Prof. Yatish Turakhia

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

My lab is also affiliated with the Center of Machine-Integrated Computing and Security (MICS), the Center of Microbiome Innovation (CMI), and the Institute for Genomic Medicine (IGM) at UCSD.

My recent CV.

Email: yturakhia [at] ucsd [dot] edu

Contact: +1 (858) 534-4496

Office: Room 0104, Franklin Antonio Hall, UC San Diego

Latest News

Sep 2025: Pranav passes his PhD qualifying exam. Congratulations, Pranav!
Aug 2025: Sumit passes his PhD qualifying exam. Congratulations, Sumit!
Aug 2025: Yatish presents a talk at University of Chicago on GPU-Accelerated Construction of Ultra-Large Pangenomes via Alignment-Phylogeny Co-Estimation
Aug 2025: Allen Yan and Alan Wang present at the UCSD Summer Research Conference
Aug 2025: Sumit Walia and Zexing Chen et al. release a preprint on DIPPER.
Aug 2025: Yu-Hsiang passes his PhD prelims exam. Congratulations, Yu-Hsiang!
July 2025: Yu-Hsiang attends ISMB/ECCB 2025 to present TWILIGHT.
July 2025: Sumit attends ISMB/ECCB 2025 to present PanMAN.
July 2025: TWILIGHT is published in Bioinformatics. Congratulations, Yu-Hsiang and Sumit!
June 2025: Yatish presents a talk at Barcelona Supercomputing Center on Algorithms, Software, and Hardware Accelerators for the Next Wave of Genomic Data
June 2025: Yatish presents a talk at ETH Zurich on Algorithms, Software, and Hardware Accelerators for the Next Wave of Genomic Data
June 2025: Yatish presents a talk at Biozentrum, University of Basel on Compressive Pangenomics and Applications to Global Pathogen Surveillance
June 2025: Yatish presents a talk at PASC 2025 Minisymposium on Building Ultra-large Pangenomes
June 2025: Yu-Hsiang presents TWILIGHT at Evolution 2025.
June 2025: Pranav Gangwar et al. release a preprint on WEPP.
June 2025: Pranav presents WEPP at Wastewater Disease Surveillance Summit 2025.
May 2025: Yatish presents a talk at Fred Hutch Cancer Center on Compressive Pangenomics and Applications to Global Pathogen Surveillance
May 2025: Jaden and Qiwen present their research project at UCSD Undergraduate Engineering Research Symposium.
May 2025: ROADIES is highlighted as the cover feature in PNAS.
May 2025: ROADIES is published in PNAS. Congratulations, Anshu!
Apr 2025: Yatish wrote a Technical Perspective for a Research Highlight in the Communications of the ACM.
Apr 2025: Turakhia Lab welcomes new members Anika Agarwal and Allen Yan to the lab.
Mar 2025: Yatish presents a talk at BME Seminar, UC Santa Cruz on Building Ultra-large Pangenomes
Feb 2025: Yatish receives the Jacobs School Early Career Faculty Development Award to harness Pangenomics for trait association studies in collaboration with Prof. Melissa Gymrek.
Jan 2025: Kyle Smith gets an Honorable Mention in the 2024-2025 CRA Outstanding Undergraduate Researcher Award. Congratulations, Kyle!
Jan 2025: Turakhia Lab welcomes new members Jaden Seangmany and Qiwen Xu to the lab.
Nov 2024: Yatish gives a talk on “Scaling Up Phylogenetics” at ICERM Workshop 2024 at Brown University.
Nov 2024: Yingqi Cao and Anshu Gupta et al. release a preprint on DP-HLS.
Oct 2024: Yatish gives HPC Sync talk at AMD.
Oct 2024: Yatish selected as one of the '100 Young Scientists' worldwide at 2024 WLA forum, Shanghai, China.
Oct 2024: Turakhia Lab welcomes new members Jade Wang and Fahad Alkhazam to the lab.
Sep 2024: Sunreet Khanna joins lab co-advised with Prof. Bill Lin. Welcome, Sunreet!
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Affiliations

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.

