Michael Gubanov

Assistant Professor
News: Two more papers accepted by ACM CIKM 2024 and EDBT 2025!
              Awarded a grant from FL Department of Health Casey DeSantis Florida Cancer Innovation Fund as a PI for constructing a hybrid Polystore/LLM simplifying access to Cancer Data Lakes!
              Awarded an NSF grant as a PI for constructing Web-scale Knowledge Graphs and LLMs for Data Science!
              Received the AWS AI Amazon Research Award (ARA)! Thanks to Amazon for supporting BigLab! research!
              One more paper by BigLab! accepted to The Web Conference (WWW) 2023, held in Austin, TX this year!
              Two more papers accepted, total 3 papers presented at EDBT by BigLab! this year!!
              Our COVIDKG.ORG paper was accepted by EDBT 2023!
              Our COVID-19 Web-scale vizualization paper was accepted to ACM CIKM 2022!
              Our tabular profiling paper was accepted to ACM SIGMOD 2022!
              Launched COVIDKG.ORG and AGINGGRAPH.ORG
              Our New Data Science courses approved by FSU and State of Florida!
              Elected to Sigma Xi, 2021
              Communications of the ACM 2020 Research Highlight Award!
              Communications of the ACM (CACM) 2020 published our "Scalable Linear Algebra" paper!
              PG 2020 Award! Thank you to FSU!
              Congratulations to the award-winning teams from my FSU Data Science course this year! Team1, Team2, Team3

              FYAP 2019 Award! Thank you to FSU!

              ACM SIGMOD Research Highlight Award, 2018!
              ICDE 2017 award paper invited to a special issue of ACM SIGMOD Record
              ICDE 2017 award paper invited to publication in "Best of ICDE" issue of TKDE 2018
              ICDE 2017 Best Paper Award!

            Watch my talk at MIT on our Hybrid Linear Relational Engine
Florida State University
Computer Science Department

1017 Academic Way
Tallahassee, FL 32304
gubanov at cs.fsu.edu
Follow me on ResearchGate

About

I am an Assistant Professor at Florida State University and a founder of BigLab!, where we do research in Web-scale Artificial Intelligence (AI), Large Language Models (LLMs), and Data Science. Our recent projects are CancerKG.ORG, CovidKG.ORG, and AgingGraph.ORG - Hybrid Web-scale LLM/RAG KGs for Cancer, COVID-19, and Ageing.

I earned my Ph.D. and M.Sc. in Computer Science from the University of Washington. I did my Postdoc at Computer Science and Artificial Intelligence Laboratory (CSAIL) of M.I.T. with the A.M. Turing Award recipient Michael Stonebraker. I completed my undergraduate education at St. Petersburg ITMO University (ACM-ICPC World Champions 7 times). Before that I graduated from the Presidential Physics/Mathematics Lyceum #239. I was also a member of the Russian National Team in Physics.

I spent some time working in industry to apply my research - At IBM Almaden Research Center on Data Integration (project Clio, productized as a part of IBM Infosphere); at Google on Web-search and Large-scale Machine Learning (productized as parts of SETI and Froogle); at Microsoft Research on Natural Language Processing (productized as a part of Bing!). My Erdös number is 3.

