Shaikh M. Arifuzzaman, Ph.D.



Dr. Shaikh M. Arifuzzaman is an Assistant Professor in Computer Science at the University of Nevada--Las Vegas (UNLV). Previously, he was an assistant professor at the University of New Orleans (UNO). Arifuzzaman received his Ph.D. in Computer Science from Virginia Tech. Dr. Arifuzzaman's research interests are in algorithmic foundations of large-scale, data-intensive computing using high-performance computing (HPC) techniques, especially for data science, artificial intelligence (AI)/machine learning (ML), and security problems. At UNLV, Dr. Arifuzzaman leads the DiSC Lab that aims for discovery through Data-intensive Scalable Computing and Algorithms. Further, as a visiting faculty with Lawrence Berkeley National Lab (Berkeley Lab), he collaborates on exascale computing problems in multidisciplinary areas.  Arifuzzaman also held positions with Sandia National Lab (SNL) and Biocomplexity Institute at Virginia Tech previously. Arifuzzaman is the recipient of 2023 and 2019 US DoE SRP Fellowship. He also won the first place in Big Data Cup Challenges competition held with 2019 IEEE Big Data Conference. Dr. Arifuzzaman's research has been supported by National Science Foundation (NSF), US Dept. of Energy (DoE), UNLV OSP/FOA, LA BoR, among others.

A quick glance on Dr. Arifuzzaman's research:



WE ARE HIRING!!! Post-doc and graduate/UG students are welcome to apply for positions in my lab. If you are strong in algorithms and have solid skills and interests in HPC and AI/ML, send me an email with your CV, interests, and writing samples. The accepted candidates will have the opportunity to collaborate/work with US national labs. My current and previous students have interned with and secured full-time positions with national labs and prominent tech companies. UNLV is among top 3 percent nationally in research activity, a Carnegie R1 (Top Tier) research university.

