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Nova · Professor Researcher · re-ranking top 20…
Su Jia

Su Jia

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Cornell University · Operations Research and Information Engineering

Active 2011–2023

h-index5
Citations230
Papers2411 last 5y
Funding
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About

Su Jia is an Assistant Research Professor at the Center for Data Science for Enterprise and Society (CDSES) at Cornell University. His research focuses on the interplay between data, algorithms, and markets. Specifically, Su is interested in designing algorithms for learning and optimization problems in online marketplaces, including areas such as pricing, advertising, and A/B testing. He has been recognized for his contributions with the 2022 INFORMS George B. Dantzig Dissertation Award, which is given for the best dissertation in operations research and management sciences that is innovative and relevant to practice.

Research topics

  • Computer science
  • Mathematics
  • Algorithm
  • Artificial intelligence
  • Mathematical optimization

Selected publications

  • Transarterial chemoembolization with PD-(L)1 inhibitors plus molecular targeted therapies for hepatocellular carcinoma (CHANCE001)

    Signal Transduction and Targeted Therapy · 2023 · 272 citations

    • Medicine
    • Internal medicine
    • Gastroenterology

    There is considerable potential for integrating transarterial chemoembolization (TACE), programmed death-(ligand)1 (PD-[L]1) inhibitors, and molecular targeted treatments (MTT) in hepatocellular carcinoma (HCC). It is necessary to investigate the therapeutic efficacy and safety of TACE combined with PD-(L)1 inhibitors and MTT in real-world situations. In this nationwide, retrospective, cohort study, 826 HCC patients receiving either TACE plus PD-(L)1 blockades and MTT (combination group, n = 376) or TACE monotherapy (monotherapy group, n = 450) were included from January 2018 to May 2021. The primary endpoint was progression-free survival (PFS) according to modified RECIST. The secondary outcomes included overall survival (OS), objective response rate (ORR), and safety. We performed propensity score matching approaches to reduce bias between two groups. After matching, 228 pairs were included with a predominantly advanced disease population. Median PFS in combination group was 9.5 months (95% confidence interval [CI], 8.4-11.0) versus 8.0 months (95% CI, 6.6-9.5) (adjusted hazard ratio [HR], 0.70, P = 0.002). OS and ORR were also significantly higher in combination group (median OS, 19.2 [16.1-27.3] vs. 15.7 months [13.0-20.2]; adjusted HR, 0.63, P = 0.001; ORR, 60.1% vs. 32.0%; P < 0.001). Grade 3/4 adverse events were observed at a rate of 15.8% and 7.5% in combination and monotherapy groups, respectively. Our results suggest that TACE plus PD-(L)1 blockades and MTT could significantly improve PFS, OS, and ORR versus TACE monotherapy for Chinese patients with predominantly advanced HCC in real-world practice, with an acceptable safety profile.

  • Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2023

    Nucleic Acids Research · 2022 · 346 citations

    • Computer Science
    • Biology
    • Database

    The National Genomics Data Center (NGDC), part of the China National Center for Bioinformation (CNCB), provides a family of database resources to support global academic and industrial communities. With the explosive accumulation of multi-omics data generated at an unprecedented rate, CNCB-NGDC constantly expands and updates core database resources by big data archive, integrative analysis and value-added curation. In the past year, efforts have been devoted to integrating multiple omics data, synthesizing the growing knowledge, developing new resources and upgrading a set of major resources. Particularly, several database resources are newly developed for infectious diseases and microbiology (MPoxVR, KGCoV, ProPan), cancer-trait association (ASCancer Atlas, TWAS Atlas, Brain Catalog, CCAS) as well as tropical plants (TCOD). Importantly, given the global health threat caused by monkeypox virus and SARS-CoV-2, CNCB-NGDC has newly constructed the monkeypox virus resource, along with frequent updates of SARS-CoV-2 genome sequences, variants as well as haplotypes. All the resources and services are publicly accessible at https://ngdc.cncb.ac.cn.

  • Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2022

    Nucleic Acids Research · 2021 · 1088 citations

    • Computer Science
    • Data Mining
    • Database

    The National Genomics Data Center (NGDC), part of the China National Center for Bioinformation (CNCB), provides a family of database resources to support global research in both academia and industry. With the explosively accumulated multi-omics data at ever-faster rates, CNCB-NGDC is constantly scaling up and updating its core database resources through big data archive, curation, integration and analysis. In the past year, efforts have been made to synthesize the growing data and knowledge, particularly in single-cell omics and precision medicine research, and a series of resources have been newly developed, updated and enhanced. Moreover, CNCB-NGDC has continued to daily update SARS-CoV-2 genome sequences, variants, haplotypes and literature. Particularly, OpenLB, an open library of bioscience, has been established by providing easy and open access to a substantial number of abstract texts from PubMed, bioRxiv and medRxiv. In addition, Database Commons is significantly updated by cataloguing a full list of global databases, and BLAST tools are newly deployed to provide online sequence search services. All these resources along with their services are publicly accessible at https://ngdc.cncb.ac.cn.

  • An excitatory ventromedial hypothalamus to paraventricular thalamus circuit that suppresses food intake

    Nature Communications · 2020 · 98 citations

    • Neuroscience
    • Biology

    It is well recognized that ventromedial hypothalamus (VMH) serves as a satiety center in the brain. However, the feeding circuit for the VMH regulation of food intake remains to be defined. Here, we combine fiber photometry, chemo/optogenetics, virus-assisted retrograde tracing, ChR2-assisted circuit mapping and behavioral assays to show that selective activation of VMH neurons expressing steroidogenic factor 1 (SF1) rapidly inhibits food intake, VMH SF1 neurons project dense fibers to the paraventricular thalamus (PVT), selective chemo/optogenetic stimulation of the PVT-projecting SF1 neurons or their projections to the PVT inhibits food intake, and chemical genetic inactivation of PVT neurons diminishes SF1 neural inhibition of feeding. We also find that activation of SF1 neurons or their projections to the PVT elicits a flavor aversive effect, and selective optogenetic stimulation of ChR2-expressing SF1 projections to the PVT elicits direct excitatory postsynaptic currents. Together, our data reveal a neural circuit from VMH to PVT that inhibits food intake.

  • Strategies to Improve the Accuracy of Memristor-Based Convolutional Neural Networks

    IEEE Transactions on Electron Devices · 2020 · 73 citations

    • Computer Science
    • Artificial Intelligence
    • Computer Science

    In this article, we quantify several nonideal characteristics of memristor synaptic devices, such as the limited conductance states, write nonlinearities, and variations, and comprehensively investigate their effects on the convolutional neural network (CNN) performance. Our result shows that the available conductance states (N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">state</sub> ), asymmetric write nonlinearities, and cycle-to-cycle (C2C) variation are critical factors to the learning accuracy, while symmetric write nonlinearities and device-to-device variation go trivial. We accordingly propose three strategies to mitigate their impacts on CNN performance: 1) limiting the weight range to improve the utilization of Nstate; 2) adopting a new “with-read” update scheme to mitigate the effects of asymmetric write nonlinearities; and 3) employing multiple memristors for each kernel element to alleviate the impact of C2C variation. Our work would provide guidance for the hardware implementation and optimization of CNN in memristor crossbar.

  • Engineering unsymmetrically coordinated Cu-S1N3 single atom sites with enhanced oxygen reduction activity

    Nature Communications · 2020 · 909 citations

    • Computer Science
    • Chemistry
    • Materials science

    moiety acts as an active center during the oxygen reduction process. Our discovery provides a universal scheme for the controllable synthesis and performance regulation of single metal atom catalysts toward energy applications.

Frequent coauthors

Education

  • Graduate, Applied Math and Statistics

    Stony Brook University

    2017

Awards & honors

  • 2022 INFORMS George B. Dantzig Dissertation Award

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