Exploratory Systems Lab

Welcome to Exploratory Systems Lab (ExpoLab) at the Computer Science Department at Purdue University. Our mission is to develop a new data science platform—referred to as ExpoDB: abstract [CIDR'17], slides—to enable real-time fusion and exploration of data at Web scale. Related research topics to fulfill this vision are:

  • Real-time OLTP & OLAP Systems (e.g., L-Store)
  • Virtualized Modern Hardware (FPGAs, GPUs, SSDs) in Database Systems on Cloud (e.g., FQP)
  • Semantic Data Enrichment through Machine Learning and Data Mining (e.g., Tiresias)
  • Data Quality and Enriched Data Curation/Integration (e.g., Self-Curating Databases)
  • Uncertainty and Inconsistency in Data Management (e.g., SPIDER)

Recent News


    Principal Investigator

    Graduate Students (Advising)

    • Spencer S Pearson (Ph.D. Candidate): Geo-Scale Distributed Transaction Processing
    • Thamir Qadah (Ph.D. Candidate, co-advising with Arif Ghafoor): Distributed, Multi-statement Transaction Over Key-Value Stores
    • Checed Aaron Rodgers (Ph.D. Candidate, co-advising with Walid Aref): Latch-free, In-memory Data Structures
    • Wolfgang P. Finkbeiner (M.Sc. Candidate): Personalized Prediction of Adverse Drug Reactions Using Social Data

    Graduate Students (Mentoring)

    • Nomchin Banga (M.Sc. Candidate): Distributed Speculative Transactions
    • Ishan Chawla (M.Sc. Candidate): Distributed Deterministic Transactions
    • Anshu Maheshwari (M.Sc. Candidate): Distributed Speculative Transactions
    • Aman Preet Singh (M.Sc. Candidate): Distributed Mutable Storage
    • Chih-Hao Fang (Ph.D. Candidate): Distributed Management of Temporal Dynamic Graphs
    • Vineeth Thomas Alex (M.Sc. Candidate): Accelerating Query Processing on Hardware Using OpenCL
    • Mengyao Wang (M.Sc. Candidate): Accelerating Query Processing on Hardware Using OpenCL

    Undergraduate Students (Mentoring)

    • Abhijeet Gaurav (B.Sc. Candidate): In-memory, Latch-free Data Structures

    External Grad Students (Mentoring)

    • Ibrahim Abdelaziz (Ph.D. Candidate at KAUST): Graph Embedding and Context-aware Graph Traversal
    • Ehab Abdelhamid (Ph.D. Candidate at KAUST): Incremental Frequent Subgraph Mining on Large Dynamic Graphs
    • Gonzalo Diaz (Ph.D. Candidate at Oxford): Ontology-aware Graph Embedding
    • Yuankun Fu (Ph.D. Candidate at IUPUI): GPU-accelerated Key-Value Stores
    • Masoud Hemmatpour (Ph.D. Candidate at Politecnico di Torino): Distributed, In-memory Key-Value Stores
    • Martin Jergler (Ph.D. Candidate at TUM): Data-centric Workflow Execution on Publish/Subscribe Abstraction
    • Fatemeh Nargesian (Ph.D. Candidate at University of Toronto): Rethinking the Relational Model in Embedding Space
    • Mohammadreza Najafi (Ph.D. Candidate at TUM): Flexible Query Processing on FPGAs


Selected Recent Papers

  • Hardware Acceleration Landscape for Distributed Real-time Analytics: Virtues and Limitations.
    M. Najafi, K. Zhang, H.-A. Jacobsen, Mohammad Sadoghi. ICDCS 2017.
  • Kanzi: A Distributed, In-memory Key-Value Store
    M. Hemmatpour, B. Montrucchio, M. Rebaudengo, Mohammad Sadoghi. Middleware 2016.
  • Geo-Distribution of Flexible Business Processes over Publish/Subscribe Paradigm.
    M. Jergler, Mohammad Sadoghi, H.-A. Jacobsen. Middleware 2016.
  • L-Store: A Real-time OLTP and OLAP System.
    Mohammad Sadoghi, S. Bhattacherjee, B. Bhattacharjee, M. Canim. arXiv 2016.
  • SplitJoin: A Scalable, Low-latency Stream Join Architecture with Adjustable Ordering Precision.
    M. Najafi, Mohammad Sadoghi, H.-A. Jacobsen. USENIX ATC 2016.
  • Self-Curating Databases.
    Mohammad Sadoghi, K. Srinivas, O. Hassanzadeh, Y-C. Chang, M. Canim, A. Fokoue, Y. Feldman. EDBT 2016 - Vision Track.
  • Predicting Drug-Drug Interactions through Large-Scale Similarity-Based Link Prediction.
    A. Fokoue, Mohammad Sadoghi, O. Hassanzadeh, P. Zhang. ESWC 2016. Best In-Use Paper Award.
  • The FQP Vision: Flexible Query Processing on a Reconfigurable Computing Fabric.
    M. Najafi, Mohammad Sadoghi, H.-A. Jacobsen. SIGMOD Record - Special Issue on Visionary Ideas in Data Management 2015.
  • Safe Distribution and Parallel Execution of Data-centric Workflows over the Publish/Subscribe Abstraction.
    Mohammad Sadoghi, M. Jergler, H.-A. Jacobsen, R. Hull, R. Vaculin. TKDE 2015.


