Find Academic Supervisors

• Microbial Genomics
• Gut Microbiome
• Aging and Healthy Aging
• +4 more

Paul O'Toole is a Professor of Microbial Genomics and Principal Investigator at the APC Microbiome Ireland, University College Cork. His research focuses on the gut microbiome's role in health, aging, and disease, particularly in the context of diet and probiotics. He leads projects like the ELDERMET study on elderly nutrition and the NU-AGE project exploring Mediterranean diets' anti-aging effects. He holds a BA (Mod.) from Trinity College Dublin and a PhD from Lund University, with postdoctoral training in Canada and New Zealand. Key grants include studies on dairy-derived microbiota, probiotic strain improvement, and microbiome analysis in aging populations. He has published extensively on Lactobacillus genomics, gut-brain interactions, and microbiome-driven health outcomes. His work bridges fundamental microbiology with clinical applications, emphasizing translational research. Scientific highlights include discovering microbiome links to cognitive decline, demonstrating dietary modulation of gut microbes to combat obesity, and identifying keystone species in healthy aging. He advocates for sustainability in conservation and food systems, reflecting his interdisciplinary approach to global health challenges.

• Biomarkers
• Stroke Research
• Proteomics
• +7 more

Dr. Shubham Misra is a Research Fellow in the Department of Neurology at Yale University School of Medicine. He holds a Ph.D. in Neurology from the All India Institute of Medical Sciences (2022) and advanced degrees in Biotechnology from Amity University (2014). His research focuses on biomarker discovery, proteomics, and clinical data analysis in neurological disorders, particularly stroke and post-stroke epilepsy. Dr. Misra has authored over 50 peer-reviewed publications, including work in JAMA Neurology and Neurology , and leads research on omics-based approaches in stroke at Frontiers in Neurology. He collaborates globally, including with the WHO's Brain Health Unit to address neurological aspects of pandemics like COVID-19. Research Interests: Biomarker discovery using proteomics and machine learning, outcomes research in stroke, genetic risk factors for neurological disorders, and systematic reviews/meta-analyses. Dr. Misra's work bridges clinical neurology with advanced data science, aiming to improve diagnostics and patient outcomes. Awards: Young Investigator Award (World Stroke Organization), DST-INSPIRE Fellowship (India), and multiple international travel grants for collaborative research. Grants & Collaborations: Leads the International Post-stroke Epilepsy Research Repository (IPSERR) and collaborates with institutions worldwide. His work on post-stroke epilepsy and stroke subtyping biomarkers has been widely cited (over 1,200 citations). Labs & Teams: Mishra Lab at Yale, Rangaraju Lab, and global networks through the WHO's Global Forum and IPSERR consortium.

Zhe JiView profile

Assistant Professor

• Data Science
• Computational Biology
• Functional Genomics
• +4 more

Zhe Ji is an Assistant Professor in the Department of Biomedical Engineering at McCormick School of Engineering and the Department of Pharmacology at Feinberg School of Medicine, Northwestern University. His research integrates computational and experimental genomics to study gene transcription and RNA translation in cell fate commitment and oncogenic processes, aiming to develop precision medicine strategies. **Education**: Postdoctoral Fellow in Cancer Systems Biology, Harvard Medical School Postdoctoral Fellow in Computational Biology, Broad Institute of MIT and Harvard Ph.D. in Computational Genomics, Rutgers University B.S. in Biotechnology, Nanjing University, China **Research Focus**: Keywords include Data Science, Computational Biology, Functional Genomics, RNA, Cancer, Inflammation, and Machine Learning. The lab explores regulatory mechanisms underlying disease, with a focus on translational control, cancer metastasis, and inflammatory networks. **Grants & Advising**: No specific grants or student advisees listed. The lab emphasizes collaborative projects and computational-experimental approaches. **Lab Affiliations**: Zhe Ji’s lab is part of Northwestern’s interdisciplinary environment, bridging engineering and medicine to advance genomic technologies and therapeutic strategies.

