CV

PhD application CV — Dhwanil R. Chauhan. Graduate Researcher at CIVS, Purdue University Northwest. Agentic AI · Multimodal Reasoning · Embodied AI · Robustness & Evaluation.

Contact Information

Name Dhwanil R. Chauhan
Professional Title Graduate Researcher · Intelligent Agents & Multimodal Reasoning
Email chauha56@purdue.edu

Professional Summary

Graduate researcher at the Center for Innovation Through Visualization and Simulation (CIVS), Purdue University Northwest. I study intelligent agents that operate in complex environments with multimodal, incomplete, and unreliable information. My work spans environment understanding, multimodal robustness, interactive information gathering, and agentic decision-making.

Experience

  • 2024 - present

    Purdue University Northwest, Hammond, IN

    Graduate Research Assistant
    Center for Innovation Through Visualization and Simulation (CIVS)
    Research at the intersection of multimodal AI and industrial safety, in partnership with the Steel Manufacturing Simulation and Visualization Consortium (SMSVC).
    • Built a conversational AI system guiding supervisors through structured incident capture via natural dialogue, replacing fragmented manual safety reporting across incident types spanning crane failures, pinch points, and equipment damage. (AISTech 2025)
    • Developed a multi-camera spatial reasoning system dynamically redefining safety zone boundaries from live equipment positions, enabling proactive hazard detection before incidents occur. (AISTech 2026)
    • Contributed core architectural components of a feed-forward framework synthesizing geometrically accurate binaural audio from standard video for industrial safety simulation. (CVPR Workshop 2026)
  • 2025 - 2025

    Remote

    AI Research Analyst
    Untapped Ventures
    • Designed three investment-decision LLM agents (Pre-Seed, Seed, Studio) that ingest heterogeneous pitch materials and generate structured invest/pass recommendations against a formalized multi-stage evaluation rubric.
    • Built an automated screening pipeline with multi-source retrieval and LLM-based scoring (1–100 scale); three-tier confidence routing triggered autonomous outreach above 67, analyst review between 40–67, and batched triage below 40.
    • Iterated through prompt engineering cycles to improve structured output reliability and context retention, developing applied intuitions around LLM failure modes in multi-step reasoning pipelines.

Publications

  • 2026
    Visual Geometry Grounded Novel-View Acoustic Synthesis
    CVPR Workshop 2026

    First unified framework for novel-view acoustic synthesis bypassing explicit 3D reconstruction via feed-forward visual geometry grounding. Contribution: designed the VGGT output representation and formulated the Q/K structure of the Geometry-Grounded Acoustic Decoder (GGAD) cross-attention mechanism.

  • 2026
    Development of Trialing Image Detection for a Melt Shop Safety Tool
    AISTech 2026

    Multi-camera perception system for dynamic safety zone reconfiguration in active industrial environments. Contribution: developed the rule-based spatial reasoning engine fusing four camera perspectives to redefine safety boundaries from outermost detected blocker positions.

  • 2025
    Artificial Intelligence-Assisted Accident Investigation: Improving Safety Reporting with LLMs
    AISTech 2025

    Conversational AI system for industrial safety incident management with context-aware dialogue and dynamic action sequencing. Contribution: designed and implemented the conversational AI backend — monolithic Django pipeline handling context retention, dialogue state, and action sequencing.

  • 2026
    TandemBench: Evaluating Dual-Encoder Retrieval Under Joint Image-Text Corruption
    Submitted to WACV 2027 Round 2

    Lead researcher. Benchmark of 19 dual-encoder retrieval models under joint image-text corruption across MS-COCO and Flickr30k, with 83,754 evaluations and analysis of nine test-time adaptation methods.

Education

  • 2024 - 2026

    Hammond, IN

    Master of Science
    Purdue University Northwest
    Computer Science
    • Thesis track under Prof. Yang Ni
    • Research focus: Intelligent Agents, Multimodal Reasoning, Environment Understanding
  • 2020 - 2024

    Gujarat, India

    Bachelor of Technology
    Charotar University of Science and Technology (CHARUSAT)
    Computer Science
    • 9 publications across ML domains including security, medical imaging, and NLP
    • ACM Student Body President
    • Training and Placement Coordinator

Skills

Research Areas: Intelligent Agents, Multimodal Reasoning, Environment Understanding, Active Information Seeking, Vision-Language Models, Robustness Evaluation
Frameworks & Tools: PyTorch, Hugging Face Transformers, LangChain, LangGraph, OpenCV, VGGT
Languages: Python, SQL, JavaScript, LaTeX
Infrastructure: Multi-GPU Training, REST APIs, Docker, Git

Academic Service

  • 2024 - present

    Springer Nature

    Peer Reviewer
    Neural Computing and Applications
  • 2024 - present

    UBahrain

    Peer Reviewer
    International Journal of Computing and Digital Systems (IJCDS)

Languages

English : Professional working proficiency
Gujarati : Native speaker
Hindi : Fluent