Rosen Center for Advanced Computing
Purdue Logo
Quick links
Helpful links

Ashish

Ashish's Profile Photo

Senior Research Data Scientist

  • ashish@purdue.edu
  • Artificial Intelligence, Generative AI, Machine Learning, Applied Data Science, High-Performance Computing (HPC), AI Systems for Research and Education

Ashish is a Senior Research Data Scientist at Purdue University's Rosen Center for Advanced Computing (RCAC), where he leads the university's generative AI strategy and was a co-founder and original architect of two of Purdue's flagship AI platforms — Purdue GenAI Studio and ANVILGPT. What began as his early vision for secure, privacy-focused GenAI infrastructure at Purdue has grown into platforms adopted by over 3,500 users spanning research, instruction, and administrative units across campus.

At RCAC, Ashish leads and manages Purdue's internal AI consulting practice, providing cross-departmental guidance on applied AI integration, data science strategy, and grant development. He has collaborated on funded, submitted, and in-preparation grants exceeding $3 million across the NSF, USDA, Amazon Research Awards, and private endowments, serving as Co-PI or Lead on projects spanning AI literacy education, cybersecurity training, VR-based professional development, genomic AI pipelines, adaptive learning systems, and AI-enhanced undergraduate research mentorship.

Ashish has designed and delivered over 100 hours of advanced AI and data science training for Purdue faculty, staff, graduate students, and researchers — covering topics ranging from LLMs and prompt engineering to RAG architectures, model fine-tuning, agentic workflows, and real-world ML deployment. He has presented at major venues including Purdue AI Day, the EMBRIO Summer School, and the MS-CC Workshop at Clark Atlanta University, and regularly delivers instruction through the RCAC Training Series and the Graduate Research Information Program (DVELoP, Purdue Libraries).

Ashish has been a consistent mentor across Purdue's research and capstone programs. Through the Anvil NSF REU Program, he co-led the development of TROUT — a hybrid neural network CLI tool for HPC job queue time prediction — resulting in an accepted paper at SC. He subsequently served as lead mentor on the CLiFF pipeline project, an automated FAQ generation system built from 2,600+ HPC support tickets using LoRA fine-tuned Mistral-7B, sentence embeddings, and Phi-4-based FAQ generation, with the resulting paper accepted at SC HUST. He is co-leading SciAgents — a planned REU initiative to prototype coordinated AI agents for end-to-end scientific discovery and reproducibility. Through Purdue's IE 431 Senior Capstone Program, he has mentored teams on HPC predictive maintenance and operational intelligence, culminating in the SupportOps Intelligence Hub — an integrated platform combining ticket volume forecasting, ML-based ticket routing, an LLM-powered staff training simulator, and a unified supervisor dashboard built on top of TicketHub.

His research contributions extend to geospatial and environmental modeling, pharmaceutical data science, and statistical consulting. He led 3D hypoxia modeling for the Lake Erie Hypoxia Project using ArcGIS and Python, supported pharmaceutical crystallization studies using Bayesian GLMs and hurdle models, conducted longitudinal social network analyses of health coalitions, and developed hyperspectral nitrogen prediction pipelines for agronomic applications. He serves as a reviewer for the PEARC Conference, evaluating submissions in applied AI and cyberinfrastructure.

Prior to his current role, Ashish served as a Statistical Consultant in Purdue's Department of Statistics, guiding over 20 cross-disciplinary research projects with a 95% client success rate, applying advanced multivariate modeling, longitudinal analysis, Monte Carlo simulations, and experimental design across a wide range of disciplines.

Education

MS, Joint Computer Science – Statistics, Purdue University BS, Applied Statistics & Applied Mathematics, Purdue University MS, Finance and Management, Harvard Extension School (In Progress)

Grant-Funded Projects

Active / Funded

  • AI-Driven DNA Primer Design and Evaluation System — USDA APHIS ($2.7M) | PI: Dr. Mohit Verma | Role: Project Advisor & Oversight Lead (Completed)
  • AI in Teaching and Learning – VR Networking Simulation — Innovation Hub / Lilly Endowment ($80,000) | PI: Dr. Shinyong Jung | Role: Co-PI (Completed)
  • Enhancing World Readiness with Bespoke Interpersonal Guide (BIG) — Office of the Provost ($89,150) | PI: Dr. Aparajita Jaiswal | Role: Co-PI (Completed)
  • AI-Enhanced Critical Reflection for Purdue Undergraduate Researchers — Innovation Hub ($30,000) | PI: Dr. Amy Childress | Role: Co-PI & AI/Backend Development Lead. Built an AI-driven reflection chatbot integrated into Purdue's OURConnect platform, guiding undergraduate researchers in articulating career readiness competencies and generating resume and LinkedIn content. (Completed)
  • ML-Cybersecurity CyberTraining – Project ACE — NSF ($60,000 over 3 years) | PI: Dr. Baijian Yang | Role: Lead Training Coordinator (In Progress)

