Skip to main content

Trinity College Dublin, The University of Dublin

Trinity Menu Trinity Search



Dr. Rajarshi Tiwari
Visiting Research Fellow, Physics

Biography

I was born in the city of Allahabad, Uttar Pradesh in India. My early education till High-school of in a small city of Jaunpur in Uttar Pradesh. After that I moved to city of Allahabad for further education.

I did my B.Sc. from University of Allahabad, India in Physics and Mathematics in 2005. I then joined the Integrated PhD (M.Sc. + Ph.D.) program at Harish-Chandra Research Institute (HRI), Allahabad, India. I finished my M.Sc. in Physics from HRI in 2008, and Ph.D. in physics in 2013 with my thesis on "The Effect of Geometric Frustration on Some Correlated Electron Systems". After Ph.D., I joined Prof. Stefano Sanvito's research group at Trinity College, Dublin in 2013.

Publications and Further Research Outputs

Peer-Reviewed Publications

Nelson J., Tiwari R., Sanvito S., Machine-learning semilocal density functional theory for many-body lattice models at zero and finite temperature, Physical Review B, 103, (24), 2021 Journal Article, 2021 TARA - Full Text DOI

Tiwari R., Nelson J., Xu C., Sanvito S., Reactivity of transition-metal alloys to oxygen and sulfur, Physical Review Materials, 5, (8), 2021 Journal Article, 2021 DOI TARA - Full Text

Saket A., Tiwari R., Orbital Mott transition in two dimensional pyrochlore lattice, Journal of Physics Condensed Matter, 32, (25), 2020 Journal Article, 2020 DOI TARA - Full Text

Nelson J, Tiwari R, Sanvito S, Machine learning density functional theory for the Hubbard model, Physical Review B, 99, (7), 2019 Journal Article, 2019 DOI TARA - Full Text URL

Liu, Y. and Tiwari, R. and Narayan, A. and Jin, Z. and Yuan, X. and Zhang, C. and Chen, F. and Li, L. and Xia, Z. and Sanvito, S. and Zhou, P. and Xiu, F., Cr doping induced negative transverse magnetoresistance in C d3 A s2 thin films, Physical Review B, 97, (8), 2018, 085303- Journal Article, 2018 URL TARA - Full Text DOI

Nyayabanta Swain, Rajarshi Tiwari and Pinaki Majumdar, Mott-Hubbard transition and spin-liquid state on the pyrochlore lattice, PHYSICAL REVIEW B, 94, (15), 2016, p155119-1 - 155119-10 Journal Article, 2016 URL TARA - Full Text DOI

Rajarshi Tiwari and Pinaki Majumdar, Spectroscopic signatures of the Mott transition on the anisotropic triangular lattice, Europhysics Letters, 108, 2014, p27007-p1 - 27007-p6 Journal Article, 2014 URL TARA - Full Text DOI

Rajarshi Tiwari and Pinaki Majumdar, NONCOLLINEAR MAGNETIC ORDER IN THE DOUBLE PEROVSKITES: DOUBLE EXCHANGE ON A GEOMETRICALLY FRUSTRATED LATTICE, International Journal of Modern Physics B, 27, (6), 2013, p1350018-1 - 1350018-26 Journal Article, 2013 URL DOI TARA - Full Text

Rajarshi Tiwari and Pinaki Majumdar, Visualizing the Mott transition, CURRENT SCIENCE, (5), 2012, p518 - 524 Journal Article, 2012 URL TARA - Full Text URL URL

T. Archer, C. D. Pemmaraju, S. Sanvito, C. Franchini, J. He, A. Filippetti, P. Delugas, D. Puggioni, V. Fiorentini, R. Tiwari, and P. Majumdar, Exchange interactions and magnetic phases of transition metal oxides: Benchmarking advanced ab initio methods, Physical Review B, 84, (11-15), 2011, p115114-1 - 115114-14 Journal Article, 2011 URL

Research Expertise

Description

I am a Research Fellow at the School of Physics and CRANN, Trinity College Dublin, where my research interests range over computational materials science, and condensed-matter physics. I specialize in physics of strongly correlated electrons, such as Mott transition, magnetism of itinerant electrons, electron phonon interactions. My interests are geared towards solving appropriate models of many-body interaction, such as Hubbard model, Double exchange model, Holstein model, Heisenberg model through real space based techniques like Monte-Carlo methods and Exact-Diagonalization. More recently, I have been interested in (i) exploring methods for structure property relations of materials with use of High-Throughput {\it ab initio} and dataminig approach, and (ii) application of artificial intelligence in solving models of many-body physics and in learning structure-propery relation of materials.

Recognition

Awards and Honours

NVIDIA Academic Hardware Grant Program for "Machine Learning material design and characterization" (2 Quadro RTX 8000 card to our research group) 27 August 2021