import torchfrom sklearn.pipeline import Pipelinemodel = TransformerEncoder(layers=12, heads=8)embeddings = vector_store.similarity_search(query)loss.backward(); optimizer.step()predictions = model(tokens).softmax(dim=-1)agent.plan(task).execute(memory=retriever)features = StandardScaler().fit_transform(dataset)with torch.no_grad(): response = llm.generate(prompt)metrics = evaluate(model, validation_loader)
Athikash Jeyaganthan
#about#resume#portfolio#contacts

Portfolio

My Projects So Far

A tighter set of case studies, product concepts, and builds.

corefinemain
AI Full-Stack

Co-Refine

An AI-augmented qualitative coding platform that helps researchers maintain coding consistency through real-time audit alerts, deterministic embedding similarity, constrained LLM feedback, visual analytics, and collaborative inter-coder reliability workflows.

qvalueheatmaps
Reinforcement Learning

Pay the Spread or Earn It: Reward Specification Shapes Execution Policy in RL Limit-Order Traders

Built and evaluated Double DQN limit-order trading agents in the Bristol Stock Exchange simulator to test how reward design changes execution behaviour. The study showed that surplus-based rewards produced a more disciplined “earn the spread” policy with a higher Sharpe ratio, while profit-based rewards encouraged aggressive spread-crossing and more trades but weaker risk-adjusted returns.

auth-lens-main
AI Full-Stack

AuthLens - Prior Authorisation Evidence Copilot

AuthLens is a full-stack AI workflow platform that helps healthcare teams prepare prior authorization and appeal packets from synthetic or de-identified PDFs. It turns payer policies, denial letters, and patient-supporting documents into structured criteria, evidence matches, readiness reports, citation-checked drafts, audit logs, and exportable review packets.

Athikash Jeyaganthanathikashj@gmail.com

Software / AI Engineer

Media