AIAC operates under academic faculty oversight and autonomous student council governance. Research pods are anchored by senior student leads who coordinate weekly experiments with undergraduate researchers.
Department of Computer Science & Engineering
Provides institutional supervision, research integrity validation, curriculum alignment, and publication oversight across all AIAC student research squads.
Industry Advisory Tier (15+ Yrs Industry Exp)
Oversees large-scale system topology, hardware feasibility constraints, production benchmarking integrity, and software delivery standards.
Industry Advisory Tier (3+ Yrs Applied AI Exp)
Guides weekly engineering sprints, reviews technical pull requests, enforces Pydantic schemas, and mentors squad members on code quality.
Four independent student councils inspect code quality, benchmark validity, training dataset licensing, and documentation standards across all pods.
Student Lead · Systems & Infrastructure Council
Oversees GPU testbed availability, Docker environment standards, and repository CI/CD runners across all pods.
Student Lead · ML Rigor & Benchmarking Council
Audits baseline evaluation protocols, seed reproducibility, statistical significance checks, and benchmark sanity.
Student Lead · Research Ethics & Lineage Council
Inspects training dataset licenses, model cards, anonymization standards, and environmental compute estimates.
Student Lead · Documentation & Reproducibility Council
Enforces self-contained replication scripts, README documentation standards, and open dataset cataloging.
Senior student researchers responsible for technical direction, PR reviews, and pod milestone execution.
Lead student anchor for Pod 01. Specializes in low-resource Kannada morphology, BPE token boundary analysis, and PEFT adaptation.
Lead student anchor for Pod 02. Leads embedded hardware acceleration experiments, TensorRT engine layer profiling, and edge telemetry.
Lead student anchor for Pod 03. Researches multi-agent consensus protocols, deterministic execution guarantees, and LangGraph runtimes.
Lead student anchor for Pod 04. Investigates continuous biological signal anomaly detection using lightweight 1D temporal networks.
Lead student anchor for Pod 05. Coordinates automated adversarial boundary fuzzing and safety evaluations against open-weight models.
Lead student anchor for Pod 06. Builds self-hosted GPU runner infrastructure, environment replication recipes, and experiment tracking.
| Name | Assigned Pod | Focus & Interests | Role |
|---|---|---|---|
| Aditi S. | Regional NLP & Indic LLMs | NLP Tokenization, Linguistic Morphology | Undergraduate Researcher |
| Bhavana V. | Regional NLP & Indic LLMs | Knowledge Distillation, Calibration Error | Undergraduate Researcher |
| Chetan L. | Edge AI & Vision Systems | Edge Vision, Zero-Copy Buffers | Undergraduate Researcher |
| Deepak G. | Edge AI & Vision Systems | Thermal Profiling, TensorRT Optimization | Undergraduate Researcher |
| Esha N. | Agentic AI & Autonomous Loops | Agentic Frameworks, State Transition Testing | Undergraduate Researcher |
| Farhan A. | Agentic AI & Autonomous Loops | Source Attribution, Vector Indexing | Undergraduate Researcher |
| Kiran R. | Healthcare & Bio-Signals | Biosignal Processing, Wavelet Filtering | Undergraduate Researcher |
| Ananya M. | Secure AI & Model Ethics | Algorithmic Fairness, Disparate Impact Auditing | Undergraduate Researcher |
| Siddharth T. | Systems, HPC & MLOps | Distributed Systems, gRPC Communication | Undergraduate Researcher |
