Yatish Turakhia

Prof. Yatish Turakhia

I am an Assistant Professor in the Department of Electrical and Computer Engineering (ECE) at the University of California San Diego, with joint appointments in Computer Science and Engineering (CSE), Bioengineering, and the Bioinformatics and Systems Biology (BISB) graduate program.

My lab also collaborates closely with the Center for Machine-Integrated Computing and Security (MICS), the Center for Microbiome Innovation (CMI), and the Institute for Genomic Medicine (IGM) at UC San Diego.

You can find my most recent CV.

Email: yturakhia@ucsd.edu

Contact: +1 (858) 534-4493

Office: Room 4304, Franklin Antonio Hall, UC San Diego

Latest News

Oct 2026: Turakhia Lab welcomes Soobum Huh, Evelyn Wyszynski, and Devang Nair.
Sep 2026: Yatish is invited to participate in the U.S. Frontiers of Engineering Symposium by the National Academy of Engineering.
Aug 2026: Yatish is invited by AMD for a Tech Talk on Hardware-Accelerated Computing for Biobank-Scale Genomics.
Aug 2026: metaWEPP is published in NAR Genomics and Bioinformatics. Congratulations, Pranav, Qiwen, Jaden, and Pratik!
Aug 2026: Pranav gives a talk on WEPP to the California Department of Public Health.
Aug 2026: Sumit graduates with a PhD from UCSD. Congratulations, Sumit!
Jul 2026: Yatish participates in an expert panel on Benefits and downsides of having a vendor-specific GPU university curriculum at PEARC 2026 at Minneapolis, MN.
Jul 2026: Pranav gives talks on WEPP and metaWEPP at ISMB 2026.
May 2026: Anshu and Yatish contribute to the flagship paper: The Vertebrate Genomes Project Phase I.
May 2026: Yatish serves as Program Chair for the inaugural RECOMB-Arch workshop at RECOMB 2026.
May 2026: Yatish gives an FCCM 2026 workshop talk on Accelerating Bioinformatics on FPGAs.
Apr 2026: Anshu passes her PhD qualifying exam. Congratulations!
Apr 2026: Sumit serves as a student member of the MICRO 2026 Technical Program Committee. Congratulations!
Apr 2026: Turakhia Lab welcomes Joachim Galil and Livia Chandra.
Mar 2026: WEPP is published in PLOS Computational Biology. Congratulations, Pranav and Manu!
Feb 2026: Yatish gives a talk on Accelerating Bioinformatics on FPGAs and joins a panel at the Domain-Specialized FPGAs Workshop.
Feb 2026: Yatish presents Evolutionary Compression Enables Pangenomics at Million-Genome Scale at ITA 2026.
Feb 2026: Anshu presents DP-HLS at HPCA 2026.
Jan 2026: Pranav wins the Innovation in Research Award at the Microbes in Wastewater Symposium. Congratulations!
Jan 2026: PanMAN is published in Nature Genetics. Congratulations, Sumit, Harsh, Yu-Hsiang, and Kyle!
Jan 2026: Yatish gives an invited talk on Ultra-large Phylogenetics: Emerging Algorithms, Hardware, and Applications at ANU.
Jan 2026: Yatish presents Enabling Genome Analysis at Extreme Scale at Arch4Health, HPCA 2026.
Jan 2026: Turakhia Lab welcomes Sean Liu.
Dec 2025: Yatish presents Ultra-Large Phylogenetics for Pathogen Surveillance and Metagenomics Applications at the UCSD CMI Retreat.
Nov 2025: DP-HLS is accepted to HPCA 2026. Congratulations, Anshu, Yingqi, and Jason!
Nov 2025: Kyle Smith and Pranav Gangwar et al. release a preprint on SARS-CoV-2 recombination.
Nov 2025: Anya Wang joins Turakhia Lab as an undergraduate researcher.
Sep 2025: Wen-Chieh Lo joins Turakhia Lab as a PhD student.
Sep 2025: Pranav passes his PhD qualifying exam. Congratulations!
Aug 2025: Sumit passes his PhD qualifying exam. Congratulations!

