PhD Candidate, Computer Science · Kansas State University

Aryan
Singh Dalal

Building AI that can explain what it knows.

I work on trustworthy knowledge engineering, pairing large language models with knowledge graphs and ontologies so the result stays interpretable, evidence-checked, and ready to reuse.

aryand@ksu.edu github.com/aryand1 linkedin
Knowledge Graphs Neurosymbolic AI Computer Vision Trustworthy AI Ontology Engineering the researcher

Publications

peer-reviewed, patents & more
Peer-reviewed
  1. OLIVE: Ontology Learning with Integrated Vector Embeddings ↗
    Yinglun Zhang, Aryan Singh Dalal, Caleb Martin, Srikar Reddy Gadusu, Hande Küçük McGinty
    Applied Ontology 20(1), 36–53 · 2025
  2. WiseOWL: Evaluating Ontological Descriptiveness and Semantic Correctness for Ontology Reuse ↗
    A. S. Dalal, H. McGinty
    IEEE Intl. Conference on Semantic Computing (ICSC 2026) · 2026
  3. GLIIDE: Global-Local Image Integration via Descriptive Extraction ↗
    Aryan Singh Dalal, Soheil Abadifard, Hande Küçük McGinty
    K-CAP '25, Dayton, OH · Dec 2025
  4. Echo-LLM: Evidence-Checked Hierarchical Ontology ↗
    Aryan Singh Dalal, Hande McGinty
    Open Conference Proceedings, Vol. 8 · 2026
  5. Examining Condensation and Freezing Behavior on a Laser-Patterned Metallic Surface Using an AI Neural Network Model ↗
    Jane C. Turner, Aryan Singh Dalal, Hande Küçük McGinty, Melanie M. Derby, Amy R. Betz
    Frontiers in Thermal Engineering 6 · 2026
  6. Computer Vision Based Automated Quantification of Agricultural Sprayers Boom Displacement ↗
    Aryan Singh Dalal, Sidharth Rai, Rahul Singh, Treman Singh Kaloya, Rahul Harsha Cheppally, Ajay Sharda
    Computers and Electronics in Agriculture 243 · 2026
  7. Enhancing Seeding Efficiency Using a Computer Vision System to Monitor Furrow Quality in Real-Time ↗
    Sidharth Rai, R. Slichter, A. Dalal, Ajay Sharda
    Precision Agriculture '25, pp. 1038–1044, Wageningen Academic · 2025
In press & submitted
  1. PERSEUS: Perceptual Semantic Extraction and Unified System submitted
    Aryan Singh Dalal, H. K. McGinty
    Extended Semantic Web Conference (ESWC 2026) · 2026
  2. Nurture KG: Navigating Urban Resilience through Urban Food Ecosystems Using Knowledge Graphs in press
    A. S. Dalal, H. K. McGinty
    Urban Food Symposium · 2024
Thesis
  1. Quantifying Target Movement Using Neural Networks ↗
    Aryan Singh Dalal
    M.S. Thesis, Kansas State University · 2023
Patent
  1. System and Method for an Agricultural Machine ↗
    Aryan Singh Dalal et al.
    U.S. Patent 12,490,733 B2 · issued Dec 2025
Selected posters & demos
  • Oct 2025WiseOWL: Evaluating Ontological Descriptiveness and Semantic Correctness · MINK-WIC, Kansas City
  • Oct 2025Drop to Data (D2D): Neural Networks for Water and Ice Droplet Analysis · AI Symposium, K-State
  • Jul 2024Quantifying Boom Movement in Agricultural Sprayers Using Neural Networks · ASABE Annual Meeting
  • Jun 2024Nurture KG: Urban Resilience through Urban Food Ecosystems · Urban Food System Symposium
  • Oct 2023Distance Quantifier System · AI Symposium, K-State

Full record on Google Scholar.

Selected Projects

5 research systems
DOD-funded · social media + public health

SparKG

An automated system that turns social media into a real-time public-health monitor for emerging drug trends. It pulls posts, comments, and videos from Reddit, TikTok, and YouTube, then reads them with transformer models, OCR, and speech recognition to catch both explicit and subtle signals. Captions, transcripts, hashtags, and on-screen text merge into single records. A risk-scoring module flags high-risk or viral content, behavioral ontologies interpret substance mentions and psychological cues, and an interactive dashboard surfaces trends from daily spikes to long-range patterns.