Recent Highlights

  • IPDPS 2024
    Research paper accepted at GrAPL Workshop with IPDPS 2024
    Our research paper titled "Unlocking the Potential: Performance Portability of Graph Algorithms on Kokkos Framework" has been accepted for presentation at GrAPL Workshop with IPDPS 2024. Thanks to my Ph.D. student Faysal, undergraduate student Hasan, and our collaborators at LBNL (Max Bremer, John Shalf, and Doru Thom Popovici). Special thanks to Thom for working closely with us throughout the summer of 2023.
  • President's Innov. Winner 2024
    Mentorship Achievement: My team became Champions in UNLV President's Innovation Challenge Competition 2024 with $25,000 grand prize
    Exciting Mentorship Achievement: Thrilled to share that the team I advised has clinched victory in the 3rd UNLV President's Innovation Challenge, securing the grand prize of $25K! These students are truly exceptional—having crafted a winning business idea, presented to distinguished judges from industry and academia, and convincingly demonstrated their merit for this year's top spot. Now, they're gearing up to launch a startup with their innovative Artificial Intelligence-based product, aimed at addressing new challenges in Nevada's education and learning sector. Congratulations to Cinnamon, Emilie, Jerwin, Stacey, and Zachary.
  • Soc. Net. Anal. Min.
    Research paper published in Social Netowrk Analysis and Mining Journal (2024)
    Our research paper titled "Sentiment analysis of tweets on social security and medicare" has been published in Springer Journal of Social Network Analysis and Mining. Thanks to my incredibly talented high-school student Unmesh who first-authored the paper. He is heading to Carnegie Melon University for his undergraduate degree in CS and engineering.
  • Ph.D. Student Graduated
    Grduated my second Ph.D. student Faysal (now Dr. Faysal).
    My second Ph.D. student Md. Abdul Motaleb Faysal graduated with him Ph.D. by the end of Fall 2023. Congratulations, Faysal! Looking forward to seeing him succeed in his endeavors. Faysal is currently completing a postdoc at Texas State with Prof. T.Z. Islam.
  • ICPP 2023
    Research paper accepted at ICPP 2023
    Our research paper titled "Fast Parallel Index Construction for Efficient K-truss-based Local Community Detection in Large Graphs" has been accepted for presentation at the 52nd International Conference on Parallel Processing. Thanks to my Ph.D. student Faysal and our collaborators at LBNL (Max Bremer, Cy Chan, and John Shalf).
  • Apl. Net. Sci.
    Research paper published in Applied Network Science Journal (2023)
    Our research paper titled "Exploring temporal community evolution: algorithmic approaches and parallel optimization for dynamic community detection" has been publisehd in Springer Journal of Applied Network Science. Thanks to my former Ph.D. student Safrin and our collaborators at LBNL (Aydin Buluc and Khaled Ibrahim).
  • LBNL Visiting Faculty 2023
    Spending my summer at Berkeley, collaborating with renowned scientists on exciting projects.
    My students M.A.M. Faysal (Ph.D.) and Hasan Arikan (undergrad) have joined me. Thanks to my collaborators on multiple projects: Thom, John, Max, Cy, Khaled, and Aydin.
  • Grant [UNLV-FOA] 23-25
    One of only 5 receipients of FOA award at UNLV this year!
    Happy to be awarded an FOA Award at UNLV to pursue interdisciplinary research at UNLV. I teamed up with Dr. Brian Labus from Biostatistics and Epidemiology to research on a data-driven approach to understanding epidemiology in urban setting. Hiring a CS graduate student for this project.
  • IPDPS23
    Paper accepted and presented at IPDPSW23
    Our paper titled "Fast Community Detection in Graphs with Infomap Method using Accelerated Sparse Accumulation is accepted for presentation at the 37th IEEE International Parallel and Distributed Symposium (IPDPS 2023), which is a premium research forum for parallel and distributed computing and systems. The work presents improved algorithms for next-generation hardware architecture for a graph data problem and related applications. The work was done in collaboration with scientists from Computer Science department at Lawerence Berkeley National Laboratory (thanks to Max, Doru, John, and Cy).
  • SC22
    Served as TPC member and Best Research Poster Judge at SC22
    Delighted to continue attending SC Conferences.
  • Grant [NSF] (2022-24)
    Awarded a National Science Foundation (NSF) grant to work on algorithms for dynamic graph data (Single PI)
    Project: Fast Algorithms for Mining and Analysis of Evolving Patterns in Large Dynamic Graphs. In collaboration with Computational Research Division of Berkeley Lab. Duration: 2022-24.
  • Ph.D. Student Graduated
    Grduated my first Ph.D. student Naw Safrin Sattar (now a postdoc with ORNL).
    My first Ph.D. student Naw Safrin Sattar graduated with a Ph.D. in summer 2022. Congratulations, Safrin! Looking forward to seeing her succeed in her career. Safrin is currently working at Oak Ridge National Laboratory as a postdoc.
  • Moving to UNLV 2022
    I am moving to UNLV with my group.
    I am excited to be joining UNLV starting July 2022. I welcome new challenges and am looking forward to new opportunities for collaborations and impactful research. At the same time, I am thankful for all the opportunities and warmth I received at UNO and am immensely proud of the accomplishments of my students. I'll miss my students and colleagues over there and will always wish them the very best.
  • SC21
    Doctoral Showcase and other accomplishments at SC21