Affiliations

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Sponsors and Collaborators

Our work is generously funded by the Centers for Disease Control and Prevention (CDC), California Department of Public Health (CDPH), Hellman Fellowship, National Institutes of Health (NIH), Advanced Micro Devices (AMD), Amazon Research Award (ARA), and the AMD AI & HPC Research Fund.

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Research Mission

Mission Updated

We are an interdisciplinary group tackling a broad set of problems at the leading edge of computer engineering and bioinformatics.

We focus on biological and medical applications where computational cost and turnaround time have become the bottleneck.

Our research mission is to develop parallel algorithms, software, and domain-specific hardware accelerators that enable faster and cheaper progress in biology and medicine.

Ongoing Research

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Pangenomics | study genetic variation across genomes

Low-cost, high-throughput sequencing has unlocked unprecedented cohorts and catalyzed pangenomics, the study of genetic variation within a species through collections of representative genomes. Realizing its potential demands moving beyond single-reference paradigms toward scalable, graph-aware methods.

Our team designs compressed data structures, novel algorithms, and hardware acceleration techniques that make pangenomic analysis more comprehensive and dramatically faster.

Related Publications

  • Alexander M. Kramer, Alan Zhang, Nicolas Ayala, Bianca de Sanctis, Lily Karim, Angie S. Hinrichs, Sumit Walia, Yatish Turakhia, Russell Corbett-Detig, "Panmap: Scalable phylogeny-guided alignment, genotyping, and placement on pangenomes" bioRxiv (2026) | DOI | Github

  • Sumit Walia, Harsh Motwani, Yu-Hsiang Tseng, Kyle Smith, Russell Corbett-Detig, Yatish Turakhia, "Compressive Pangenomics Using Mutation-Annotated Networks" Nature Genetics (2026) | DOI | Github | Website | Video

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Phylogenomics | study evolutionary relationships of species

Phylogenomics uses genome-scale data to infer the evolutionary relationships among organisms or species, underpinning evolutionary biology, outbreak analysis, and comparative genomics. Large-scale consortia such as the Vertebrate Genomes Project (VGP) and the Earth Biogenome Project (EBP) generate vast genomic data sets, yet inferring species trees from raw genome assemblies at this scale remains computationally demanding.

In collaboration with Prof. Siavash Mirarab's lab at UC San Diego, we are developing automated, scalable, GPU-accelerated, and hardware-software co-designed methods that address these challenges end to end, from raw genome assemblies to species trees.

Related Publications

  • Anshu Gupta, Wen-Chieh Lo, Siavash Mirarab, Yatish Turakhia, "ROADIES-XP: GPU Acceleration and Phylogenetic Update Improve Scalability of Species Tree Inference from Raw Genomic Assemblies", bioRxiv (2026) | DOI | Github | Website

  • Giulio Formenti, 170+ VGP Consortium authors (including Anshu Gupta and Yatish Turakhia), "The Vertebrate Genomes Project Phase I: A global reference genome resource", bioRxiv (2026) | DOI

  • Anshu Gupta, Siavash Mirarab, Yatish Turakhia, "Accurate, scalable, and fully automated inference of species trees from raw genome assemblies using ROADIES", PNAS (2025) | DOI | Github | Website | Slides | Video

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Hardware Acceleration | make computational genomics faster

Genomic data is among the fastest-growing data types on the planet and already outpaces Moore's law. From personalized medicine to species conservation, realizing its value demands far more efficient computation.

We design novel algorithms and GPU/FPGA/ASIC acceleration strategies that speed up genome assembly, read alignment, multiple sequence alignment, and whole-genome alignment workflows by orders of magnitude.

Related Publications

  • Anshu Gupta, Yingqi Cao, Jason Liang, Yatish Turakhia, "DP-HLS: A High-Level Synthesis Framework for Accelerating Dynamic Programming Algorithms in Bioinformatics", HPCA (2026) | DOI | Github | Website | Slides | Video

  • Sumit Walia, Zexing Chen, Yu-Hsiang Tseng, Yatish Turakhia, "Ultrafast and Ultralarge Distance-Based Phylogenetics Using DIPPER", Nature Computational Science (2026) | DOI | Github | Website

  • Yu-Hsiang Tseng, Sumit Walia, Yatish Turakhia, "Ultrafast and ultralarge multiple sequence alignments using TWILIGHT", Bioinformatics (2025) | DOI | Github | Website | Slides | Video

