- Reporting to Reinier Van Mourik (Senior Scientist, Software & Data Science).
- Designing and implementing a physics-informed machine learning model to predict properties of accelerated electron bunches from laser and plasma parameters in laser-plasma wakefield accelerators.
- Building the associated data preprocessing and feature-engineering pipeline.
- Developing strategies for the model to handle day-to-day variation in accelerator operation, and an ML-assisted optimization loop to automate start-up and tuning of the accelerator.
Personal
Private email: gurukalyan1.618@gmail.com
Professional email: gjayasingh@ucsd.edu
UC San Diego, Department of Physics, 9500 Gilman Drive, La Jolla CA 92093, USA
Present Position
Ph.D. Candidate in Theoretical Physics, University of California San Diego (2022–present).
Honors and Achievements
- Institute Silver Medal, IIT Bombay (2022) – Awarded to the top-ranked student in the graduating class of each academic program.
- K. Seshia Research Excellence Award, IIT Bombay (2022) – Given to the best Master's thesis in Physics for research originality and rigor.
- Physics Excellence Award, Department of Physics, University of California San Diego.
- Institute Academic Prizes, IIT Bombay (2019, 2021) – Annual award for the highest GPA in the Physics Department.
- Aalto Science Institute (AScI) Fellowship, Finland (2020) – International research fellowship for top students in science and engineering.
- Indian Young Physicists' League (IYPL) – All-India Rank 3 (2021), national theoretical physics competition.
- KVPY Fellowship, Department of Science & Technology, India (2017) – Prestigious national fellowship for the top ~1% of science students with research potential.
Professional Experience
- Conducting research with Prof. Nigel Goldenfeld on the statistical mechanics of turbulence and non-equilibrium phase transitions.
- Demonstrated that the laminar–turbulent transition in pipe flows with body forces is governed by tricritical directed percolation, published in Physical Review Letters.
- Currently working on problems related to wave turbulence, transitions to turbulence in shear flows, and stochasticity in turbulent fluids.
- Completed Dual Degree (B.Tech + M.Tech) in Engineering Physics with specialization in Nanoscience.
- Master's thesis: Topological Insulator–Superconductor Junctions under Prof. Hridis K. Pal.
- Conducted theoretical and computational work on superconductivity and topological quantum matter.
- Worked with Prof. Rajdeep Sensarma on electron–phonon equilibration within the Keldysh field-theoretic framework.
- Selected for the prestigious AScI International Internship Program.
- Investigated fluctuations in non-centrosymmetric superconductors under Dr. Alexander Zyuzin, studying the effects of spin–orbit coupling on thermodynamic observables.
- Extended this work into my bachelor's thesis, which also investigated odd-parity superconductors.
- Supervised by Dr. Sutanu Roy; studied Banach spaces, fixed-point theorems, and mathematical formulations of Google's PageRank algorithm.
Research Interests
Fluid Mechanics and Turbulence · Non-Equilibrium Statistical Mechanics · Condensed Matter · Machine Learning for Physical Sciences · AI for Physics
Publications
- G. K. Jayasingh & N. Goldenfeld (2025) — Tricritical directed percolation controls the laminar–turbulent transition in pipes with body forces, Physical Review Letters (2025).
- S. Chakraborty, G. K. Jayasingh, H. Pal (2025) — Topological bound states inhibit superconducting order in quasi-one-dimensional heterostructures (manuscript in preparation).
Education

Advisor: Prof. Nigel Goldenfeld. Focus: Statistical Mechanics of Turbulent Phenomena.
Specialization: Nanoscience · GPA 9.44 / 10.
Honors: Institute Silver Medal, K. Seshia Research Excellence Award, Institute Academic Prizes (2019, 2021).
Research Experience
- Developed a stochastic model to describe the laminar-to-turbulent transition as a non-equilibrium phase transition in flows with body forces.
- Predicted a tricritical fixed point governing turbulence in curved and heated pipes.
- Constructed a phase diagram linking body-force strength to directed-percolation universality classes.
- Provided scaling predictions for future experimental verification.
- Investigated self-consistent electron–phonon dynamics within the Keldysh formalism, beyond the standard static-bath approximation.
- Wrote extensive and modular Python (& Julia) codes for evolving the coupled system; tested constituents by connecting them to baths and studying equilibration characteristics from specific initial conditions.
- Extended Ginzburg–Landau theory to spin–orbit-coupled superconductors lacking inversion symmetry.
- Analyzed fluctuation effects on magnetic susceptibility and specific heat near critical temperature.
- Modeled superconductor–topological insulator and superconductor–metal junctions using quasi-classical Green's function methods to study critical temperature, critical fields, and the influence of surface states on superconductivity.
- Derived a non-local Ginzburg–Landau functional for the order parameter, and investigated the effects of topology in superconductor–topological insulator heterostructures.
Talks and Presentations
Presented results on tricritical turbulence scaling in flows under body forces.
Invited talk on statistical mechanics of turbulence and universality in boundary-driven flows.
Discussed dimensional reduction and low-rank structure in complex systems. Slides.
Classification of order parameters within a generalized BCS theory and the nature of physical observables for different pairing symmetries.
Two-part seminar deriving bosonization identities and their application to transport in Luttinger liquids.
Teaching and Academic Service
- Supported undergraduate and graduate courses including:
- Emergent States of Matter (twice; graduate course, Prof. Nigel Goldenfeld).
- Phys 1 & Phys 2 series — Mechanics, Electromagnetism, and hands-on labs covering Waves and Oscillations.
- Led weekly discussion sections, held office hours, and assisted with grading and logistics.
- Served as TA for undergraduate and graduate courses: Statistical Physics, Advanced Statistical Mechanics, Complex Analysis, Electromagnetism.
- Conducted weekly tutorials; assisted with examinations, grading, and curating practice problems.
Leadership and Organization
- Led a 5-member team organizing lectures, workshops, and outreach for a 400-member campus community and 9,000+ online followers.
- Coordinated visits including the Atomic Physics and Quantum Optics Lab at IISER Pune; managed campus-wide experimental physics competitions.
Technical Skills
- Programming: Python · C/C++ (working familiarity) · PyTorch
- Libraries: NumPy · SciPy · scikit-learn · Pandas · Numba · Matplotlib · Seaborn
- Tools: LaTeX · Mathematica · Git · Jupyter · Markdown
- Methods: Stochastic Modeling · Monte Carlo Simulation · Machine Learning · Statistical Analysis
Selected Coursework
- Physics: Advanced Statistical Mechanics · Condensed Matter Theory · Quantum Field Theory · Topological Aspects of Quantum Matter · Nonlinear Dynamics
- Mathematics: Group Theory · Complex Analysis · Differential Equations · Numerical Analysis
- Computational: Machine Learning · Programming · Data Analysis
Extracurricular and Outreach
- Invited speaker for "Why a Maths and Physics Club?" — Advanced Pedagogy Workshop (TEQIP-KITE III, 2019). Addressed over 100 college-level mathematics faculty from across India as part of an Advanced Pedagogy Workshop under the aegis of the World Bank and the Government of India.
Last updated: March 2026.