Selected Publications

  1. "Tabular Embeddings for Tables with Bi-Dimensional Hierarchical Metadata and Nesting"
    Gyanendra Shrestha, Chutian Jiang, Sai Akula, Vivek Yannam, Anna Pyayt, Michael Gubanov, to appear in EDBT, 2025 [pdf]
  2. "CancerKG.ORG - a Web-scale, Interactive, Verifiable Knowledge Graph-LLM Hybrid for Assisting with Optimal Cancer Treatment and Care"
    Michael Gubanov, Anna Pyayt, Aleksandra Karolack, in ACM CIKM, 2024 [pdf]
  3. "Learning Topical Structured Interfaces from Medical Research Literature"
    Maitry Chauhan, Anna Pyayt, Michael Gubanov, in The Web Conference (WWW), 2023[pdf]
  4. "COVIDKG.ORG - a Web-scale COVID-19 Interactive, Trustworthy Knowledge Graph, Constructed and Interrogated for Bias using Deep-Learning"
    Chris Caballero, Anna Pyayt, Nick Piraino, Bhim Kandibedala, Michael Gubanov, in EDBT, 2023
  5. "Leveraging Scalable Profiling to Learn and Visualize the Latest Trustworthy COVID-19 Medical Research Findings"
    Michael Gubanov, Sophie Pavia, Anna Pyayt, William Goble, in ACM CIKM, 2022[pdf]
  6. "Simplifying Access to Large-scale Structured Datasets by Meta-Profiling with Scalable Training Set Enrichment"
    Sophie Pavia, Rituparna Khan, Anna Pyayt, Michael Gubanov, in ACM SIGMOD, 2022[pdf]
  7. WebLens: Towards Interactive Large-scale Structured Data Profiling
    Rituparna Khan, Michael Gubanov, in ACM CIKM 2020, online [pdf]
  8. Hybrid.Poly: A Consolidated Interactive Analytical Polystore System
    Maksim Podkorytov, Michael Gubanov, in ICDE 2019, Macao, China SAR [pdf]
  9. CognitiveDB: An Intelligent Navigator for Large-scale Dark Structured Data  [pdf]
    Michael Gubanov, Manju Priya, Maxim Podkorytov, in WWW 2017, Perth, Australia
  10. Generating UFOs from the Classified Object Tables  [pdf]
    Anusha Kola, Harshal More, Sean Soderman, Michael Gubanov, in IEEE Bigdata 2017, Boston, MA
  11. Hybrid: A Large-scale Linear-Relational Database Management System  [bib] [pdf][video]
    Michael Gubanov, Christopher Jermaine, Zekai Gao, Shangyu Luo, MIT Annual Database Research Conference 2016, Cambridge, MA
  12. Type-aware Web search  [bib] [pdf]
    Michael Gubanov, Anna Pyayt , in EDBT 2016, Bordeaux, France
  13. DataXFormer: Leveraging the Web for Semantic Transformations  [bib] [pdf]
    Zia Abedjan, John Morcos, Michael Gubanov, Ihab Ilyas, Michael Stonebraker, Paolo Papotti, Mourad Ouzanni, in CIDR 2015, Asilomar, California
  14. Large-scale Semantic Profile Extraction  [bib] [pdf]
    Michael Gubanov, Michael Stonebraker EDBT 2014, Athens, Greece
  15. Text and Structured Data Fusion in DataTamer at Scale  [bib] [pdf]
    Michael Gubanov, Michael Stonebraker, Daniel Bruckner, IEEE ICDE 2014, Chicago, Illinois
  16. ReadFast: High-relevance Search-engine for Big Text [bib] [pdf]
    Michael Gubanov, Anna Pyayt. ACM CIKM 2013, San Francisco, California
  17. IBM UFO Repository: Object-oriented Data Integration [bib] [pdf] [book]
    Michael Gubanov, Lucian Popa, Howard Ho, Hamid Pirahesh, Jeng-Yih Chang, Shr-Chang Chen. VLDB 2009, Lyon, France
"Much have I learned from my teachers, more from my colleagues, but from my students, most of all."

--Rabbi Hanina (b. Ta'anit 7a)

Postdocs
  1. Todor Ivanov
Graduate students(advice by Jason Eisner,Kevin Gimpel,David Peterson)
  1. Gyanendra Shrestha
  2. Chutian Jiang
  3. Sai Ganesh
  4. Mamatha Edivelli
  5. Nilkod Yashaswini
  6. Kartik Vemireddy
  7. Ishitha Yarlagada
  8. Kalyan Kadari
  9. Shardha Hirve
  10. Ruchita Munugala
BigLab! Alumni
  1. Manju Krishnan, US Bank, TX, Full Stack Software Engineer; Amazon Alexa, WA, Software Engineer
  2. Anusha Kola, HCL America, TX, Software Engineer
  3. Sai Amirishetty, Walmart, AR, Software Engineer
  4. Yuqi Li
  5. Maxim Podkorytov, Facebook, CA, Research Scientist
  6. Bhim Kandibedala, Builder Homesite, TX, Software Engineer
  7. Sophie Pavia
  8. William Goble, Dickinson College, PA, Visiting Assistant Professor
  9. Maitry Chauhan, Bank of America, NJ, Software Engineer

Links