SparKG dashboard with a bar chart of most-mentioned drugs and a category breakdown
Dashboard displaying drug analyses
SparKG dashboard charting drug mentions over a one-month window
Recent drugs trending over one month
NSF-funded · space systems + computer vision

Water Condensation

Neural networks that study how water and ice droplets form and behave in normal and microgravity conditions, where nucleation is hard to observe by traditional means. The pipeline processes large sets of experimental imagery to quantify droplet growth, coalescence, and freezing. Hand-annotated data trained a neural analysis interface (NAI) that detects and measures droplet dynamics, and a knowledge graph links the observed behavior to the underlying physics. It ships as a cloud-based, open-source module that accepts both image and video input, replacing a slow manual process with scalable analysis for aerospace and heat-transfer research.

Instance-segmentation overlay marking detected water and ice droplets
Instance segmentation of detected water and ice
Line charts tracking ice and water counts over time with freezing patterns
Time analysis of counts with freezing-pattern detection
multimodal · submitted to ESWC 2026

PERSEUS

A method for building reliable ontologies from mixed sources while catching the hallucinations that large language models introduce. A cross-modal validation pipeline runs consistency checks across text, image, and audio, verifying LLM-inferred relations against metadata and semantic labels. An interactive interface lets people inspect, refine, and approve ontology graphs as they go. The feedback loop raised ontology accuracy by 11% over standard LLM-only methods and made multimodal ontology construction a transparent, user-guided process.

Ontology editor view of an ontology built with PERSEUS from an image
Ontology built with PERSEUS from an image
Node-link graph visualization of the resulting ontology
Graph visualization of the ontology
ontology evaluation · submitted to ICSC 2026

WiseOWL

An ontology validation tool that scores any ontology or knowledge graph across four metrics: entity-description quality, semantic connectivity between descriptions and entities, connection richness, and the depth and balance of the class hierarchy. It reports each score plus an average, and automatically flags any metric below 40%. Where it finds gaps, it suggests concrete next steps, such as clarifying descriptions, adding relational links, or rebalancing the hierarchy, so a raw validation result becomes a clear plan for improving reuse.

WiseOWL interface showing four circular metric scores and an average for a FOAF ontology
Evaluation scores on the FOAF ontology
tool · LLM + Neo4j · published

OLIVE

A semi-automated system that makes ontology building faster and easier to manage. Instead of experts defining every relationship by hand, OLIVE pairs large language models (ChatGPT and LLaMA) with the Neo4j graph database to generate and organize relationships from structured and unstructured data. People enter concepts or short prompts, and OLIVE assembles a knowledge graph showing how they connect, visualized live through WebVOWL. Experts review and correct results in the same interface. Validation with Protégé's reasoner and the OOPS! pitfall scanner confirmed logically sound output, and the workflow cut the time to build an ontology while improving how precisely relationships are captured.

OLIVE interface for creating and extending graphs from prompts
OLIVE interface
Generated ontology visualized as a node-link graph in WebVOWL
Generated ontology in WebVOWL

Experience

education · research · talks · service
Education
  • Present
    PhD in Computer Science · Kansas State University

    Trustworthy knowledge engineering with large language models: knowledge graphs, ontology learning, ontology evaluation, and applied AI systems.

  • Dec 2023
    M.S. in Computer Science · Kansas State University

    Thesis: Quantifying Target Movement Using Neural Networks.

  • May 2021
    B.Tech in Computer Science · Maharshi Dayanand University, Rohtak, India
Research appointments
  • Jan 2024 to Dec 2025
    Graduate Research Assistant, KONCORDANT Lab · K-State, Computer Science

    Built and evaluated methods for LLM-assisted ontology learning, knowledge graph construction, semantic validation, and evidence-aware knowledge engineering. Worked on ontology reuse and recommendation, multimodal knowledge graphs, and hallucination mitigation, and coordinated interdisciplinary projects across AI, agriculture, food systems, and space systems.

  • May 2022 to Dec 2023
    Graduate Research Assistant, FARMS Lab · Kansas State University

    Developed computer vision and machine learning methods for agricultural systems, including automated quantification of sprayer boom displacement, and supported grant writing and interdisciplinary research.

  • Jan to Aug 2021
    Student Intern · Tech Saksham

    Applied machine learning project on image-based prediction and COVID-19 safety monitoring.

Invited talks
  • 20 July 2026 · in person
    From Generation to Verification: A Neuro-Symbolic Approach to Trustworthy AI · Sharda University, Greater Noida, India

    Guest lecture hosted by Dr. Sanju Tiwari. Covered how neural methods generate knowledge while symbolic methods decide what can be trusted, drawing on the OLIVE, PERSEUS, and WiseOWL systems.

