Dr. Steven G. Clarke is a Distinguished Professor at UCLA Department of Chemistry & Biochemistry and director of research at the Molecular Biology Institute . His work bridges protein chemistry , methylation biology , and aging research through studies of spontaneous protein damage and its repair mechanisms. Education: BA in Chemistry and Zoology, Pomona College (magna cum laude, Phi Beta Kappa) PhD in Biochemistry and Molecular Biology, Harvard University (NSF Fellow) Postdoctoral Fellowship at UC Berkeley (Miller Fellow) Dr. Clarke's research focuses on protein isoaspartyl repair via PCMT1/PIMT enzymes , ribosomal protein methylation in Saccharomyces cerevisiae , and PRMT family characterization including PRMT7 and PRMT9. His lab combines biochemical assays , genetic models , and structural analysis to investigate aging mechanisms and disease implications. Recent publications highlight: COQ5 structure-function analysis in coenzyme Q biosynthesis PCMTD1 ubiquitin ligase interactions PRMT7 substrate specificity in histone H2B Protein isoaspartyl impacts on T cell function in lupus Novel PRMT inhibitors for cancer therapy Methionine addiction in osteosarcoma malignancy Major scientific awards: American Chemical Society Ralph F. Hirschmann Award in Peptide Chemistry NIH MERIT Award Ellison Medical Foundation Senior Scholar Award William C. Rose Award, ASBMB UCLA Distinguished Teaching Award (Eby Award winner) Current lab members include PhD candidates Eric Pang (UCSB) and Sining "Cindy" Wang (UCLA), while undergraduates Celeste Medina-Seymoure , Elizabeth Oroudjeva , Olivia Pacheco , and Jasmine Winter contribute to ongoing proteostasis studies. Collaborations with Profs. Jose Rodriguez and Catherine Clarke demonstrate interdisciplinary research approaches.
Dana Pe'er is a Professor and Chair of the Computational and Systems Biology Program at the Sloan Kettering Institute (SKI) of Memorial Sloan Kettering Cancer Center. She is also an Investigator of the Howard Hughes Medical Institute and holds the Alan and Sandra Gerry Endowed Chair. Dr. Pe'er leads an interdisciplinary research group that combines advanced genomics approaches with machine learning to address fundamental questions in biomedical science, with particular focus on cancer biology, developmental biology, and immunology. Dr. Pe'er earned her PhD from Hebrew University in Jerusalem, Israel. Her academic journey includes a postdoctoral fellowship with George Church at Harvard Medical School. Before joining Memorial Sloan Kettering Cancer Center in 2016, she held faculty positions at Columbia University. Dr. Pe'er's research focuses on understanding cellular plasticity, the consequences of intra-tumor heterogeneity, cancer evolution and metastasis, and the mechanisms by which regulatory circuits go awry in disease. Her lab combines single-cell and spatial profiling technologies with machine learning approaches to investigate gene regulation, cellular plasticity, and cell-cell communication in the contexts of cancer, immunity, and development. They are particularly interested in how organisms develop from a single cell to generate diverse cell types, how epigenetic control rewires during development, and how cells communicate to execute multicellular responses. Analysis of Dr. Pe'er's recent publications reveals a strong focus on developing computational methods for single-cell and spatial genomics data analysis. Her work spans cancer types including pancreatic, prostate, colorectal, and breast cancer, with emphasis on tumor heterogeneity, metastasis mechanisms, and cellular plasticity. A significant portion of her research involves creating novel algorithms and tools like CellRank, REUNION, and SEACells that enable researchers to extract meaningful biological insights from complex genomic datasets. 2023 Class of 2023 Inductee - American Academy of Cancer Research (AACR) Academy 2023 Innovator Award - International Society for Computational Biology (ISCB) 2021 Fellow - International Society for Computational Biology (ISCB) Howard Hughes Medical Institute Investigator (2021) 2019 Ernst W. Bertner Memorial Award - University of Texas MD Anderson Cancer Center 2016 Lenfest Distinguished Faculty Award - Columbia University 2014 Director's Pioneer Award - National Institutes of Health 2014 Overton Prize - International Society for Computational Biology (ISCB) Dr. Pe'er is known for her dedicated mentorship approach, describing herself as "a mama bear" who cares deeply about her trainees while expecting independence, innovation, and hard work. She mentors numerous PhD students and postdocs in her lab. Her HHMI Investigator award provides approximately $9 million over seven years, enabling ambitious research directions. She also collaborates extensively with the Single-cell Analytics and Innovation Lab (SAIL) at MSK to generate new data from emerging technologies, working closely with wet-lab collaborators at MSK and beyond to apply computational methods to cutting-edge datasets across multiple disease areas. The Pe'er Lab is an interdisciplinary group of computational biologists with diverse backgrounds ranging from pure mathematics to clinical medicine. They work closely with wet-lab collaborators to apply their computational methods to cutting-edge datasets across cancer, immunology, and developmental biology. The lab is described as open, supportive, collaborative, and fun, with access to world-class facilities at the Sloan Kettering Institute. Dr. Pe'er's work continues to push the boundaries of computational biology and cancer research, with the ultimate goal of developing more effective, personalized therapies for cancer patients.
