Work Experience

2022 — present: Senior Tech­ni­cal Intel­li­gence Engi­neer, Input Output

Tech­ni­cal analy­sis and audit­ing of projects in blockchain. This involves cre­at­ing reports for C‑level and a vari­ety of tasks such as: eval­u­a­tion of require­ments, archi­tec­ture trade­offs, code audits, mea­sur­ing tech­nol­o­gy adop­tion, com­peti­tor analy­sis and sci­en­tif­ic lit­er­a­ture surveys.

2021 — 2022: Lead Data Engi­neer, Sin­gu­larity­Dao

Team Lead and devel­op­er. Archi­tect, devel­op and man­age stream­ing, cloud-agnos­tic ELT pipelines for cryp­tocur­ren­cies data
New tech­nolo­gies: Kuber­netes, Snowflake, dbt, Kaf­ka, Air­flow, Spark, Grafana, Prometheus, Loki, poet­ry, web3, AWS RDS, AWS EMR 

2020 — present: Python, Kotlin and DevOps devel­op­er, Riff on That

Designed and devel­oped a social plat­form for musi­cians’ online dis­cov­ery and col­laboration.
New tech­nolo­gies: Dock­er Swarm, Trae­fik, Post­greSQL, App­smith, FastAPI,  pytest, boto3, sqlalche­my, pydan­tic, AWS EC2, AWS S3, Android SDK (Kotlin),  RoomDb, Retro­fit, Jet­pack Nav­i­ga­tion Components

2019 — 2021: Python Devel­op­er and research assis­tant, Fraun­ho­er IIS- Future Engi­neer­ing, Nürnberg

Data Sci­ence con­sult­ing ser­vices for busi­ness­es look­ing for cus­tomer insights from social media and oth­er online data.

  • Super­vised 4 interns (Mas­ter Thesis) 
  • NLP for IE (Top­ic mod­el­ing, Ques­tion Answer­ing, RE) 
  • Social graph clus­ter­ing analysis 
  • Dock­er­ized data pipelines for ETL 
  • Knowl­edge Graph design (Neo4j, GraphDb) 
  • Lin­ux and Dock­er sys­tems administration 

New tech­nolo­gies: Dock­er, SPARQL (GraphDb), Cypher (Neo4j), SQL (Mari­aDb),
Dataiku DSS, Azure, sqlalche­my, scik­it-learn, pytorch, ten­sor­flow, sen­tence­trans­form­ers, hug­ging­face, nltk, gen­sim, tomo­topy, pyl­davis, net­workx, numpy, pandas

2015 — 2019: Research assis­tant, Insti­tut für Numerische und Ange­wandte Math­e­matik, Göt­tin­gen

  • Adap­tive wavelet transforms 
  • Image seg­men­ta­tion and data clustering 
  • Dic­tio­nary Learn­ing and Sparse Coding 

New tech­nolo­gies: Mat­lab, numpy, pan­das, scik­it-learn, Latex Mat­lab, numpy, pan­das, scik­it-learn, Latex


2018: Phd in Math­e­mat­ics, Insti­tut für Numerische und Ange­wandte Math­e­matik, Göt­tin­gen, magna cum laude 
2015: MsC in Math­e­mat­ics, Uni­ver­si­ty of Pisa, Pisa, 110/110
2011: Bach­e­lor of Math­e­mat­ics, Uni­ver­si­ty of Tri­este, Tri­este, 110/110 cum laude 

The­sis title:  Fouri­er Series: some clas­si­cal results on con­ver­gence and non convergence


  • Randim­age, python pack­age: EPWT-based ran­dom image generator. 
  • Trans­former­topic, python pack­age: Top­ic Mod­el­ing based on Trans­former DNN. 

Professional Skills

Pro­gram­ming Languages

  • Exten­sive expe­ri­ence in Python 
  • Expe­ri­enced in Kotlin and the Android SDK 
  • Inter­me­di­ate expe­ri­ence with C, Javascript, For­tran, Super­col­lid­er, Bash 


  • Exten­sive expe­ri­ence in Lin­ux sys­tem administration 
  • Expe­ri­enced in Dock­er and Dock­er Swarm 
  • Basic knowl­edge of AWS (EC2, S3) 


Ital­ian (native), Eng­lish (flu­ent), Ger­man (inter­me­di­ate), Russ­ian (begin­ner)


Bran­dl, C., Albrecht, J., Budinich, R. (2021) An Eval­u­a­tion of State-of-the-Art Approach­es to Rela­tion
Extrac­tion for usage on Domain-Spe­cif­ic Cor­po­ra
NATL 2021

Bel­ger, A., Budinich, R., Blum, R., Zabloc­ki, M., Zim­mer­mann, R. (2020).  Mar­ket and Tech­nol­o­gy Mon­i­tor­ing dri­ven by Knowl­edge Graphs, ESWC 2020

Budinich, R., Plon­ka, G. (2020). A Tree-based Dic­tio­nary Learn­ing Frame­work Inter­na­tion­al Jour­nal of
Wavelets, Mul­tires­o­lu­tion and Infor­ma­tion Pro­cess­ing, 18(05), 2050041.

Budinich, R. (2017). Image com­pres­sion with the region based easy path wavelet trans­form, PAMM,

Budinich, R. (2017). A region-based easy-path wavelet trans­form for sparse image rep­re­sen­ta­tion.
Inter­na­tion­al Jour­nal of Wavelets, Mul­tires­o­lu­tion and Infor­ma­tion Pro­cess­ing, 15(05):1750045.