Submitted / Pending

  • The Next Big Question (NBQ): Adaptive, Inquiry-Driven AI Literacy for the 21st-Century Classroom — NSF RITEL | PI: Dr. Javier Gomez-Lavin | Role: Co-PI & Adaptive Systems Lead. Co-leads design of the adaptive AI content-delivery system, Bayesian learner-state modeling, multi-institution scalability, and the AI-engagement quality classifier.
  • Clarify, Compose, Code: A Self-Questioning Framework for Agentic AI Workflows — Amazon Research Awards | PI: Dr. Julia Rayz | Role: Co-PI. Co-leads design of a self-questioning agentic AI framework with dynamic clarification loops and AWS-native orchestration, evaluated in NLP and Data Structures & Algorithms courses. (Submitted — Awaiting Decision)
  • AI-Driven Decision Simulations for Spreadsheet Modeling Education — NSF IUSE Level 1 | PI: Prateek Jaiswal | Role: Co-PI. Multi-agent AI persona environment embedded in a semester-long semiconductor supply-chain simulation across 16 AI personas. (In Preparation)
  • Human-AI Coaching Agents for Risk Analysis — NSF Early CAREER | PI: Dr. Gaurav Nanda | Role: Senior Personnel
  • Human-AI Conversational Agents for Professional Development — JMHC Research Breakthrough Award | PI: Dr. Cho Hyun Park & Dr. Shinyong Jung | Role: Co-PI

Publications

Accepted / Published

  • Ashish, A., Jaiswal, A., Vhaduri, S., Nerella, N., & Jha, S. Empa: An AI-Powered Virtual Mentor for Developing Global Collaboration Skills in HPC Education. arXiv:2511.17669.
  • Joslin, C., Burns, D., Ashish, & Barezi, E. J. Generating Frequently Asked Questions from Technical Support Tickets using Large Language Models. HUST at SC.
  • Rodenbeck, S., Gough, E., Ashish, et al. Providing On-Prem GenAI Inference Services to a Campus Community. PEARC, Columbus, OH.
  • Lovell, A., Wisniewski, P., Rodenbeck, S., & Ashish. A Hierarchical Deep Learning Approach for Predicting Job Queue Times in HPC Systems. HUST at SC, pp. 621–628. DOI: 10.1109/SCW63240.2024.00086
  • Rodenbeck, S., Gough, E., Ashish, et al. An Introductory Guide to Developing GenAI Services for Higher Education. Gateways Conference, Article 23. DOI: 10.5281/zenodo.13864404

Accepted — Forthcoming

  • Jaiswal, A., & Ashish. AI as a collaborative partner: EMPA's role in supporting reflective teamwork learning. Accepted, ISLS Annual Meeting, CSCL Track.
  • Jaiswal, A., & Ashish. AI-mediated metacognition for global teamwork. Accepted, ASEE Annual Conference & Exposition.
  • Ashish & Jaiswal, A. Generative AI for Curriculum Design and AI-Driven Mentoring Systems in Higher Education. Full chapter accepted in AI in Cybersecurity Higher Education: Innovation, Ethics and Practice.

In Progress

  • Ashish. SupportOps Intelligence Hub: Forecasting Ticket Volume and Intelligent Assignment for Research Computing Support. Planned submission to HUST at SC, PEARC, US-RSE, or IEEE eScience.

Selected Presentations

  • "Foundations of Generative AI: Basic Theory and Use Cases." Purdue AI Day.
  • "Prompt Engineering for Generative AI." Purdue AI Day.
  • "Fine-Tuning and Retrieval-Augmented Generation (RAG)." Purdue AI Day.
  • "Agentic Workflows: Building Task-Oriented AI Systems." Purdue AI Day.
  • "Integrating Generative AI into Software and APIs." Purdue AI Day.
  • "AI in Research Tutorial Series." EMBRIO Summer School, Purdue University.
  • "Building Resilient Futures Through Cyberinfrastructure." MS-CC Workshop, Clark Atlanta University.
  • "Love Data: The Secret Lives of Algorithms." Purdue Libraries + Institutional Data Analytics.
  • "Enhancing Generative AI with Retrieval Augmented Generation." RCAC Training Series.
  • "Generative AI Series Parts 1–3: Prompt Engineering, Architecture & Mechanics, and Custom Model Tuning." RCAC Training Series.
  • "AI Day: Prompt Engineering, RAG, Agents, Fine-Tuning." Purdue AI Training Series.
  • "AI Bytes Sessions 1 & 2." RCAC Training Series.

Engagement

  • Reviewer, PEARC Conference (Applied AI & Cyberinfrastructure track)
  • Co-PI & Adaptive Systems Lead, NSF RITEL – The Next Big Question (NBQ) (Submitted)
  • Co-PI, Amazon Research Awards – Clarify, Compose, Code (Submitted)
  • Co-PI, NSF IUSE – AI-Driven Decision Simulations for Spreadsheet Modeling Education (In Preparation)
  • Lead Training Coordinator, NSF CyberTraining Project ACE
  • Lead Mentor, Anvil NSF REU Program
  • Co-Lead, SciAgents REU Initiative (Planned)
  • Lead Mentor, IE 431 Senior Capstone Program, Purdue University
  • Graduate Assistant, DVELoP (Data Visualization Experience Laboratory of Purdue), Purdue Libraries