Dr. Christina Leslie is a Research Professor and Member of the Computational & Systems Biology Program at Memorial Sloan Kettering Cancer Center (MSK). She leads an active research laboratory focused on developing computational approaches to understand complex biological systems. Dr. Leslie earned her PhD from the University of California, Berkeley and has established herself as a leading computational biologist in cancer research and immunology. Computational & Systems Biology Program, Memorial Sloan Kettering Cancer Center Gerstner Sloan Kettering Graduate School of Biomedical Sciences Dr. Leslie's research focuses on developing novel computational methods to study cellular biological systems from a global and data-driven perspective. Her lab exploits diverse high-throughput functional and genomic data to understand molecular networks underlying fundamental cellular processes, including transcription regulation, pre-mRNA processing, signaling, and post-transcriptional gene silencing. Her algorithmic methods draw heavily on machine learning to build accurate predictive models from noisy and high-dimensional biological data. Key areas of interest include modeling cell-type specific transcriptional programs and dissecting co- and post-transcriptional regulation, particularly microRNA-mediated gene regulation. Analysis of Dr. Leslie's publication record over the last five years reveals a strong focus on computational approaches to cancer genomics, immunology, and epigenetics. Her work bridges multiple disciplines, with a particular emphasis on developing machine learning methods to interpret complex biological data. The publications demonstrate increasing sophistication in integrating multiple data types (genomic, transcriptomic, epigenomic) to understand cancer biology and immune responses. Recent work shows a growing emphasis on single-cell technologies and spatial analysis of tumor microenvironments. Introduction of string kernel methodology for SVM classification of biological sequences Development of algorithms for predictive modeling of gene regulation First systems-level analyses of competition between microRNAs and between target transcripts Dr. Leslie actively mentors numerous graduate students and research associates, with current lab members including Vianne Gao, Alireza Karbalaghareh, Erik Ladewig, and several others. Her lab has received significant research funding to support their work on computational approaches to cancer biology and immunology. The Leslie Lab maintains close collaborations with multiple experimental groups at MSK, facilitating the translation of computational insights into biological understanding. The Leslie Lab operates within the Computational & Systems Biology Program at MSK, with strong ties to both the research and clinical missions of the institution. The lab maintains state-of-the-art computational infrastructure for analyzing large-scale genomic and proteomic datasets and collaborates extensively with wet-lab researchers to validate computational predictions experimentally.
Michael Levin is a Vannevar Bush Professor and Distinguished Professor at Tufts University, affiliated with the School of Arts and Sciences (Department of Biology) and School of Engineering (Biomedical Engineering). His research focuses on bioelectricity, developmental biology, and collective intelligence. He leads the Allen Discovery Center and the Tufts Center for Developmental and Regenerative Biology. Education: PhD in Genetics from Harvard Medical School (1996); BS in Computer Science and Biology from Tufts University (1992). Research Interests: Integrates developmental biology, computer science, and cognitive science to study morphogenesis, regeneration, and cancer. Explores bioelectric signaling, synthetic organisms, and AI-driven discovery. Key areas include regenerative medicine, cancer reprogramming, and collective intelligence in biological systems. Publications: Over 600 articles, with recent work on xenobots, neuroevolution, and bioelectric therapies. Themes include bioelectric control of form, AI in biology, and collective intelligence. Awards: INNS Donald O. Hebb Award, AAAS Fellow, and Vox Future Perfect 50 List recognition. Frequently invited to speak at conferences on biology, AI, and consciousness. Advising & Labs: Mentored numerous postdocs and students, including pioneers in bioelectricity and synthetic biology. Lab focuses on interdisciplinary approaches to biological pattern formation and regeneration.