  • Sumit Walia, Cheng Ye, Arkid Bera, Dhruvi Lodhavia, Yatish Turakhia, "TALCO: Tiling Genome Sequence Alignment using Convergence of Traceback Pointers", HPCA (2024) | DOI | Github | Slides | Video

  • Sneha D. Goenka, Yatish Turakhia, Benedict Paten, Mark Horowitz, "SegAlign: A scalable GPU-based whole genome aligner", SC20 (2020) | DOI | Github | Slides | Video

  • Yatish Turakhia, Sneha D. Goenka, Gill Bejerano, William J. Dally, "Darwin-WGA: A co-processor provides increased sensitivity in whole genome alignments with high speedup", HPCA (2019) | DOI | Github | Slides | Video

  • Yatish Turakhia, Gill Bejerano, William J. Dally, "Darwin: A Genomic Co-processor Provides 15,000× Speedup on long read assembly", ASPLOS (2018) | DOI | Github | Slides | Video

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Outbreak Analysis | real-time phylogenetics for pandemic analysis

With more than 16 million complete SARS-CoV-2 genomes already sequenced, COVID-19 is the most comprehensively characterized pathogen in history. Phylogenetic analysis of these data is essential for tracking viral evolution and transmission, yet keeping pace with the deluge of sequences is a formidable computational challenge.

Our lab partners with Prof. Russell Corbett-Detig’s group at UC Santa Cruz to maintain and refine a comprehensive phylogenetic tree that incorporates every available SARS-CoV-2 genome.

Related Publications

  • Kyle Smith, Cheng Ye, Yatish Turakhia, "Tracking and curating putative SARS-CoV-2 recombinants with RIVET", Bioinformatics (2023) | DOI | Website | Slides | Video

  • Yatish Turakhia, Bryan Thornlow, Angie Hinrichs, Jakob McBroome, Nicolas Ayala, Cheng Ye, Kyle Smith, Nicola De Maio, David Haussler, Robert Lanfear, and Russell Corbett-Detig, "Pandemic-scale phylogenomics reveals the SARS-CoV-2 recombination landscape", Nature (2022) | DOI | Github | Slides | Video

  • Cheng Ye, Bryan Thornlow, Angie Hinrichs, Alexander Kramer, Cade Mirchandani, Devika Torvi, Robert Lanfear, Russell Corbett-Detig, and Yatish Turakhia, "matOptimize: a parallel tree optimization method enables online phylogenetics for SARS-CoV-2", Bioinformatics (2022) | DOI | Github | Slides | Video

  • Yatish Turakhia, Bryan Thornlow, Angie S. Hinrichs, Nicola De Maio, Landen Gozashti, Robert Lanfear, David Haussler, and Russell Corbett-Detig, "Ultrafast Sample placement on Existing tRees (UShER) enables real-time phylogenetics for the SARS-CoV-2 pandemic", Nature Genetics (2021) | DOI | Github | Slides | Video

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Wastewater-based Epidemiology | tracking pathogen evolution and transmission

Wastewater-based epidemiology (WBE) analyzes community sewage to recover genome sequences of circulating pathogens. A UC San Diego team showed that WBE can detect emerging variants up to two weeks earlier than traditional clinical genomic surveillance.

Today, WBE is being rapidly adopted worldwide to monitor pathogens such as SARS-CoV-2, RSV, mpox, influenza, and polio, yet the resulting torrent of data poses significant computational and algorithmic challenges.

We are developing algorithms and software that enhance the accuracy, resolution, and timeliness of wastewater genomics.

Related Publications

  • Pranav Gangwar, Qiwen Xu, Jaden Seangmany, Pratik Katte, and Yatish Turakhia, "metaWEPP: leveraging biobank-scale intra-species phylogenies for near-haplotype resolution in metagenomic analysis" NAR Genomics and Bioinformatics (2026). | DOI | Github | Website | Slides

  • Pranav Gangwar, Pratik Katte, Manu Bhat, and Yatish Turakhia, "WEPP: Phylogenetic Placement Achieves Near-Haplotype Resolution in Wastewater-Based Epidemiology" PLOS Computational Biology (2026). | DOI | Github | Website | Slides | Video