Arash AramiView profile

Associate Professor

• Assistive Robotics
• Human-Robot Interaction
• Machine Learning
• +6 more

Arash Arami is an Associate Professor in the Department of Mechanical and Mechatronics Engineering at the University of Waterloo, cross-appointed in Systems Design Engineering. He directs the Neuromechanics and Assistive Robotics Laboratory and maintains affiliations with Waterloo Robohub, the Centre for Bioengineering and Biotechnology, Waterloo AI institute, and KITE institute at Toronto Rehab Institute. He earned his Doctorate in Electrical Engineering from EPFL (2014), Master of Science from University of Tehran (2009), and Bachelor of Science from University of Tabriz (2006), all in Control Engineering. His research in Assistive Robotics and Rehabilitation Engineering integrates Machine Learning with Neuromechanics to develop intelligent systems for human movement analysis. Key focus areas include exoskeleton control algorithms, wearable sensor systems, and neural control modeling for rehabilitation applications. Recent publications demonstrate interdisciplinary work spanning robotics, biomedical engineering, and materials science, with emphasis on real-time human locomotion prediction, exoskeleton-human interaction, and data-driven health monitoring solutions. Dr. Arami serves as Chair of the NSERC Scholarship Committee (2021-2023) and mentors graduate students through the Mechatronics Exchange Study program. His teaching includes core courses in control systems, robot manipulators, and biomechanical engineering. The Neuromechanics and Assistive Robotics Laboratory fosters collaborations with clinical partners at Toronto Rehab Institute, focusing on translating robotic innovations into practical rehabilitation tools through interdisciplinary teamwork.

• Robotics
• Mechatronics
• Humanoid Robots
• +4 more

Atsuo Takanishi is a distinguished Professor at Waseda University's Faculty of Science and Engineering, School of Creative Science and Engineering, with appointments in both the Department of Bioscience and Biotechnology and the Department of Modern Mechanical Engineering. With over 700 publications, 10,399 citations, and an h-index of 47, Professor Takanishi has established himself as a leading figure in robotics research. His work spans multiple institutions, including visiting positions at Showa University School of Dentistry and KDDI Research, Inc. Professor Takanishi received his Doctor of Engineering degree from Waseda University in 1985, following his undergraduate studies in the Faculty of Science and Engineering at the same institution, which he completed in 1980. His academic journey began with positions as an Assistant at Waseda University (1985-1988), Lecturer (1988-1990), and Associate Professor (1990-1997) before achieving his current Professor status. Professor Takanishi's research interests center around robotics and intelligent systems, with particular expertise in humanoid robotics, surgical dentistry applications, and biomechatronics. His work demonstrates a unique integration of mechanical engineering principles with biological systems, resulting in innovative robotic platforms that mimic human capabilities. Notably, his laboratory has developed the Waseda Anthropomorphic Saxophonist Robot series and various medical training simulators that have significantly advanced the field of human-robot interaction. His research in experimental psychology complements his robotics work, particularly in human-robot interaction studies. Analysis of Professor Takanishi's recent publications reveals a strong focus on practical applications of robotics technology, particularly in assistive devices for elderly mobility, medical training simulators, and agricultural robotics for Synecoculture environments. His work consistently bridges theoretical robotics with real-world implementation, with recent papers emphasizing reinforcement learning approaches, haptic feedback systems, and computer vision techniques for complex environments. The Waseda Anthropomorphic Saxophonist Robot series represents a culmination of decades of research in humanoid robotics and musical expression. IEEE Fellow (2020-present) Robotics Society of Japan Fellow (2012-present) Japan Society of Mechanical Engineers Fellow (2007-present) Multiple Best Paper Awards from IEEE conferences (ICRA, IROS, ROMANSY) BusinessWeek Asia's Stars Bloomberg (2001) IFToMM Award of Merit (2010) Professor Takanishi has maintained extensive collaborations with research institutions worldwide, particularly with Italian institutions through the Italy-Japan Workshop series. His laboratory has secured substantial funding from Japanese government agencies including the Japan Science and Technology Agency, with particular emphasis on projects bridging robotics with medical applications and human-centered technologies. His international recognition is evidenced by his numerous visiting professorships and collaborative projects across continents. Professor Takanishi leads the Takanishi Laboratory at Waseda University, which maintains specialized facilities for humanoid robotics development, medical robotics research, and human-robot interaction studies. The laboratory has developed several notable robotic platforms including the WABIAN series of bipedal humanoid robots, the WASEDA FLUTIST ROBOT, and various medical training simulators used in clinical education settings. His work on the WASEDA SAXOPHONIST ROBOT represents a unique fusion of musical artistry and robotics engineering.

• Numerical Modeling
• Computational Simulation
• Materials Science
• +5 more

Assoc Prof Ng Teng Yong is an Associate Professor at the School of Mechanical & Aerospace Engineering (NTU), specializing in numerical modeling and simulation. With a background as Research Manager at A*STAR Institute of High Performance Computing, his work spans materials science, nanotechnology, and aerospace engineering. Current focus on graphene-based desalination membranes Expertise in molecular dynamics simulations Investigates nanoscale fluid mechanics and structural dynamics Recent publications highlight advancements in energy-efficient electrodialysis, smart robotics, and nonlinear vibration analysis. His interdisciplinary approach integrates computational methods with experimental validation in additive manufacturing and soft material mechanics.

