Bhanu Prakash Vangala

Research

I study whether we can trust what AI systems produce, from hallucinations in language models to the reproducibility of code written by AI agents, and I build benchmarks and systems to measure it and make LLM-based systems reliable and efficient.

Dissertation: Executable Reliability: Unifying Trust, Reproducibility, and Efficiency in LLM-Based Systems.

Education

Experience

Published & accepted

1. 

   One Threshold Does Not Fit All Languages: Language-Conditional Deferral for Reliable and Efficient Low-Resource Text Classification

   Bhanu Prakash Vangala, Navya Vangala

   Global South in AI Workshop at NeurIPS 2026 · Oral

   @misc{vangala2026thresholddoesfitlanguages,
         title={One Threshold Does Not Fit All Languages: Language-Conditional Deferral for Reliable and Efficient Low-Resource Text Classification},
         author={Bhanu Prakash Vangala and Vangala Navya},
         year={2026},
         eprint={2609.37861},
         archivePrefix={arXiv},
         primaryClass={cs.CL},
         url={https://arxiv.org/abs/2609.37861},
   }

2. 

   AI-Generated Code Is Not Reproducible (Yet): An Empirical Study of Execution Reliability in LLM-Based Coding Agents

   Bhanu Prakash Vangala, Ashish Gehani, Tanu Malik

   ACM REP 2026 · Oral

   @inproceedings{vangala2026aigeneratedcodeexecution,
     author    = {Vangala, Bhanu Prakash and Gehani, Ashish and Malik, Tanu},
     title     = {AI-Generated Code Is Not Reproducible (Yet): An Empirical Study of Execution Reliability in LLM-Based Coding Agents},
     booktitle = {Proceedings of the 4th ACM Conference on Reproducibility and Replicability},
     series    = {ACM REP '26},
     publisher = {ACM},
     year      = {2026},
     month     = jul,
     pages     = {33--46},
     doi       = {10.1145/3820002.3828581},
     url       = {https://doi.org/10.1145/3820002.3828581}
   }

3. 

   Pick and Spin: Cold-Start-Aware Routing for Self-Hosted LLM Serving

   Bhanu Prakash Vangala, Tanu Malik

   IEEE CLOUD 2026 · Oral

   @inproceedings{vangala2026pickspin,
     author    = {Vangala, Bhanu Prakash and Malik, Tanu},
     title     = {Pick and Spin: Cold-Start-Aware Routing for Self-Hosted LLM Serving},
     booktitle = {2026 IEEE 19th International Conference on Cloud Computing (CLOUD)},
     publisher = {IEEE},
     year      = {2026},
     month     = jul,
     pages     = {388--394},
     doi       = {10.1109/cloud72782.2026.00050},
     url       = {https://doi.org/10.1109/cloud72782.2026.00050}
   }

4. 

   CAMP: Consumption-Aware Memory Prediction for Scientific Workflows

   Nagarjuna Chowdary Kandimalla^*, Bhanu Prakash Vangala^*, Tanu Malik

   WORKS at SC26, the International Conference for High Performance Computing

   * Equal contribution
5. 

   AI-Generated Code Is Not Reproducible (Yet): An Empirical Study of Dependency Gaps in LLM-Based Coding Agents

   Bhanu Prakash Vangala, Ali Adibifar, Ashish Gehani, Tanu Malik

   RAI Workshop at AAAI 2026 · Oral

   @misc{vangala2026aigeneratedcodereproducibleyet,
         title={AI-Generated Code Is Not Reproducible (Yet): An Empirical Study of Dependency Gaps in LLM-Based Coding Agents},
         author={Bhanu Prakash Vangala and Ali Adibifar and Ashish Gehani and Tanu Malik},
         year={2026},
         eprint={2512.22387},
         archivePrefix={arXiv},
         primaryClass={cs.SE},
         url={https://arxiv.org/abs/2512.22387},
   }

6. 

   Efficient Multi-Model Orchestration for Self-Hosted Large Language Models

   Bhanu Prakash Vangala, Tanu Malik

   DAI Workshop at AAAI 2026 · Oral

   @misc{vangala2025efficientmultimodelorchestrationselfhosted,
         title={Efficient Multi-Model Orchestration for Self-Hosted Large Language Models},
         author={Bhanu Prakash Vangala and Tanu Malik},
         year={2025},
         eprint={2512.22402},
         archivePrefix={arXiv},
         primaryClass={cs.DC},
         url={https://arxiv.org/abs/2512.22402},
   }

7. 

   HalluMat: Detecting Hallucinations in LLM-Generated Materials Science Content Through Multi-Stage Verification

   Bhanu Prakash Vangala, Sajid Mahmud, Pawan Neupane, Joel Selvaraj, Jianlin Cheng

   AAAI Spring Series 2025, AI for Engineering and Scientific Discoveries · Oral

   View the benchmark

   @misc{vangala2025hallumatdetectinghallucinationsllmgenerated,
         title={HalluMat: Detecting Hallucinations in LLM-Generated Materials Science Content Through Multi-Stage Verification},
         author={Bhanu Prakash Vangala and Sajid Mahmud and Pawan Neupane and Joel Selvaraj and Jianlin Cheng},
         year={2025},
         eprint={2512.22396},
         archivePrefix={arXiv},
         primaryClass={cs.AI},
         url={https://arxiv.org/abs/2512.22396},
   }

8. 

   HalluFormer: A Transformer-Based Framework for Detecting Hallucination in Large Language Models

   Sajid Mahmud^*, Pawan Neupane^*, Joel Selvaraj^*, Bhanu Prakash Vangala^*, Jianlin Cheng

   AAAI Spring Series 2025, AI for Engineering and Scientific Discoveries · Oral

   * Equal contribution
9. 

