Researcher, data scientist, software engineer
📧 firstname.lastname@example.org 🌐 pulk.in 🏠 Amsterdam NL 🇳🇱
🔍 jobs: researcher, ML scientist, research engineer, data scientist, software engineer
Developing innovative machine learning approaches to engineer electronic materials and molecules addressing modern society challenges
Computational quantum, machine learning, research code development
Docteur ès Sciences EPFL in physics Lausanne CH 🇨🇭
Specialized on: numerical electronic structure, quantum simulations.
Thesis: Electronic Transport in 2D Materials with Strong Spin-orbit Coupling (03/2017);
supervisor: Oleg Yazyev
Master of Science Chalmers in applied physics Göteborg SE 🇸🇪
Thesis: Spintromechanical Aspects of Charge Transport in Nanostructures (06/2012);
supervisor: Robert Shekhter
B.Sc. in Physics cum laude V.N. Karazin’s State University Kharkiv UA 🇺🇦
Coursera: Machine Learning from Stanford University
Postdoc @ QuTech Delft university of technology NL 🇳🇱
I researched a stack of machine learning tools: deep neural networks DNN, generative models (reverse Monte-Carlo, RMC), adversarial attack approaches in the context of electronic structure/nanoscale atomic dynamics. I developed a DNN/atomic descriptor code for nanoscale dynamics miniff. I discovered novel electronic materials as a part of a multi-disciplinary team of quantum researchers.
Postdoc @ Caltech US 🇺🇸
I developed and implemented a computational many-body quantum chemistry framework to model two-dimensional crystalline materials. I investigated low-energy spectral properties of two-dimensional molybdenum disulphide with numerical modeling.
Doctoral assistant @ EPFL CH 🇨🇭
I carried out a scientific project in the quantum materials modelling domain. I discovered a new class of electronic band structure effects in two-dimensional semiconductors. I collaborated with world-leading experimental groups to prove my findings experimentally.
Research assistant @ Seoul National University, KR 🇰🇷
Research assistant @ Chalmers, SE 🇸🇪
15 publications >500 citations 14 talks
More on github/pulkin
miniFF https://gitlab.kwant-project.org/qt/miniff (python, cython)
Simulate molecular dynamics with classical force fields and machine learning. Combines the power of cython, numpy and torch to deliver maximal performance in a high-quality python code.
pyscf https://github.com/pyscf/pyscf (python, C)
A large collaboration across universities and public companies towards high-performance Quantum chemistry in python. I contributed towards implementing periodic boundary conditions for diagrammatic kernels.
Pause, teleport and resume your python runtime from within the stack. Manipulates cPython memory and bytecode.
dfttools https://github.com/pulkin/dfttools (python)
Parsing and plotting the results of first-principles simulations.
openmx-hks https://github.com/pulkin/openmx-hks (C)
A practical tool to convert the data from a popular density functional theory code into numpy.
micropython https://github.com/pulkin/micropython (C)
A micropython port to a popular cellular network module A9G.
💰 Personal Swiss NSF grant to study abroad
80k CHF, 18 months, postdoctoral level (Early Postdoc.Mobility) grant P2ELP2_175281
💰 Personal computing time at national supercomputing facilities (SURF NL) Approximate equivalent of 26k EUR, 24 months project 45873
🥇 Olympiad in Physics for University Students (national in Ukraine) – first prize
🏅 Youth Physicists Tournament (national in Ukraine, team) – multiple prizes
🥇 Open Olympiad in Applied Physics (MIPT Moscow) – first prize
💰 Kharkiv City Mayor and Kharkiv State Governor scholarships for gifted youth
🥇 Dozens of prizes in physics and informatics (olympiads, student projects; top-10 and top-1 in national competitions)
💰 Multiple scholarships
Science: quantum condensed matter, first-principles approaches.
Machine learning: supervised learning (DNN, linear fits, logistic fits, SVM); unsupervised learning (PCA/SVD, K-means, anomaly detection); dataset generation, feature extraction, adversarial models; deployment: HPC, heterogeneous environments (GPU+CPU).
Software development in 🐍 Python (7 years): scientific stack: numpy, torch, matplotlib; notebooks; HPC and parallel/distributed/concurrent computing (MPI, OpenMP, multiprocessing, async); performance-driven development with C and cython; styling, testing, documenting, packaging; micropython and python beyond standards (cPython bytecode).
C: HPC and parallel environments (MPI, OpenMP); Lapack; embedded platforms.
Infrastructure: git, CI/CD (Travis, Gitlab-CI, Azure pipelines).
IDEs: Pycharm, vim.
Soft skills: critical analysis, problem solving, communicating (organizing discussions, presenting, paper/grant/documentation writing), full-cycle project management (idea - funding - implementation - reporting), supervision.
English (proficient), Russian (mother), French (basic), Dutch (basic).
Sports, ✈ travels, cross-stitching, soldering, 🔒 lock picking, 🕹️ board and video games, open-source projects.