    Safrin and my work is one of top 10 dissertations selected by SC21 to be showcased at the conference. We also had another research poster accepted. I served the Technical Program Committee.
  • Grant [DoE] (2020-21)
    Awarded a subcontract from US Department of Energy (DoE)/Berkeley Lab/University of California
    Project: Innovative Architecture for High Performance Data Analytics. In collaboration with Computational Research Division of Berkeley Lab. Duration: 2020-21.
  • BigData 2020
    [Article+Leadership] Paper on machine learning and parallel algorithms published in 2020 IEEE International Conference on BigData. I also co-organized BigGraphs Workshop.
    BigData Paper Title: Community Detection using Semisupervised Learning with Graph Convolutional Network on GPUs. With Naw Safrin Sattar (thanks!). I also co-chaired BigGraphs workshop: Seventh International Workshop on High Performance Big Graph Data Management, Analysis, and Mining (BigGraphs 2020). https://biggraphs.org/. December 2020
  • IPDPS 2020
    [Article] Paper accepted in ScaDL 2020 Workshop (Scalable Deep Learning over Parallel And Distributed Infrastructures) with IPDPS 2020. Theme: machine learning, algorithms.
    Data Parallel Large Sparse Deep Neural Network on GPU. More info on the workshop: https://2020.scadl.org/program. Thanks Safrin for co-authoring the paper.
  • ACM TKDD (2020)
    [Article] Paper published in ACM Transactions on Knowledge Discovery from Data (TKDD). Theme: Parallel algorithms, HPC, approximation algorithms, graph data mining.
    Shaikh Arifuzzaman, Maleq Khan, and Madhav Marathe. Fast Parallel Aglroithms for Counting Triangles in Big Graphs. ACM Transactions on Knowledge Discovery from Data (TKDD), Vol. 14 Num. 1, Pages 5:1--5:34, ACM, Feb 2020. Thanks to my co-authors!
  • BigData 2019
    [Article+Leadership+Award] IEEE BigData Conference 2019 in LA, CA: Won IEEE Brain Data Analytics Challenges competition, presented multiple papers, co-organized BigGraphs Workshop
    Happy to lead our team "BDTigers" to The 1st Place (Championship) in a Big Data Cup Challenges competition in the 2019 IEEE Big Data Conference at Los Angeles, California. This was a data analytics competition organized by IEEE Brain Initiative, namely Brain Data Bank Challenges and Competitions. More info on the competition: https://tinyurl.com/u9uwlsx. Further, we had three papers to present on problems involving graphs and machine learning (thanks and congratulations to my Ph.D. students Md Abdul Motaleb Faysal and Naw Safrin Sattar for their papers). Moreover, I co-organized a workshop on large-scale graph mining (BigGraphs 2019), which was also very well-attended and appreciated by a diverse audience.
  • SC19
    [Leadership+Article] Attending SC19 at Denver: Serving the Best Poster Judging Committee, paper presented at PDSW workshop (area: parallel algorithms).
    I'll work as a Supercomputing mentor and judge for the best poster presentation. Safrin will present our work-in-progress paper in PDSW Workshop.
  • LBNL/UC Berkeley (2019)
    [Prof. Position] Started working with Berkeley Lab (Computational Research Division) as Visiting Faculty. Collaborating on problems in areas of algorithms, performance modeling/benchmarking, and machine learning
    Spent my Summer 2019 at Berkeley with Performance and Algorithms Research Group. Safrin joined with me as my Ph.D. intern.
  • Grant[UNO/CoS] (2019)
    Awarded College of Sciences research grant. Theme: machine learning, high-performance computing.
    On an exciting work on machine learning and graph analytics! Year: 2019.
  • UNO/SCoRe Award 2019
    Awarded Stimulating Competitive Research (SCoRe) Award by ORSP/UNO. One of the topmost research ideas for this yearly competition at UNO. Theme: algorithmic foundations of dynamic data.
    The award was announced during its annual Achievements in Research, Creativity and Scholarship (ARCS) awards ceremony. Link: 2019 ARCS Awards.
  • DependSys19
    [Articles] Multiple papers accepted in DependSys19 Conference. Collaborated with Stennis Space Center, MS. Theme: scalable system for oceanographic data, data analytics
    Congratulations to all my co-authors! The 5th International Conference on Dependability in Sensor, Cloud, and Big Data Systems and Applications (DependSys 2019), Guangzhou, China, November 12-15, 2019.
  • SC18
    SC'18 at Dallas! We participated, presented paper, and volunteered. Served as SC Mentor.
    I worked as an SC Mentor. I was delighted to have interacted with so many young enthusiastic SC students. I also took part in the Early Career Workshop. We presented in PDSW-DISCS Workshop in SC'18. Safrin served as the Student Volunteer for SC. Link: 2018 The International Conference for High Performance Computing, Networking, Storage, and Analysis.
  • Grant[UNO] (2018)
    Awarded UNO research grant for multidisciplinary research. Theme: graph mining, brain network analysis, scalable systems.
    Co-Principal Investigator, High-resolution Human Connectome Network Analysis (PI: Dr. Elliot Beaton, Psychology; Co-PI: Dr. Vasil Roussev, CS). Jan 2018.
  • Grant[LA/BoR RCS] (2017-21)
    Awarded Louisiana Board of Regents (BoR) RCS Grant. Rated as one of the top proposals. Theme: parallel algorithms, randomized algorithms, graph data mining.
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    PI: Shaikh Arifuzzaman
    Year: June 2017- June 2021

  • Grant[UNO/CoS] (2017)
    Awarded College of Sciences grant for multidisciplinary research. Theme: biological data mining, high performance computing.
    Project: Scalable Mining and Analysis of PPI Networks. Jan 2017.