Anna G Orr serves as Nan and Stephen Swid Assistant Professor of Frontotemporal Dementia Research and Assistant Professor of Neuroscience at Weill Cornell Medical College's Brain and Mind Research Institute since 2016, leading pioneering research on astrocyte biology in dementia pathogenesis. Her educational background includes: Ph.D. from Emory University (2008) B.S. from Allegheny College (2002) Dr. Orr's research program centers on astrocytic-neuronal interactions , mitochondrial signaling , and neuroimmune mechanisms through three interconnected pathways: neuroimmune , oxidative , and G protein-coupled signaling . Her lab investigates how these mechanisms influence neuroinflammation, protein aggregation, synaptic function, and behavioral outcomes in dementia, with parallel therapeutic discovery efforts targeting astrocytic pathways for novel dementia treatments. Analysis of her 15 most recent publications (2025-2010) reveals escalating focus on astrocyte-specific dementia mechanisms , particularly mitochondrial ROS signaling, sex-dimorphic memory effects, TDP-43 pathology interactions with antiviral pathways, and lipid dysregulation in neurodegeneration. Her work consistently bridges molecular discoveries with therapeutic applications, demonstrating increasing NIH funding support for translational approaches. Key scientific recognitions include: NIH K99/R00 Pathway to Independence Award (2017) Leon Levy Fellowship in Neuroscience (2021) Nan and Stephen Swid Endowed Professorship (2021) Outstanding Neuroscience Teaching Award (2021) Dr. Orr actively mentors eight trainees across career stages, including Ph.D. candidates Evelyn Hardin and Constance Zhou, while securing major NIH grants as Principal Investigator for projects like Uncovering Dementia-Related Lipid Alterations in Astrocytes (NIA 2024-2026) and Mitochondrial Complex III Free Radicals in Dementia Pathology (NIA 2020-2026), alongside collaborative awards from the Alzheimer's Association. Her Orr Lab maintains a dual focus on mechanistic astrocyte biology and therapeutic translation, with current projects examining astrocytic TDP-43 dysregulation, mitochondrial complex III signaling, and sex-specific memory mechanisms using advanced in vivo techniques and disease models.
Keisuke Ishihara is an Assistant Professor in the Department of Computational and Systems Biology at the University of Pittsburgh School of Medicine. His research focuses on engineering human brain and cardiac organoids using genetic, chemical, and computational approaches to uncover novel regulatory mechanisms and physical principles underlying tissue development. His lab is located at Biomedical Science Tower 3, with an office in room 10020A. Dr. Ishihara holds a PhD in Systems Biology from Harvard University. His work bridges synthetic biology, developmental biology, and biophysics to address fundamental questions in organogenesis and cellular morphogenesis. Recent research highlights include studies on BMP-mediated neural tube patterning in organoids and the biophysical dynamics of microtubule assemblies in large cells. Publications from his lab emphasize interdisciplinary approaches to understand cell size scaling, mitotic spindle dynamics, and self-organization in synthetic tissues. His team has contributed to advancements in organoid technology, uncovering dormant genetic programs and physical principles governing tissue architecture. Laboratory activities are centered at the University of Pittsburgh, collaborating with the School of Medicine's computational and systems biology initiatives. For more details, visit his lab website linked below.
Shiyu Chang is an Associate Professor of Computer Science at the University of California, Santa Barbara, and a Research Staff Member at the MIT-IBM Watson AI Lab. His work bridges machine learning, natural language processing, and computer vision with a focus on interpretability and robustness. Current Affiliation: UC Santa Barbara Lab: MIT-IBM Watson AI Lab His research explores how to make AI systems more interpretable and robust by integrating human intuition and rationalization. Key themes include adversarial learning, self-supervised methods, and improving transferability in models. Recent publications span conferences like ICML, CVPR, and NeurIPS, addressing topics such as black-box text classification, fairness-aware algorithms, and speech representation disentanglement. Broad keywords include Machine Learning, NLP, and Computer Vision. Fairness Reprogramming (AI Fairness) TransGAN: Transformer-based GANs Adversarial Robustness Certificates
Stelios Andreadis is the SUNY Distinguished Professor of Chemical and Biological Engineering at the University at Buffalo, affiliated with the School of Engineering and Applied Sciences. He directs the Cell, Gene and Tissue Engineering Center and previously led the Stem Cells in Regenerative Medicine (SCiRM) Training Program. His research focuses on stem cell bioengineering, vascular and gland tissue engineering, and biomaterials design. He holds a PhD in Chemical Engineering from the University of Michigan and has been funded by NIH, NSF, and NYSTEM, totaling over $20M. His awards include the NSF CAREER Award, SUNY Chancellor’s Excellence in Scholarship, and AIMBE and BMES Fellowships. Research interests span stem cell rejuvenation, cell-free vascular grafts, and metabolic reprogramming. He has published 140+ papers and advised 28 PhD students, many now in academia or industry. His lab co-founded Angiograft, LLC to commercialize vascular grafts. Key achievements include developing self-healing vascular grafts and demonstrating monocyte recruitment for vascular regeneration. His work bridges basic science and clinical applications in regenerative medicine.
