About
Rajiv Chaitanya M. Final-year CS undergrad at DSCE Bengaluru with a minor in Economics and Finance. Most of my work sits at the intersection of reinforcement learning, graph learning, and sequential decision-making, with applications to financial markets, macro-financial systemic risk, and biomedical signal processing.
Six conference papers, two manuscripts under journal review, three working papers, sole or first author throughout. One Best Paper Award (ICEI 2025) and one Best Paper Candidate selection (ICEdge 2025). Reviewer for IEEE WCCI 2026 (CEC track) and IEEE AISIIS 2026.
Currently a research intern at Indiana University Bloomington (biomedical imaging, until May 2026) and a part-time econometrics intern at JSPM University.
Research focus
- Reinforcement learning. Policy-gradient methods under non-stationarity (ARISE), reward-aware document selection in edge RAG (SRAS), and inverse RL for decoding black-box trading strategies (RRR).
- Graph learning. Streaming graph partitioning under drift (RAMP), meta-learning GNNs over correlation graphs (MetaGraph), and spatio-temporal forecasting on real grids (GridCast).
- Quantitative finance and macro risk. Drawdown-aware allocation (REBOUND) and sovereign wealth funds as dynamic risk systems (SWF, under review at the Journal of Economic Surveys).
Education
BE, Computer Science and Engineering
Dayananda Sagar College of Engineering (DSCE)
Minor in Economics and Finance. CGPA 9.63 / 10.0.
Open to PhD positions and quant or risk-management roles. If any of the above is your problem too, send a note.
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