Research Mission

We are an interdisciplinary group of researchers working on a broad range of problems at the cutting-edge intersection of computer engineering and bioinformatics.

We work on problems that have enormous potential in biological and medical applications but where computational costs and speed impose a barrier.

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 and high-throughput sequencing have enabled extensive genome sequencing, leading to the emergence of Pangenomics, an area that studies genetic variation within a species using a collection of genomes. This research is set to impact numerous fields but requires a shift from traditional single-reference genome approaches. 

Our team is developing new data structures, algorithms, and hardware acceleration to facilitate compressive, comprehensive and faster pangenomic analysis.

Related Publications

  • Sumit Walia, Harsh Motwani, Kyle Smith, Russell Corbett-Detig, Yatish Turakhia, "Compressive Pangenomics Using Mutation-Annotated Networks" bioRxiv (2024) | DOI | Talk | PDF

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Phylogenetics | study evolutionary relationships of species

Phylogenetics studies the evolutionary relationships among biological sequences, organisms, or species, with applications in evolutionary biology, outbreak analysis, and comparative genomics. Large-scale consortiums like VGP and Earth Biogenome Project generate vast genomic data, offering deeper insights into species evolution. However, constructing and analyzing large-scale phylogenies presents computational challenges.

In collaboration with Prof. Siavash Mirarab's Lab at UCSD, our team focuses on developing new automated, scalable, hardware-software co-designed solutions to address these challenges.

Related Publications

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

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Hardware Acceleration | make computational genomics faster

Genomic data is one of the fastest-growing data types on the planet and is far outpacing Moore’s law. From personalized medicine to species conservation, genomic data has far-reaching applications, but computational costs are posing ever greater challenges to exploit the full potential of this data. 

We are developing novel algorithms and hardware (GPU/FPGA/ASIC) acceleration approaches to speed computational genomics tasks, such as genome assembly, read alignment, multiple sequence alignment, and whole-genome alignments, by orders of magnitude.

Related Publications

  • Sumit Walia, Zexing Chen, Yu-Hsiang Tseng, Yatish Turakhia, "Ultrafast and Ultralarge Distance-Based Phylogenetics Using DIPPER", bioRxiv (2025) | DOI | PDF

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

  • Yingqi Cao, Anshu Gupta, Jason Liang, Yatish Turakhia, "DP-HLS: A High-Level Synthesis Framework for Accelerating Dynamic Programming Algorithms in Bioinformatics", arXiv (2024) | DOI | Talk | PDF

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

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

  • 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 | Talk | PDF

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

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Outbreak Analysis | real-time phylogenetics for pandemic analysis

With over 16 million (and counting) whole SARS-CoV-2 genomes sequences already, the COVID-19 pathogen is the most sequenced pathogen in history. Phylogenetic analysis using these genomes has played a vital role in tracking the virus evolution and transmission, but is posing major computational challenges.

Our lab is working closely with Prof. Russell Corbett-Detig’s lab at UC Santa Cruz in maintaining and refining a comprehensive phylogenetic tree consisting of all available SARS-CoV-2 genomes.

Related Publications

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

  • 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 | Talk

  • 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 | Talk

  • 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 | Talk

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Wastewater-based Epidemiology | tracking pathogen evolution and transmission

Wastewater-based epidemiology (WBE) involves analyzing sewage data to identify the genome sequences of disease-causing pathogens. A UCSD team demonstrated that WBE can even detect emerging variants up to two weeks earlier than traditional clinical genomic surveillance.

Today, WBE is being rapidly adopted worldwide to monitor a broad spectrum of pathogens, including SARS-CoV-2, RSV, Monkeypox, influenza, and Polio. However, the vast amount of WBE data presents significant computational and algorithmic challenges.

We are developing novel algorithms and software tools that aim to enhance the accuracy, resolution, and timeliness of current WBE tools.

Related Publications

  • Pranav Gangwar, Pratik Katte, Manu Bhat, and Yatish Turakhia, "WEPP: Phylogenetic Placement Achieves Near-Haplotype Resolution in Wastewater-Based Epidemiology" medRxiv (2025) | DOI | Talk | PDF