Andrea H. Brand serves as the Frederick L. Ehrman Professor of Cell Biology and Professor of Neuroscience at NYU Grossman School of Medicine, New York University, where she chairs the Department of Cell Biology. Her dual appointments reflect an interdisciplinary research program spanning molecular mechanisms of stem cell regulation and neural development. Dr. Brand earned her PhD from the University of Cambridge followed by prestigious postdoctoral fellowships: a Leukemia Society Special Fellowship at Harvard Medical School and a Helen Hay Whitney Fellowship at Harvard University. These foundational experiences established her expertise in genetic model systems. Her research integrates stem cell biology and neuroscience through innovative work with Drosophila and mouse models. Key investigations focus on chromatin dynamics in stem cell quiescence, Notch/insulin signaling pathways, neural progenitor reprogramming, and blood-brain barrier formation. Current projects explore obesity-related gene function and CHD8 genomic targets relevant to neurodevelopmental disorders, emphasizing translational potential for regenerative medicine. Recent publications (2020-2022) reveal consistent themes in stem cell niche organization and disease mechanisms, with notable contributions to understanding tumorigenesis through neural progenitor studies and metabolic influences on barrier development. Her work demonstrates strong interdisciplinary convergence between developmental genetics and systems neuroscience. No scientific awards were documented in the provided profile information. While the profile indicates Professor Brand's leadership as Department Chair, specific details regarding student mentorship, grant funding, or laboratory structure were not included in the available text. Her position suggests active supervision of research teams and potential involvement in major collaborative initiatives.
Zhandong Liu is an Associate Professor at Baylor College of Medicine with joint appointments in the Department of Pediatrics and Department of Neurology . He serves as Chief of Computational Sciences at Texas Children's Hospital and co-directs the Quantitative & Computational Biosciences Graduate Program at Baylor. Education: B.S. in Computer Science, Nankai University (2001) M.S. in Computer Science, Wayne State University (2003) Ph.D. in Genomics and Computational Biology, University of Pennsylvania (2010) Dr. Liu's research integrates genomics , machine learning , and bioinformatics to advance understanding of neurological diseases. His work focuses on: Multi-omics data integration for disease mechanism discovery Development of cloud-based CRISPR analysis tools like CRISPRcloud Augmented reality platforms for biomedical data visualization Identification of disease genes through computational models Alternative splicing analysis in cancer and neurodegeneration Single-cell and spatial transcriptomics algorithms His recent publications emphasize Alzheimer's disease , MECP2 syndromes , and computational therapy prediction across multiple domains. Scientific awards include the 2018 Outstanding Service Award from the International Association for Intelligent Biology and Medicine. He has secured major grants from NIH, CPRIT, and NSF for projects including: NSF grant #199977 (2018-2020): Augmented reality therapy platforms CPRIT grant #RP170387 (2016-2019): Network-guided cancer analysis NIH #1R01AG057339 (2017-2022): Alzheimer's disease networks As head of the Liu Lab , he leads teams developing tools like: MARRVEL : Human-model organism gene variant integration CRISPRcloud : Secure CRISPR screen analysis platform CrypSplice : Cryptic splicing detection algorithm
Dana Pe'er is Chair of the Computational and Systems Biology Program at the Sloan Kettering Institute (SKI) and an Investigator at the Howard Hughes Medical Institute (HHMI). She holds the Alan and Sandra Gerry Endowed Chair and leads an interdisciplinary lab combining single-cell genomics, machine learning, and computational modeling to study cancer biology, immunity, and development. Pe'er earned her PhD at the Hebrew University in Jerusalem and focuses on cellular plasticity, epigenetic regulation, and tumor-immune interactions. Her lab develops tools like CellRank , Wishbone , and SEACells to analyze single-cell data and uncover mechanisms in cancer progression and immunotherapy. Key research areas: Computational Biology, Single-Cell Genomics, Cancer Systems Biology, Epigenetics, Immunotherapy Recent trends: Articles from 2025-2024 emphasize spatial transcriptomics, tumor microenvironment mapping, and regulatory network inference using machine learning. Scientific honors include the NIH Director’s Pioneer Award , AACR Academy Induction , and Packard Fellowship . Her work has direct clinical implications for precision medicine and cancer immunotherapy. Labs & Teams: Leads the Dana Pe'er Lab at SKI, directs the Single Cell Research Initiative (SCRI), and collaborates with the SAIL program.
