Akshat Bokdia

Akshat Bokdia

AI/ML Engineer | MSE CIS at UPenn

I build models that make language systems safer to deploy, and I care about whether they hold up on real traffic rather than on a benchmark.

I am a graduate student at the University of Pennsylvania, where I study computer science with a focus on machine learning and natural language processing. Most of my work sits at the point where a model meets production: taking something that performs well in a notebook and finding out what it actually does when real users are on the other side of it.

Recently that has meant guardrails for large language models — classifiers that sit in front of and behind a generative agent, deciding what is safe to answer and what needs a second look before it reaches a user. Before that I worked on anomaly detection and causal inference over telecom network data, and on deep learning for medical imaging and genomics across research groups at Yale and the University of Cincinnati.

I have co-authored six peer-reviewed papers and book chapters, listed below. I am always glad to talk about evaluation, model reliability, or anything adjacent — write to me.

TIFIN

Jun 2026 – Aug 2026

AI Engineering Intern · Boulder, CO

  • Built the response-side compliance classifier for an advisor-facing chat agent — a fine-tuned ModernBERT that scores every generated response against 26 regulatory categories in roughly 37 ms, trained on a 10,000-record corpus of synthetic scenarios and PII-anonymized production traces.
  • Built the question-side screen as a pair of models: a LoRA fine-tuned general-purpose guardrail adapted to domain risks its broader taxonomy could not isolate, and a capability classifier reaching 0.97 micro-F1 at 96.7% precision on held-out production traffic.
  • Owned the evaluation and serving path end to end — prevalence-adjusted test sets, threshold calibration, real-versus-synthetic slices, and GPU deployment behind authenticated inference endpoints.

PyTorch · Hugging Face · PEFT/LoRA · Modal · vLLM · Logfire

Ericsson

Feb 2025 – Aug 2025

Data Scientist Intern · Chennai, India

  • Built a semi-supervised anomaly detection pipeline for time-series network KPIs, combining decomposition techniques with tree-based and density-based models.
  • Applied causal inference to estimate the effect of network configuration parameters on user throughput, separating genuine causal impact from confounded correlation.
  • Curated a 10,000-sample question-answering dataset and fine-tuned DeepSeek-R1 distilled models with instruction-tuned prompts for domain adaptation.

Python · scikit-learn · statsmodels · DoWhy · Hugging Face · Amazon SageMaker

itTrident

Sep 2024 – Oct 2024

Data Analyst Intern · Chennai, India

  • Created an interactive Power BI dashboard analyzing airline operations and passenger behavior.
  • Built a CRM app in Power Apps to manage customer data, track leads, and automate follow-ups.

Excel · Power BI · Power Apps

Cheeni Labs

Aug 2023 – Sep 2023

ML Project Intern · Chennai, India

  • Fine-tuned a pre-trained general embedding model for movie review classification, improving retrieval relevance for the team's recommendation surface.
  • Preprocessed a 100,000-review dataset and trained a BERT-based summary classifier for Flixjini, the company's streaming search product.

Python · SQL · Sentence Transformers

Gerstein Lab, Yale University

Jul 2024 – Aug 2024

Summer Research Intern · New Haven, CT (Remote)

  • Trained convolutional and autoencoder models to classify structural variants in genomic sequences.
  • Built the preprocessing and sequence-embedding pipeline the classifiers were trained on.

Python · TensorFlow · Hugging Face

Prasath Lab, University of Cincinnati

Mar 2024 – Aug 2024

Research Intern · Cincinnati, OH (Remote)

  • Developed hybrid feature extraction techniques for brain tumour classification in medical imaging.
  • Built deep learning models that improved context-based retrieval accuracy over a brain tumour image corpus — work that became a published conference paper.

Python · TensorFlow · OpenCV

Journal & conference papers

Book chapters

Citation counts and any newer work are on Google Scholar.

Bully Detector

A cyberbullying classifier for short-form social text, trained on a corpus of over 40,000 labelled tweets and reaching an F1 of 0.87.

Python · NLTK · scikit-learn · MySQL

DebateMate

An LLM-backed debate partner. Pick a topic and a difficulty, argue a side, and get structured feedback on your reasoning as the exchange goes on.

Python · Streamlit · LLM APIs

Wave Control

Real-time hand gesture recognition mapped to media controls, so playback and volume can be driven without touching the keyboard.

Python · OpenCV · TensorFlow

Uber Data Analysis

An exploratory analysis of six months of New York Uber pickups, visualising how demand moves across hours, days and boroughs.

R · ggplot2

University of Pennsylvania

2025 – 2027

MSE in Computer and Information Science · Philadelphia, USA GPA 4.0/4.0

Coursework: Machine Learning · Trustworthy ML · Agentic AI · Computer Vision & Computational Photography

Vellore Institute of Technology

2021 – 2025

B.Tech in Computer Science and Engineering · Vellore, India GPA 3.97/4.0

Coursework: Natural Language Processing · Artificial Intelligence · Big Data Analytics · Programming for Data Science

Languages

Python, R, SQL, C++, Shell

Machine learning

PyTorch, TensorFlow, scikit-learn, Hugging Face (Transformers, PEFT, Datasets), DSPy, OpenCV, NLTK

Data & statistics

NumPy, pandas, statsmodels, DoWhy, Matplotlib, Seaborn, Excel, Power BI, Tableau

Infrastructure

Modal, vLLM, Amazon SageMaker, Logfire, Git, MySQL, SQLite, Streamlit, Flask