News

Mohammad Tariqul Islam’s research is focused on employing AI to develop next-generation biomedical applications, including nanotechnologies. Specifically, Tariq specializes in unsupervised machine learning, a field that looks for patterns in unlabeled data. In his doctoral research, he developed a new approach for analyzing chest X-rays that successfully distinguishes Covid-19 patients from healthy patients and differentiates between two distinct types of Covid response. Additionally, he developed unsupervised methods for curating large radiological datasets. As an MIT-Novo Nordisk Artificial Intelligence Postdoctoral Fellow, he aims to create innovative algorithms specifically tailored for nano-electronic and bio-hybrid systems. To accomplish this, he will develop algorithms to identify related groups within data, with a particular focus on neighbor relations and topology-preserving approaches. Tariq’s work holds exciting potential to bridge the field of AI with next-generation nanodevices and improve diagnosis, treatment, and understanding of human disease.

Johannes Lachner’s research focuses on applying motor neuroscience and robot control to aid individuals with neurological and physical disorders. More specifically, he is developing personalized robot-aided rehabilitation systems that could improve the therapy provided to stroke survivors and relieve caregivers from physically demanding work. In his doctoral research, he applied differential geometric methods to achieve stable, safe, and efficient control of robots interacting with people and the environment. As an MIT-Novo Nordisk Artificial Intelligence Postdoctoral Fellow, Johannes will develop the mechanical, electrical, and software-based subsystems necessary to apply his theoretical research to practical robot-based stroke rehabilitation. By incorporating human therapists’ actions into robot-aided treatment, his work could expand access to care and promote superior outcomes. Additionally, he aims to deploy advanced mathematical tools to interpret data that is observed, for example, the geometry of movements by unimpaired people and movements by stroke survivors that could quantify impairment. Johannes’s work has the potential to advance the field of robot-aided rehabilitation and revolutionize therapy, offering tailored and efficient treatments while prioritizing patient comfort, building trust, and reducing the physical toll on healthcare professionals.

Herui Liao’s main research direction is developing sophisticated computational algorithms to achieve high-resolution composition analysis in metagenomic data. During his PhD studies, he developed and published three tools to address computational challenges in microbial studies: one identifies viral strains from next-generation sequencing data; a second provides high-resolution bacterial strain-level composition analysis for next-generation sequencing data; and a third classifies host disease status and identifies disease-related microbial biomarkers based on human gut microbiome data. As an MIT-Novo Nordisk Artificial Intelligence Postdoctoral Fellow, he will apply machine learning to update high-resolution microbial genomics pipelines and make them more tractable for a wide audience. One of these pipelines aims to construct highly accurate phylogenetic trees between closely related bacterial isolates, which is a task highly sensitive to false positive and false negative mutation calling. By applying machine learning to identify dataset-specific thresholds that distinguish real and fake maturations, Herui’s work has the potential to increase automation of this pipeline, making it accessible to less experienced users, such as microbiologists with minimal coding experience, microbiome researchers using this novel data type, as well as epidemiologists detecting outbreaks in hospital settings.

Babak Mahjour is an MIT-Novo Nordisk Artificial Intelligence Postdoctoral Fellow whose research interests lie in uniting chemical synthesis, data science, and engineering to drive translational studies. As part of his doctoral studies, Babak developed phactor, a software that facilitates the performance and analysis of high throughput experiments in a chemical laboratory. This tool enables users to access online reagent data and to procedurally generate multiplexed reaction array protocols that can be downloaded as human-readable instructions or as robotic executables. As a postdoctoral fellow, Babak seeks to develop protocols that accelerate the synthesis and evaluation of potential small molecule therapeutics. This will be achieved by linking synthetic campaigns with biological assays within a framework centered around a robotic infrastructure. Central to this work will be the development of robust, high-throughput, and assay-amenable high-value methodologies as well as the invention of novel reactivities. His work holds tremendous promise to advance the development of impactful treatments for various diseases and to promote sustainable chemistry practices in drug discovery.

Adi Millman’s research is focused on the interactions between bacteria and the viruses that infect them called bacteriophages (phages). Specifically, Adi seeks to illuminate how phages shape the gut microbiome and expose their contribution to bacterial adaptation to different conditions in the gut. In her doctoral research, Adi identified novel bacterial anti-phage defense systems and discovered a role for bacterial retrons, a breakthrough in microbiology. As an MIT-Novo Nordisk Artificial Intelligence Postdoctoral Fellow, her goal is to elucidate how phages influence the bacterial composition of the gut by using large longitudinal microbiome data. This work will employ a variety of tools, including AI and differential network analysis, to understand how phages influence the microbiome’s trajectory and to develop predictive models. Her research holds the potential to unearth pivotal insights into the ecological and evolutionary forces at play within the gut microbiome while aiding in the differentiation of microbiome dynamics in health and disease. As of September 2024, Adi departed the program but will remain at MIT through an external three-year fellowship.