Shyni Varghese is the Laszlo Ormandy Distinguished Professor of Orthopaedic Surgery at Duke University, with joint appointments in Mechanical Engineering & Materials Science and Biomedical Engineering. She directs the Varghese Lab, an interdisciplinary team focused on smart biomaterials, organ-on-chip models, rejuvenation therapies, and translational medical technologies. Her research bridges tissue engineering, regenerative medicine, and disease modeling to address bone healing, osteoarthritis, and age-related tissue degeneration. Education: Ph.D. in Chemistry/Materials Science, National Chemical Laboratory (India), 2002 Research spans four pillars: Smart Biomaterials : Engineered ECM mimetics, self-healing hydrogels, and stimuli-responsive systems for tissue regeneration. Miniature Organs : Organoid and organ-on-chip platforms (e.g., tumor-on-chip, lung alveolus models) to study disease mechanisms. Rejuvenation : Targeting cellular senescence, adenosine signaling, and inflammation to enhance aged tissue repair. Bench to Bedside : Translating technologies like 'bone bandages' and nanocarriers for fracture healing and osteoporosis. Recent publications emphasize orthopaedic repair (fracture healing, osteoarthritis), immunomodulation (macrophage reprogramming, immunotherapy), and advanced biomaterials (self-healing lubricants, cartilage-penetrating carriers). Studies frequently employ mouse models and microengineered platforms to dissect pain mechanisms, senescence, and tissue regeneration pathways. Dr. Varghese advises 10+ doctoral students and postdoctoral researchers. Her lab has pioneered innovations like 'DraBot' (environment-responsive soft robot) and 'cell pouch' xenotransplantation devices. Collaborative projects include NIH-funded work on bone radioprotection and NSF-supported biomaterial design. The Varghese Lab occupies the Duke Medical Science Research Building, fostering collaborations with clinicians and engineers. Current projects explore: Senolysis for neuroinflammation mitigation Adenosine-based therapies for bone loss 3D tumor models for immunotherapy screening
Heather R. Christofk is a Professor in the Department of Biological Chemistry at the David Geffen School of Medicine at UCLA. Her research focuses on the intricate relationship between cellular metabolism and various biological processes, particularly in the contexts of cancer development, stem cell function, and viral infections. Education: PhD in Cell and Developmental Biology from Harvard University (2007) BS in Molecular, Cell, and Developmental Biology from UCLA (2001) Dr. Christofk's research program centers on understanding how metabolic pathways regulate cellular processes in both normal physiology and disease states. Her laboratory has made significant contributions to understanding how cancer cells reprogram their metabolism to support rapid growth and proliferation, with particular focus on glucose metabolism, amino acid utilization, and metabolic adaptations in tumor microenvironments. She has also pioneered work on the metabolic regulation of stem cell function, especially in hair follicle stem cells, demonstrating how metabolic pathways control stem cell activation and differentiation. Her research has important implications for developing novel therapeutic approaches that target cancer metabolism while preserving normal tissue function. Analysis of Dr. Christofk's recent publications reveals a strong focus on metabolic heterogeneity across different biological contexts. Her work spans cancer metabolism (particularly in liposarcoma, melanoma, and hepatocellular carcinoma), stem cell metabolism (especially hair follicle stem cells), viral metabolism (including Epstein-Barr virus and Zika virus), and developmental metabolism (fetal development and organogenesis). A recurring theme is how metabolic pathways serve as regulatory nodes that control cell fate decisions, tumor progression, and therapeutic responses. Selected Research Funding: Metabolic Control of Hair Follicle Stem Cell Homeostasis and Tumorigenesis (NIH R01AR070245, 2018-2023) - Co-Principal Investigator Nutrient regulation of cancer cell growth (NIH R01CA215185, 2017-2022) - Principal Investigator Regulation of the Warburg Effect in Cancer (NIH DP2OD008454, 2011-2016) - Principal Investigator Dr. Christofk's laboratory maintains active collaborations across multiple disciplines, working with clinicians, basic scientists, and computational biologists to address complex questions in metabolism and disease. Her team employs a range of cutting-edge techniques including metabolomics, stable isotope tracing, molecular biology, and in vivo models to investigate metabolic regulation in health and disease.