Michael WilczekView profile

Teaching Professor

• Virology
• Bioinformatics
• Molecular Epidemiology
• +3 more

Dr. Michael Wilczek is Assistant Teaching Professor in Biotechnology/Bioinformatics at Northeastern University's Roux Institute. His research bridges virology, bioinformatics, and educational innovation, with particular focus on JC polyomavirus pathogenesis and graduate education reform. Key research domains include: Molecular mechanisms of viral infections Bioinformatic analysis of host-pathogen interactions Observational health and real-world evidence Evidence-based graduate education His publication record demonstrates: Expertise in JC polyomavirus cellular pathways Innovative applications of machine learning in virology High-throughput drug screening methodologies Health disparities research in aging populations

Richard FairView profile

Professor

• Microfluidics
• Electrowetting Technology
• Lab-on-a-Chip Systems
• +7 more

Dr. Richard Fair is the Lord-Chandran Distinguished Professor of Engineering at Duke University, with a career spanning semiconductor physics, digital microfluidics, and lab-on-a-chip systems. His research group collaborates with faculty across Duke, Harvard, and Stanford in bioengineering, genomics, and environmental science to develop applications-driven microfluidic platforms. Ph.D. in Electrical and Computer Engineering, Duke University (1969) B.S.E.E., Duke University (1964) M.S.E.E., Pennsylvania State University (1966) Research interests focus on electrowetting-based microfluidics for biosensing, diagnostics, and synthetic biology applications. Key innovations include adaptive droplet routing , magnetic bead manipulation , and integrated optical sensors for real-time analyte detection in environmental and medical contexts. Recent publications emphasize deep reinforcement learning for biochip automation, fluorescent nucleosome detection , and inorganic ion analysis in aerosols. Collaborations with institutions like Advanced Liquid Logic and NSF-funded projects highlight his interdisciplinary approach. IEEE Third Millennium Medal (2000) Solid State Science and Technology Award (Electrochemical Society, 2003) Gordon E. Moore Medal (2009) Fellow, IEEE and Electrochemical Society Grants include NSF awards with Nan Jokerst and Krish Chakrabarty for adaptive lab-on-a-chip optical control, DARPA funding for genomic engineering platforms, and collaborations with the Desert Research Institute on airborne particle sensing. His lab develops scalable solutions for environmental monitoring, clinical diagnostics, and synthetic biology applications.

• Biomaterials
• Tissue Engineering
• Regenerative Medicine
• +12 more

Professor Hala Zreiqat AM is a leading biomedical engineer at The University of Sydney , serving as the Director of the ARC Training Centre for Innovative BioEngineering . A Fellow of all major Australian academies (AAS, ATSE, FAHMS, FRSN), she develops 3D printed bioceramics for bone regeneration while championing diversity through initiatives like the IDEAL Society and BIOTech Futures mentorship program. Her work bridges academia, clinical practice, and industry in musculoskeletal research . Research Focus: Her lab creates synthetic bone scaffolds that mimic natural bone architecture, strength, and porosity, enabling non-rejected bone regeneration via patient-matched implants. Key applications include orthopaedic, dental, and maxillofacial repair , with over $18M in competitive funding and multiple patents. Current projects explore AI-driven scaffold performance prediction and anti-senescence strategies for aging-related bone loss. Scientific Trends: Recent publications highlight 3D printed nanovoxelated ceramics , antisenescence biomaterials , and multifunctional theranostic platforms . Her team integrates machine learning for scaffold design, atom probe tomography for interface analysis, and two-photon imaging for cellular monitoring in 3D environments. 2021-2022 Fulbright Senior Scholar 2018 NSW Premier's Woman of the Year 2019 Eureka Prize for Innovative Use of Technology Fellow of Australian Academy of Science (2021) Over $18M in research funding Teaching & Leadership: She designed core courses like Tissue Engineering and Nanomaterials in Medicine , mentoring 158 students in 2020 alone. As Chair of CAAR (2020-2023), she strengthens Australia-Arab collaborations. Her lab trains early-career researchers , with alumni now in academia and industry.