  • Spring 2017
    CS 590: Topics in Big Data Systems

    This new graduate seminar course surveys the recent developments in data management such as NoSQL (e.g., distributed key-value stores) and NewSQL (e.g., geo-distributed data stores) with respect to storage architecture (e.g., log-structured, row-oriented, and column-oriented layouts), concurrency controls (e.g., ranging from eventual consistency to full serializability), cloud computing and virtualization, the emerging commodity hardware trends (e.g., many-core and distributed main memory), modern hardware accelerators (e.g., GPUs, FPGAs, and SSDs), and types of workloads (e.g., OLTP and OLAP).

    Course Website

  • Fall 2016
    CS 541: Database Systems

    This graduate course provides an introduction to the design and development of fundemental concepts in relational database management systems (DBMS). You will learn the theory behind database systems, the issues that affect their functionality and performance, and most importantly, what it takes to build the engine of a relational database management system and to explore the role of modern data processing platforms, e.g., Apache Spark/Hadoop.

    Course Website

Recent Services

  • Serving as a PC member for ICDE 2018 (Research Track)
  • Serving as a PC member for VLDB 2018 (Research Track)
  • Serving as a PC member for ACM SIGMOD 2018 (Research Track)
  • Serving as a Co-Chair for Events Meet Processes Workshop at DEBS 2017
  • Serving as a Co-Chair for Active'17 Workshop at ICDE 2017
  • Serving as the PC Chair for ACM DEBS 2017 (Industry Track)
  • Serving as a Co-Chair for Doctoral Symposium at ACM/IFIP/USENIX Middleware 2017
  • Serving as a PC member for ACM SIGMOD 2017 (Research Track)
  • Serving as a PC member for VLDB 2017 (Research Track)
  • Serving as a PC member for ACM/IFIP/USENIX Middleware 2017 (Research Track)
  • Serving as a PC member for DBPL 2017 (Research Track)
  • Serving as a PC member for IJCAI 2016 (Research Track)
  • Serving as a PC member for ACM/IFIP/USENIX Middleware 2016 (Industry Track)
  • Serving as a PC member for ICSOC 2016 (Research and Industry Tracks)
  • Serving as a Publicity Co-Chair for ACM DEBS 2016


Mohammad Sadoghi is an Assistant Professor in the Computer Science Department at Purdue University. Previously, he was a Research Staff Member at IBM T.J. Watson Research Center for nearly four years. He received his Ph.D. from the Computer Science Department at the University of Toronto in 2013. He was the recipient of the Ontario Graduate Scholarship (2006-2007) and the NSERC Canada Graduate Scholarship (2007-2008, 2009-2011).

Broadly speaking, Professor Sadoghi's research focuses on high-performance and extensible Big Data Management Systems in the context of designing novel data structures and (parallel) algorithms and utilizing modern hardware advancements, especially many-core processors, hardware accelerators (e.g., FPGAs and GPUs), and storage-class memories (e.g., flash and phase change memory). In particular, he is interested in rethinking the foundation of relational database system design for future hardware and computing platform (i.e., cloud) by reshaping the transaction and storage model to sustain the unprecedented scale of data proliferation and heterogeneity observed in the Big Data era.

Professor Sadoghi has over 40 publications in leading database conferences/journals (including SIGMOD, VLDB, ICDE, EDBT, TODS, and TKDE) and over 30 filed U.S. patents. His SIGMOD'11 paper, “BE-Tree: an index structure to efficiently match Boolean expressions over high-dimensional discrete space”, was awarded EPTS Innovative Principles Award; his EDBT'11 paper, “GPX-Matcher: a generic Boolean predicate-based XPath expression matcher”, was selected as one of the best EDBT papers in 2011; and his ESWC'16 paper titled "Predicting Drug-Drug Interactions through Large-Scale Similarity-Based Link Prediction" won the Best In-Use Paper Award. He has presented a tutorial at ICDE'16 on “Accelerating Database Workloads by Software-Hardware-System Co-design”. Currently, he is serving as the PC Chair (Industry Track) for ACM DEBS'17, he is co-chairing a new workshop at ICDE'17 entitled "Active'17: First International Workshop on Data Management on Virtualized Active Systems", he is co-chairing a new workshop at DEBS'17 entitled "First International Workshop on Events Meet Processes", and he is co-chairing the Doctoral Symposium at ACM/IFIP/USENIX Middleware'17. Previously, he was the publicity co-chair of ACM DEBS (2015-16). He regularly serves on the program committee of SIGMOD, VLDB, ICDE, EDBT, IJCAI, ICDCS, ECOOP, ICSOC, DEBS, and ADMS; and has been invited reviewers for TKDE and TPDS.

Join Us

I am looking for motivated and creative students to push the boundry of database systems. If you are interested, please email me a brief summary of your qualifications and research interests.