  • 9 July 2026 · virtual
    Trust, but Verify: Neurosymbolic Knowledge Graph Construction from Text, Speech, and Images · Indian Institute of Technology Palakkad, India

    Research seminar hosted by Dr. Raghava Mutharaju for master's and doctoral students, with additional participants joining remotely from Delhi. Led to ongoing collaboration discussions with the KONCORDANT Lab on using textual evidence for ontology development and knowledge graph enrichment.

  • 30 June 2026 · virtual
    Trust, but Verify: Neurosymbolic Knowledge Graph Construction from Text, Speech, and Images · KASTLE Lab Speaker Series, Wright State University

    Featured speaker, invited by Dr. Cogan Shimizu, Director of the Knowledge and Semantic Technologies Lab, on automated knowledge graph construction and Neo4j-based deployment. Delivered to an international audience of academic researchers, industry practitioners, and early-career professionals.

Academic service & reviewing
  • May 2026General Co-chair, LLMS4KGOE 2026, the first workshop on LLM-driven Knowledge Graph and Ontology Engineering · co-located with ESWC 2026
  • 2026Editor, Joint Proceedings of LLMS4KGOE 2026 and ELMKE 2026 · ESWC 2026, Dubrovnik
  • May 2026Organizer, judge, and research-talk moderator, 4th Kansas Data Science Conference (KDSC 2026) · Manhattan, KS
  • Apr 2026Program Committee, The Web Conference · WWW 2026
  • Nov 2025Editor and Program Committee, 16th Workshop on Ontology Design and Patterns (WOP 2025) · ISWC 2025
  • Nov 2025Editor, HAIBRIDGE 2025, bridging hybrid AI and the Semantic Web · ISWC 2025
  • Sep 2025Reviewer, International Conference on Biomedical Ontologies · ICBO 2025
  • Feb 2025Reviewer, AAAI/ACM Conference on AI, Ethics, and Society · AIES-25
Toolkit
Knowledge GraphsOntology EngineeringSemantic WebRDFOWLSPARQLNeo4jGraph Data ScienceLLMsMachine LearningDeep LearningComputer VisionPythonData Analytics

Teaching

instruction & mentoring
Courses
  • Jan 2026 to present
    Graduate Teaching Assistant, Knowledge Graphs for AI (CIS 890) · Kansas State University

    Supports graduate instruction in knowledge graphs, semantic technologies, and AI systems.

  • Jul 2025
    Guest Lecturer, Advanced Algorithms (CIS 775) · Kansas State University

    Delivered guest lectures for a graduate-level computer science course under Prof. Dr. Hande Küçük McGinty.

  • May 2021 to May 2022
    Graduate Teaching Assistant, Database System Concepts (CIS 560) · Kansas State University

    Supported instruction and grading, and ran lab tutorials on SQL and MySQL.

Mentoring
  • 2026
    Mentor, ASA DataFest

    Mentored undergraduate teams on data analysis, modeling strategy, and presentation.

  • Student research mentoring

    Guided undergraduate students across knowledge graph, applied AI, and data science projects.

Awards

honors & certifications
Aryan Singh Dalal being recognized on stage at Kansas State University
Recognized at Kansas State University
Honors
  • May 2026Best Judge Award, 4th Kansas Data Science Conference · KDSC 2026
  • Dec 2025Graduate Student of the Month · Kansas State University
  • Oct 2025Graduate Travel Award, $500 · Kansas State University
  • May 2024Graduate Travel Award, $450 · Kansas State University
  • Apr 2024Graduate Travel Award, $400 · Kansas State University
  • Feb 2018Second Position, Paper Presentation · Dronacharya College of Engineering
  • Sep 2017First Position, Paper Presentation · Dronacharya College of Engineering
Certifications
  • Feb 2026Neo4j Graph Data Science Certification · Neo4j
  • Jan 2026Graph Data Modeling Fundamentals · Neo4j

Get in touch

open to research + roles

Happy to talk research, collaboration, or what comes next.

email aryand@ksu.edu aryan.dalal79@gmail.com
linkedin linkedin.com/in/aryan-singh-dalal
github github.com/aryand1
labs Koncordant Lab DaSe Lab, K-State CS FARMS Lab, K-State
Eroded sandstone ridges raking into late light, a study in structure
Structure, everywhere you look.