Ian StavnessView profile

Professor

• Biomedical Computation & Visualization
• Computer Graphics
• 3D Displays
• +6 more

Dr. Ian Stavness is a Professor and Department Head in the Department of Computer Science at the University of Saskatchewan. His research focuses on interdisciplinary applications of computer science, including deep learning in agriculture, biomedical computation, and 3D display technologies. He leads the Biological Imaging & Graphics (BIGLAB) laboratory, which develops tools for plant phenotyping and musculoskeletal modeling. Education: Ph.D. in Computer Engineering, University of British Columbia, 2010 M.A.Sc. in Computer Engineering, University of British Columbia, 2006 B.Sc. in Computer Science & B.Eng. in Electrical Engineering, University of Saskatchewan, 2004 Research Interests: Deep Learning for Plant Phenomics & Agriculture 3D Displays and VR/AR Technologies Musculoskeletal Biomechanical Simulation (OpenSim, ArtiSynth) Computer Vision and Image Analysis Awards: ACM CHI 2019 Honourable Mention ACM VRST 2018 Polyphony Digital Award Key Projects: Deep Plant Phenomics Platform Parametric Human Project (Digital Human Modeling) P2IRC (Plant Phenotyping & Imaging Research Center)

Klavs F. JensenView profile

Professor

• Materials Science
• Chemical Engineering
• Machine Learning
• +4 more

Professor Klavs F. Jensen is the Warren K. Lewis Professor of Chemical Engineering and Professor of Materials Science and Engineering at MIT. His research focuses on integrating automation, machine learning, and robotics to accelerate materials discovery and pharmaceutical synthesis. He leads the Jensen Research Group, pioneering automated reaction systems with online analytics and optimization algorithms. Education: MS in Chemical Engineering (Technical University of Denmark, 1976); PhD in Chemical Engineering (University of Wisconsin, 1980). Research Interests: Thermochemistry, electrochemistry, photochemistry, Bayesian optimization, high-throughput experimentation, and AI-driven synthesis planning. He collaborates with MIT’s Machine Learning for Pharmaceutical Discovery Consortium to develop algorithms for drug development and process chemistry. Awards: Member of National Academy of Sciences (2017), Member of National Academy of Engineering (2002), Fellow of the American Association for the Advancement of Science (2007), and Fellow of the National Academy of Inventors (2022). Grants & Labs: Editor-in-Chief of Reaction Chemistry and Engineering ; holds 63 US patents and over 490 journal articles. His lab’s innovations include ASKCOS (open-source synthesis planning software) and automated platforms for closed-loop molecular discovery.

Daniel RoxburyView profile

Associate Professor

• Nanoscience
• Carbon Nanotubes
• Nanomaterials
• +4 more

Dr. Daniel Roxbury is an Associate Professor and Graduate Director at the Department of Chemical, Biomolecular and Materials Engineering within the University of Rhode Island's College of Engineering. With expertise in nanoscience and carbon nanomaterials, his research focuses on nano-bio interactions, developing functionalized nanotubes for biomedical applications and environmental monitoring through his NanoBio Engineering Laboratory. His work spans multiple disciplines including: Biomedical nanosensors Smart wearable biomaterials Targeted drug delivery systems Environmental nanotechnology Single-molecule imaging Nanotoxicology Recent publications emphasize machine learning-enhanced spectral analysis, coral reef conservation nanotechnology, and wearable stress monitoring textiles. His 2024 ACS Nano study introduces AI-driven macrophage phenotyping, while 2023 Nature Nanotechnology work explores coral reef restoration strategies using nanomaterials. Awarded the 2019 NSF CAREER grant for cellular nanometrology, he leads multiple NIH-funded projects including: $820,000 NSF CAREER: Spectral Imaging for Sub-Cellular Nanometrology $140,000 Miriam Hospital COBRE: Cortisol Detection Textiles $700,000 NSF EAGER: Multiplexed Wound Biomarker Detection His laboratory houses state-of-the-art equipment including: Near Infrared Hyperspectral Microscope Custom NIR Fluorescence Spectrometer Jasco UV/VIS/NIR Spectrophotometer Biosafety Cabinet Cell Culture Incubator Cryo-Storage System