Dr. Zhengqing Hu is a tenured, full-time Professor in the Department of Otolaryngology – Head and Neck Surgery at Wayne State University School of Medicine. He holds joint appointments in the Department of Physiology/Cell Biology and has active research programs in stem cell-based hearing restoration. Dr. Hu's academic journey includes dual MD and PhD training in China, a second PhD at Karolinska Institute, Sweden, and postdoctoral work at the University of Virginia. Education : MD from Shanghai Medical University, PhD in neurotology from China, second PhD in cell replacement therapy at Karolinska Institute Grants : NIH R01, DoD grants, VA SPiRE, and Wayne State OVPR funding His research focuses on auditory synapse regeneration , epigenetic reprogramming for hair cell repair, and development of biological hearing restoration models . The Hu lab employs stem cell biology, in vitro and in vivo transplantation, advanced microscopy, and electrophysiology to investigate inner ear progenitor cell differentiation and neural integration. Recent publications highlight DNA demethylation strategies for hair cell regeneration and auditory neuron synaptogenesis. Dr. Hu serves on multiple NIH, VA, and international grant review panels. He teaches graduate courses in Stem Cell Biology , Molecular Physiology , and Cell Biology at Wayne State University, including directing the Embryonic Stem Cell Biology course. His lab's work aims to establish a Biological-EAR model for future hearing loss treatments.
Dr. Yanjie Fu is an Associate Professor in the School of Computing and AI at Arizona State University, part of the Ira A. Fulton Schools of Engineering. He maintains his office in BYENG 506 at the Tempe campus and can be reached at yanjie.fu@asu.edu. Dr. Fu received his Ph.D. from Rutgers University in 2016, the B.E. degree from the University of Science and Technology of China, and the M.E. degree from the Chinese Academy of Sciences. His industry research experience includes positions at Microsoft Research Asia and IBM Thomas J. Watson Research Center. His research focuses on developing disruption-robust machine intelligence that can handle imperfect and complex data. Dr. Fu's work spans two major efforts: Data for AI (D4AI), exploring how structure knowledge of data can guide AI, and AI for Data (AI4D), investigating how AI can augment, reprogram, and knowledgeize data. His current research interests include space-time intelligence, data-centric AI, sim2decision, multimodal reasoning, and LLM with agentic AI. His lab has contributed projects including D4AI-spatial, D4AI-timeseries, D4AI-causal outliers, AI4D-RL, AI4D-Gen, and AI4D-LLM. Dr. Fu's recent publications reveal a strong trend toward integrating causal reasoning with deep learning for robust anomaly detection, advancing time series forecasting with novel normalization techniques, and applying generative AI to urban planning. His work increasingly bridges traditional machine learning with large language models, particularly focusing on data-centric approaches for tabular data transformation and feature engineering. US NAE FOE early career engineer (2023) US NSF CAREER (2021) NSF CRII (2018) ACM KDD18 Best Student Paper Finalist IEEE ICDM Best Paper Finalist (2014, 2021, 2022) ACM SIGSpatial Best Paper Runner-up (2020) 2022 Baidu Scholar global top Chinese young scholars in AI 2021 Aminer.org AI 2000 Most Influential Scholar Award Honorable Mention Dr. Fu has successfully mentored multiple Ph.D. students who have secured tenure-track faculty positions at prestigious institutions including University of Kansas, Chinese Academy of Sciences, Great Bay University, Portland State University, and University of Macau. His research has been supported by significant grants including the NSF CAREER award, and he currently serves as Associate Editor of ACM Transactions on Knowledge Discovery from Data. He is also a senior member of both ACM and IEEE. Dr. Fu leads a research group focused on developing trusted and safe machine intelligence. The lab connects computing issues across representation learning, self-supervised learning, interactive learning, adaptive learning, and stream learning to build disruption-robust frameworks. The group executes two key steps: data representation construct (integrating structure knowledge, self-optimization, explainability) and learning strategy construct (integrating robust representations with adaptive and interactive learning).
