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Aditya More

Career & Experience

Professional Experience

From enterprise software engineering to applied machine learning and AI systems — experience building, testing, and scaling real-world solutions.

Clemson University

Researcher - LLM Agents and Human Behavior

Clemson University

Clemson, SC / Remote
Apr 2026 – Present
ResearchLLM Agents & Human Behavior · School of Computing

Research Areas

Large Language Models · LLM Agents · Multi-Agent Systems · Generative AI · Human Behavior Simulation · AI Evaluation

Conducting research under Dr. Long Cheng on whether societies of Large Language Model agents can realistically simulate human behavior and support early-stage behavioral studies.

Research & Contributions

  • Researching whether societies of LLM agents can substitute for human participants in behavioral pilot studies.
  • Reproducing published behavioral experiments and designing new studies with AgentSociety, YuLan-OneSim, Generative Agents, and related multi-agent frameworks.
  • Developing a taxonomy and metrics for behavioral realism, consistency, and human alignment across decision-making and social scenarios.
  • Designing and reproducing behavioral experiments such as Trust Games and Dictator Games to compare LLM-agent decisions against established human behavioral data.
  • Exploring evaluation methods and benchmarks for quantifying behavioral realism, consistency, and human-agent similarity.
  • Building toward a research survey on the strengths and limitations of LLM agents for simulating human behavior, including their potential role in early-stage studies.

Technologies & Research Tools

PythonLarge Language ModelsMulti-Agent SystemsAgentSocietyYuLan-OneSimGenerative AgentsMiroFishLiterature ReviewExperimental DesignBehavioral Evaluation
Clemson University

Graduate Teaching Assistant

Clemson University

Clemson, SC, USA
Aug 2024 – Dec 2025
TeachingApplied Data Science · School of Computing
  • Designed Jupyter labs and assignments covering data preprocessing, supervised learning, unsupervised learning, model evaluation, and visualization
  • Built automated grading pipelines with Python and nbgrader to improve scoring consistency and reduce manual effort
  • Maintained live course infrastructure and resolved notebook and autograder issues
  • Explained machine-learning concepts and debugged student code during office hours
  • Collaborated with faculty on curriculum design and course deployment on Coursera
  • Debugged and resolved autograder and grading pipeline issues via Salesforce tickets, implementing fixes, validating outputs, and deploying updated notebook versions
PythonJupyterscikit-learnPandasNumPy
Amdocs

Software Test Engineer

Amdocs

Pune, India
Oct 2021 – Dec 2022
Software Engineering & QASoftware Quality Engineering · Telecom Systems
  • Performed end-to-end, regression, and integration testing for enterprise telecom systems supporting AT&T
  • Designed test cases and validation strategies for new feature releases based on product requirements and stakeholder discussions
  • Ran functional, UI, and API release tests with Selenium and Postman
  • Collaborated with cross-functional global teams (US & India) in Agile environments to ensure smooth release cycles
  • Participated in feature planning, requirement analysis, and system validation across multiple production releases
PostmanSelenium