Artem Pulkin
[ΙrΛtsΚ²Ι΅m]
π§ gpulkin@gmail.com
π pulk.in
π Amsterdam NL π³π±
Expertise
Software development, machine learning, data, scientific research
Education π
2012-2017
Docteur Γ¨s Sciences EPFL in physics Lausanne CH π¨π
Specialized on: numerical electronic structure, quantum simulations.
Thesis: Electronic Transport in 2D Materials with Strong Spin-orbit Coupling (03/2017);
supervisor: Oleg Yazyev
2010-2012
Master of Science Chalmers in applied physics GΓΆteborg SE πΈπͺ
Thesis: Spintromechanical Aspects of Charge Transport in Nanostructures (06/2012);
supervisor: Robert Shekhter
2006-2010
B.Sc. in Physics cum laude V.N. Karazinβs State University Kharkiv UA πΊπ¦
Training
Coursera: Machine Learning from Stanford University
Experience π¬
Apr'19-Apr'22
Engineering scientific software @ QuTech TU Delft π³π±
I led development of an open-source ML research software in python for material properties miniff: formulated tech requirements and designed the software; organized a team of 2-4 people with different backgrounds towards Agile workflow and priority goals; optimized and scaled the code; prepared, released and integrated the package for running in distributed HPC environment; attracted users and coordinated various parties (scientists, HPC platform, industry users).
Jul'17-Mar'19
Research and engineering @ Caltech US πΊπΈ
Performed R&D in numerical computer simulations of properties of novel materials. As a part of a bigger team (10-20 team members) implemented new functionality in the open-source python software project pyscf; contributed to strategic decisions and assigning priorities; refactored, prepared unit tests and documentation.
Oct'12-Apr'17
Pursued PhD @ EPFL CH π¨π
Jun'12-Aug'12
Contributed to scientific research @ Seoul National University, KR π°π·
Aug'10-Jun'12
Performed scientific research @ Chalmers, SE πΈπͺ
Projects
More on github/pulkin
miniff
https://gitlab.kwant-project.org/qt/miniff
A machine learning project in python to simulate molecular dynamics with classical force fields. Combines the power of cython, numpy and torch to deliver maximal performance in a high-quality python code. Demonstrates my passion for using cython when it comes to solving bottlenecks.
pyscf
https://github.com/pyscf/pyscf
A large collaboration across universities and public companies towards high-performance quantum chemistry in python. Implemented with numpy and pure-C. Proud of having worked with these people.
pyteleport
https://github.com/pulkin/pyteleport
My experiment in teleporting python runtimes from within the stack. Uses cPython bytecode (and relies on dill for object serialization). Integrates with AWS EC2. A sole project and idea I am very proud of.
pycoordinates https://github.com/pulkin/dfttools
A simple computational package for basis transformations. Implemented with python, numpy and cython. One of my cleanest code where I discovered the power of python build.
micropython https://github.com/pulkin/micropython
A micropython (python dialect) port to a popular cellular network module A9G written in C. Enjoyed supporting others in their hardware projects while digging into embedded firmware design.
Awards π
postgraduate
π° Personal Swiss NSF grant to study abroad
80k CHF, 18 months, postdoctoral level (Early Postdoc.Mobility) grant P2ELP2_175281
π° Personal computing time at national supercomputing facilities (SURF NL) Approximate equivalent of 26k EUR, 24 months project 45873
graduate
π₯ Olympiad in Physics for University Students (national in Ukraine) β first prize
π Youth Physicists Tournament (national in Ukraine, team) β multiple prizes
π₯ Open Olympiad in Applied Physics (MIPT Moscow) β first prize
π° Kharkiv City Mayor and Kharkiv State Governor scholarships for gifted youth
high school
π₯ Dozens of prizes in physics and informatics (olympiads, student projects; top-10 and top-1 in national competitions)
π° Multiple scholarships
Skills π¨
Software development in π 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; other: FastAPI, django, OpenCV, OpenCL, bytecode.
C/C++: HPC and parallel environments (MPI, OpenMP); Lapack; embedded platforms; interfacing other languages; decompiling and reverse-engineering.
Other: β Java, Fortran, Julia, Javascript, Matlab.
Infrastructure: git, CI/CD (Travis, Gitlab-CI, Azure pipelines), docker, HPC, AWS (EC2, S3).
IDEs: Pycharm, vim.
Machine learning: supervised learning (DNN, linear fits, logistic fits, SVM); unsupervised learning (PCA/SVD, K-means, anomaly detection); dataset generation, feature extraction, adversarial models.
Soft skills: critical analysis, problem solving, communicating (organizing discussions, presenting, paper/grant/documentation writing), full-cycle project management (idea - funding - implementation - reporting), supervision.
Languages
English (prof), Ukrainian (mother), Russian, French (basic), Dutch (basic).
Hobbies
Sports, β travels, cross-stitching, soldering, π lock picking, πΉοΈ board and video games, open-source projects.