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Subject Matter Expert – Mathematics (AI Training)
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Demonstrated experience with LaTeX.
Demonstrated experience with Python.
Demonstrated experience with SymPy.
Demonstrated experience with NumPy.
Demonstrated experience with SageMath.
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Subject Matter Expert – Mathematics (AI Training) open to new opportunities
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Subject Matter Expert – Mathematics (AI Training)
Wrote 1,400+ original problems with complete step-by-step reference solutions in LaTeX, spanning olympiad, Putnam, qualifying-exam and research-adjacent difficulty, for supervised fine-tuning and RL reward data.. Graded and ranked model-generated proofs against structured rubrics; flagged circular reasoning, unjustified limit and summation interchanges, silent domain assumptions, misapplied theorem hypotheses and fabricated citations.. Built multi-step grading rubrics for open-ended proof tasks and calibrated them across annotator cohorts, raising inter-annotator agreement from 0.71 to 0.92 on pilot batches.. Red-teamed reasoning models with false-premise questions, near-miss counterexamples, non-standard notation and edge-case hypotheses to surface systematic failure modes.. Wrote SymPy and NumPy scripts to machine-check final answers and symbolic simplifications; formalised selected lemmas in Lean 4 (mathlib) for proof-level verification.. Senior reviewer on peer submissions with a 96% first-pass acceptance rate; mentored eight new contributors on rigour, notation and ambiguity removal.
Postdoctoral Fellow – Department of Mathematics
Independent research programme in spectral graph theory and extremal combinatorics; produced two journal articles and presented at four national conferences.. Co-supervised two M.Sc. dissertations and ran a weekly reading seminar on eigenvalue methods in combinatorics.
Postdoctoral Fellow – Department of Mathematics
Collaborative work on algebraic combinatorics and its algorithmic applications, resulting in one published article and one preprint.
Visiting Researcher – Department of Mathematics
Short-term research visit on eigenvalue interlacing techniques; delivered two invited seminars and tutored at an instructional workshop on graph spectra.
Assistant Professor – Department of Mathematics
Taught Real Analysis, Linear Algebra, Abstract Algebra and Discrete Mathematics to undergraduate and postgraduate cohorts of 40–110 students.. Authored problem sets, internal assessments and end-semester papers with full solution keys; served on the departmental curriculum revision committee.
Visiting Faculty – Department of Mathematics
Delivered Probability & Statistics, Numerical Methods and Graph Theory; mentored six B.Tech. capstone projects and coordinated assessment design.