Matthew LakinView profile

Associate Professor

• Molecular Computing
• DNA Nanotechnology
• Synthetic Biology
• +7 more

Matthew Lakin is an Associate Professor with tenure in the Department of Computer Science at the University of New Mexico, with a courtesy appointment in the Department of Chemical & Biological Engineering. He is affiliated with the UNM Center for Biomedical Engineering and the School of Engineering, and collaborates extensively with the UNM Health Sciences Center and external institutions. Education: Ph.D., Computer Science, University of Cambridge, 2010 M.A. (Cantab), University of Cambridge, 2009 B.A. (Hons), Computer Science, University of Cambridge, 2005 Dr. Lakin's research focuses on molecular computing, DNA nanotechnology, synthetic biology, and formal verification of biomolecular circuits. He develops computational models and experimental systems for programmable biological devices, especially using heterochiral DNA to enhance stability in living cells. His work spans software tools for biodesign and experimental validation in mammalian systems, with applications in nanomedicine and biosensing. The recent publications highlight a strong trend in engineering robust, intelligent biomolecular systems. His work integrates machine learning concepts into chemical reaction networks, advances geometric modeling of DNA systems, and pioneers L-DNA-based circuits for intracellular applications. The research spans theoretical foundations, software tools, and wet-lab experimentation, emphasizing interdisciplinary innovation. Scientific Awards: Presidential Early Career Award for Scientists and Engineers (PECASE), 2025 NSF CAREER Award, 2021 UNM School of Engineering Junior Faculty Research Excellence Award, 2021 Multiple student awards under his mentorship, including the Outstanding Graduate Student Award and DNA28 Best Student Presentation recognition Dr. Lakin has advised numerous graduate and undergraduate students, including Ph.D. graduates in Biomedical Engineering and Computer Science. He leads major funded projects such as the NSF CAREER grant on heterochiral molecular computing, an EPSCoR Research Fellowship, and a $3M NSF grant on heavy metal biosensing in collaboration with Native American communities. He is also PI on multiple NSF grants related to synthetic cells and nucleic acid technologies. He directs the Lakin Lab for Programmable Biology, which operates within the Department of Computer Science and collaborates with Chemical & Biological Engineering and the Center for Biomedical Engineering. The lab emphasizes both computational modeling and experimental molecular biology, and runs an NSF-funded biotechnology summer camp in partnership with ¡Explora! science museum to strengthen STEM education in New Mexico.

Brian HieView profile

Assistant Professor

• Machine Learning
• Computational Biology
• Protein Engineering
• +6 more

Brian Hie is an Assistant Professor of Chemical Engineering at Stanford University , a Dieter Schwarz Foundation Stanford Data Science Faculty Fellow , and an Innovation Investigator at Arc Institute . He leads the Laboratory of Evolutionary Design , focusing on the intersection of biology and machine learning . His prior roles include a Stanford Science Fellow in the Stanford University School of Medicine and a Visiting Researcher at Meta AI . Education: Ph.D. , Electrical Engineering and Computer Science , Massachusetts Institute of Technology (2021) Bachelor’s Degree , Stanford University Research Interests: Brian’s work bridges machine learning and computational biology , with a focus on protein engineering , single-cell RNA sequencing , and viral evolution . His Evolutionary velocity framework predicts protein evolutionary dynamics across timescales, while his Scanorama algorithm enables efficient integration of heterogeneous single-cell datasets. He also develops structure-informed language models for antibody optimization and uncertainty-aware ML for biological discovery. Publication Trends: His recent work (2023) emphasizes structure-based inverse folding for antibody evolution, evolutionary scale modeling , and unsupervised optimization . Earlier studies (2022-2021) cover evolutionary velocity , multi-modal single-cell analysis , and viral escape prediction using natural language analogies. Scientific Awards: Stanford Science Fellow (2021) National Defense Science and Engineering Graduate Fellowship (2019) Advising: He mentors doctoral students including Brandon Ameglio , Garyk Brixi , and Chang M. Yun , with a focus on biological design and computational methods . Labs & Collaborations: His lab collaborates with Bio-X and the Institute for Human-Centered Artificial Intelligence (HAI) , and he maintains affiliations with Sarafan ChEM-H and Stanford Data Science .

Michael BaymView profile

Associate Professor

• Microbial Evolutionary Genomics
• Antibiotic Resistance
• Computational Biology
• +7 more

Dr. Michael Baym is an Associate Professor of Biomedical Informatics at Harvard Medical School with affiliate appointments in Microbiology and the Laboratory of Systems Pharmacology, and as an Associate Member of the Broad Institute. He leads the Baym Lab, which studies microbial evolutionary genomics and antibiotic resistance through a hybrid of experimental, computational, and theoretical approaches. His research focuses on: Antibiotic Resistance Evolution and practical interventions Mobile Genetic Elements (plasmids, phages, transposons) Computational Genomic Algorithms for big data analysis Synthetic Biology tools and technologies Key recent publications explore phage discovery systems , phylogenetic compression of microbial genomes, and RNA-guided gene drives in plasmids. His work is supported by multiple NIH/NIGMS and NSF grants including a MIRA award. Scientific honors include: Packard Fellowship (2018) Pew Biomedical Scholarship (2020) Sloan Research Fellowship (2020) A. Clifford Barger Excellence in Mentoring Award (2021) SSQBio Mentorship Award (2022) The lab actively trains PhD students and postdoctoral fellows with alumni occupying academic and industry positions globally. Current team members include researchers from interdisciplinary backgrounds working at the intersection of experiment, computation, and theory .