowledge synthesis tools.
  • Led HIPAA-compliant ML development for secure medical data processing, optimizing models and advancing privacy research through automated workflows and data masking techniques.

Co-Founder

Oct 2021 – Sept 2023

Digital Fortress Pvt. Ltd.

  • Founded and led a passwordless authentication startup, developing FIDO2‑compliant biometric solutions with advanced facial recognition and liveness detection.
  • Established zero‑knowledge proofs and decentralized identity protocols, achieving a 99.9% reduction in account takeovers and a 40% increase in user adoption rates compared to traditional 2FA methods.

Research Assistant

Oct 2021 – May 2023

Artificial Intelligence and Robotics Center, VIT-AP

  • Developed advanced lip synchronization modules using VQGAN and Codebook algorithms, improving mouth movement accuracy by 40% and reducing visual artifacts by 60%. Achieved a lip‑sync error rate below 100 milliseconds, resulting in highly realistic talking face animations.
  • Led a project on federated learning for cyberbullying detection using zero‑shot learning and a CNN‑BiLSTM‑ Attention mechanism, integrated with custom GloVe and context vector analysis. The system achieved an accuracy of 97.4% for English and 92.7% for Hindi, demonstrating effectiveness across multiple languages.

AI Product Developer

Jan 2021 – Jun 2021

RAPYD AI GmbH

  • Enhanced abstractive summarization of podcast content by refining transformer and PEGASUS models, achieving a 35.69% improvement in ROUGE‑L score, reducing factual inconsistencies by 25%, and increasing summary coherence by 30%.
  • Conducted in‑depth statistical and linguistic analysis of Spotify's podcast corpus, deriving insights to augment model precision and facilitate smoother integration into user‑focused applications.

Portfolio

Selected projects from research, hackathons, and systems development.

Hover and click "+" to preview images, or the link icon for project details.

  • All
  • LLMs
  • RAG / Retrieval
  • Security
  • GenAI
  • Systems
DONNA - Dynamic Online Neural Network Assistant
MediaRF - Secure Radio Transmission
LLM Interpretability: Refusal Mechanisms
FAISS Optimized Information Retrieval System
MAuthN - Facial Anti-Spoofing

Achievements

  • Contributed during the Metaverse demonstration at the "Recent Research Trends and Applications of AI and IoT" FDP (Faculty Development Program) at NIT Warangal
  • Hosted Mindhack, a student-run AI summit where AI pioneers such as Thomas Wolf (HuggingFace CTO), Sam Lightstone (IBM CTO) and other twenty dignitaries provided insights on "Can Machines Think?" — View LinkedIn posts
  • Winner at Smart India Hackathon 2022 — Project repository
  • Top 3 startups at FIDO Developer Challenge India 2022 — View certificate
  • Runner-up at Fintech Innovative Challenge 2022
  • INEX 2022 – Silver Award Certificate — View certificate

Publications

Selected publications and research works. Full list available on Google Scholar.

Conference Papers & Journal Articles
  • DUCK: Developing Unassisted Cognitive Knowledge for Cyberbullying Detection — Gautam Galada, Dev Kapadia, Sibi Chakkaravarthy Sethuraman, Sunil Kumar Singh, Anupama Namburu, and Hari Seetha. ACM (In-Press). Manuscript link
  • Optimizing Policy Gradient Methods for Adaptive Gait Rehabilitation — Galada, Gautam & Chakkaravarthy, Sibi. (2024). DOI: 10.13140/RG.2.2.25370.04807/1
  • Metakey: A Novel and Seamless Passwordless Multifactor Authentication for Metaverse — Sibi Chakkaravarthy Sethuraman, Aditya Mitra, Gautam Galada, Anisha Ghosh, and S Anitha, 2022 IEEE International Symposium on Smart Electronic Systems (iSES), pp. 662–664, 2022. IEEE Xplore
Preprints & arXiv
  • MetaSecure: A Passwordless Authentication for the Metaverse — Sibi Chakkaravarthy Sethuraman, Aditya Mitra, Anisha Ghosh, Gautam Galada, and Anitha Subramanian. arXiv:2301.01770, 2023. https://arxiv.org/abs/2301.01770
  • MagicEye: An Intelligent Wearable Towards Independent Living of Visually Impaired — Sibi C. Sethuraman, Gaurav R. Tadkapally, Saraju P. Mohanty, Gautam Galada, and Anitha Subramanian. arXiv:2303.13863, 2023. https://arxiv.org/abs/2303.13863

Other Stuff

Writing: https://medium.com/@gautamgalada1105

Current code: compression-layer

Hobbies and Interests

  • Podcasts: Lex Fridman, Huberman Labs
  • Books: Quantum Computing Since Democritus, Surely You're Joking, Mr. Feynman!
  • Sports: European Football
  • Research Areas: Open Source, Internet of Things, Quantum Computing, Memory-based Learning

Contact

Location:

Denton, TX

Find me online