   Image Colorization using AI

   Bhanu Prakash Vangala, Abdul Mannan Khan, Sagar Sujith Somepalli, Rakesh Chigurupati, Pratham Shah, Shubham Nandlal Vishwakarma

   IJARESM 2022

Under review

1. 

   Code That Works, Environments That Don’t: Measuring Environment Reproducibility in AI-Generated Software

   Bhanu Prakash Vangala, Tanu Malik

   AI Magazine — Special Issue on AI and Reproducibility (AAAI · Wiley) Under review

   Next version in progress: a public benchmark that tests how reliable code from AI coding agents really is, covering reproducibility, environment instability and dependency security. View the benchmark

   @misc{vangala2026codeworksenvironmentsdont,
         title={Code That Works, Environments That Don't: Measuring Environment Reproducibility in AI-Generated Software},
         author={Bhanu Prakash Vangala and Tanu Malik},
         year={2026},
         eprint={2610.00425},
         archivePrefix={arXiv},
         primaryClass={cs.SE},
         url={https://arxiv.org/abs/2610.00425},
   }

2. 

   How Many Labels Does a Language Need? Annotation Budgets and Cross-Lingual Pooling for African-Language Text Classification

   Bhanu Prakash Vangala, Sowmya Guda, Navya Vangala

   Africa in AI Affinity Workshop at NeurIPS 2026 Under review

   @misc{vangala2026labelsdoeslanguageneed,
         title={How Many Labels Does a Language Need? Annotation Budgets and Cross-Lingual Pooling for African-Language Text Classification},
         author={Bhanu Prakash Vangala and Sowmya Guda and Navya Vangala},
         year={2026},
         eprint={2609.37882},
         archivePrefix={arXiv},
         primaryClass={cs.CL},
         url={https://arxiv.org/abs/2609.37882},
   }

3. 

   Evaluation Choices Shape Biomedical ML Claims: A Pediatric Pneumonia Benchmark Case Study

   Bhanu Prakash Vangala, Sowmya Guda, Latha Peddi, Navya Vangala

   RCMLR Workshop at NeurIPS 2026 Under review

   @misc{vangala2026evaluationchoicesshapebiomedical,
         title={Evaluation Choices Shape Biomedical ML Claims: A Pediatric Pneumonia Benchmark Case Study},
         author={Bhanu Prakash Vangala and Sowmya Guda and Latha Peddi and Navya Vangala},
         year={2026},
         eprint={2609.37848},
         archivePrefix={arXiv},
         primaryClass={cs.CV},
         url={https://arxiv.org/abs/2609.37848},
   }

4. 

   AI Sees, XAI Explains? Evaluating Explanation Reliability in Automated Seed Quality Inspection

   Bhanu Prakash Vangala, Navya Vangala

   Computers and Electronics in Agriculture (Elsevier · ScienceDirect) Under review

   @misc{vangala2026aiseesxaiexplains,
     author       = {Vangala, Bhanu Prakash and Vangala, Navya},
     title        = {AI Sees, XAI Explains? Evaluating Explanation Reliability in Automated Seed Quality Inspection},
     year         = {2026},
     howpublished = {SSRN},
     note         = {Available at SSRN: https://ssrn.com/abstract=7544801},
     doi          = {10.2139/ssrn.7544801},
     url          = {https://doi.org/10.2139/ssrn.7544801}
   }

5. 

   Visual Realism Does Not Predict Seed-Quality Utility in AI-Generated Synthetic Seeds

   Bhanu Prakash Vangala, Navya Vangala

   Artificial Intelligence in Agriculture (KeAi / Elsevier · ScienceDirect) Under review
6. 

   AI-Generated Seed Images Do Not Outperform Matched Reuse of Scarce Real Defect Images in Seed Quality Assessment

   Bhanu Prakash Vangala, Navya Vangala

   Scientific Reports (Nature Portfolio · Springer Nature) Under review
7. 

   Scores That Hold, Benchmarks That Leak: Measuring Dataset Contamination in Public Brain-Tumor MRI Classification

   Bhanu Prakash Vangala, Sowmya Guda, Latha Peddi, Navya Vangala

   IEEE Journal of Biomedical and Health Informatics (IEEE · IEEE Xplore) Under review

   @misc{vangala2026scoresholdbenchmarksleak,
         title={Scores That Hold, Benchmarks That Leak: Measuring Dataset Contamination in Public Brain-Tumor MRI Classification},
         author={Bhanu Prakash Vangala and Sowmya Guda and Latha Peddi and Navya Vangala},
         year={2026},
         eprint={2610.00421},
         archivePrefix={arXiv},
         primaryClass={cs.CV},
         url={https://arxiv.org/abs/2610.00421},
   }

Posters & presentations

1. 

   Adaptive Inference: Orchestrating Fine-Tuned LLMs with Serverless GPUs in HPC Environments

   Bhanu Prakash Vangala, Tanu Malik

   University of Missouri · Poster

Awards & honors

2026

Top 100, ACM Doctoral Summit · Association for Computing Machinery

2026

Chameleon Cloud Travel Award · Top 10 proposals, NSF Chameleon Cloud

2026

EECS Graduate Travel Fellowship · University of Missouri

2025

Outstanding Reviewer Award · AI4Mat Workshop, NeurIPS 2025

2025

Google PhD Fellowship Nominee · NLP track, University of Missouri

2025

Outstanding Master’s Student Award · University of Missouri · Photos & post

2025

Runner-up, Generative AI for Social Good Hackathon · IBM / MUIDSI · Photos & post

2023

Dean’s Research Excellence Award · Vellore Institute of Technology

Teaching

Service