Osbert Bastani is an Associate Professor at the Department of Computer and Information Science, University of Pennsylvania, leading the trustml@Penn research group. He is affiliated with the ASSET , PRECISE , and PRiML centers, and the PLClub research group. His research focuses on Trustworthy Neurosymbolic Systems , Synthesizing Neurosymbolic Programs , and Machine Learning for Programmer Productivity , with applications in verification, fairness, and human-AI collaboration. He received the NSF CAREER Award in 2023. His recent publications (2024-2025) emphasize AI Safety , LLM Robustness , and Algorithmic Fairness , including work on adversarial robustness, conformal prediction, and program synthesis. Students he has advised include Sagnik Anupam, Stephen Mell, Jason Ma, Shuo Li, and others. Awards: NSF CAREER Award (2023)
Dr. Camila Aquino serves as Assistant Professor in both the Department of Clinical Neurosciences and Department of Community Health Sciences at the University of Calgary's Cumming School of Medicine, and is a Full Member of the Hotchkiss Brain Institute. As Medical Director of the Deep Brain Stimulation Program, she specializes in Parkinson's disease, essential tremor, dystonia, and chorea management, including EMG-guided botulinum toxin injections. Her educational background includes: M.D. in Medicine from Escola Superior de Ciencias da Santa Casa (2005) M.S. in Neurosciences from Federal University of Sao Paulo (2012) Ph.D. in Neurosciences from Federal University of Sao Paulo (2019) M.S. in Health Research Methods, Clinical Epidemiology from McMaster University (2020) Dr. Aquino's research addresses unmet needs in movement disorders through innovative clinical trial designs for Parkinson's disease, focusing on precision-medicine approaches, early intervention, and outcome optimization. She actively evaluates neuromodulation therapies including Deep Brain Stimulation, Spinal Cord Stimulation, and MRgFUS, with emphasis on expanding indications and improving patient outcomes. As an International Parkinson and Movement Disorder Society member, she chairs the web-based learning committee and serves on evidence-based medicine and outcome measure committees. Analysis of her 15 most recent publications (2021-2025) reveals a cohesive research trajectory centered on Parkinson's disease management, with dominant themes in motor fluctuation treatments, deep brain stimulation methodology, and clinical trial innovation. Her work bridges fundamental clinical practice guidelines with advanced neuromodulation technologies, demonstrating consistent commitment to evidence-based solutions for movement disorders. Her scientific recognition includes: Parkinson Canada research grant Mohammed Al Zaibak Foundation scholarship CAPES scholarship from Brazilian Ministry of Education Dr. Aquino has secured significant research funding supporting clinical trials in Parkinson's disease neuroprotection and neuromodulation therapies. While specific student advisees aren't listed, her leadership of the DBS Program and active clinical trial portfolio indicate substantial mentorship responsibilities. Her grant portfolio emphasizes translational research with direct clinical impact. She directs the University of Calgary's Deep Brain Stimulation Program and contributes to the MRI-guided focused ultrasound initiative. Through her International Parkinson and Movement Disorder Society committee roles, she shapes global educational standards and evidence-based practices in movement disorders.
Professor Maria Craig is a distinguished academic and researcher at the University of New South Wales, Faculty of Medicine & Health, specializing in childhood diabetes research. She holds a prominent position as a Professor with extensive contributions to the field of pediatric endocrinology and diabetes, particularly focusing on type 1 diabetes in children. Professor Craig's educational background includes: MB BS from the University of Melbourne MMedSc(ClinEpid) from the University of Newcastle PhD from the University of Sydney FRACP (Fellow of the Royal Australasian College of Physicians) Professor Craig's research primarily focuses on childhood diabetes, with special emphasis on prediction and prevention of type 1 diabetes. She has a significant interest in the association between viruses and type 1 diabetes, collaborating with the Virology Research Group at Prince of Wales Hospital (POWH). Together with Professor Bill Rawlinson, she leads the viral theme for the multicentre ENDIA study (endia.org.au). As principal investigator for the CoRD trial, she is conducting a world-first phase 1 study using autologous cord blood for prevention of type 1 diabetes in children with islet autoimmunity. Additionally, she serves as principal investigator for the Australasian Diabetes Data Network (ADDN). Her research portfolio also encompasses the epidemiology of various forms of childhood diabetes (type 1, type 2, cystic fibrosis related diabetes and monogenic diabetes) and diabetes complications, in collaboration with Professor Kim Donaghue at the Children's Hospital at Westmead. Professor Craig's extensive publication record, including over 361 journal articles, demonstrates her leadership in advancing our understanding of childhood diabetes. Her recent work shows increasing focus on early detection methods, risk prediction models, technological interventions for diabetes management, and the complex interplay between viral infections and autoimmune diabetes development. She has been instrumental in developing clinical practice guidelines through her role as co-editor of the International Society for Pediatric and Adolescent Diabetes (ISPAD) guidelines. Professor Craig has received numerous prestigious awards recognizing her contributions to pediatric endocrinology and diabetes research: Australian Paediatric Endocrine Group Young Investigator's Award (1997) Asia Pacific Paediatric Endocrine Society Clinical Teaching Award (2008) Lifetime Honorary Member, Caring and Living as Neighbours (2013) Australian Diabetes Society Jeff Flack Diabetes Data Award (2019) Australian Paediatric Endocrine Group Norman Wettenhall Award for Research and Innovation (2019) Throughout her career, Professor Craig has demonstrated exceptional leadership in professional societies, having served as former president/treasurer of the Australasian Paediatric Endocrine Group (APEG) and currently as Scientific Convenor of the Asia Pacific Paediatric Endocrine Society Fellows school. Her work with the ENDIA study and Australasian Diabetes Data Network represents significant collaborative research efforts involving multiple institutions across Australia and internationally. Her principal investigator roles for major studies indicate substantial research funding support. Professor Craig leads several important research initiatives including the ENDIA study, the CoRD trial, and the Australasian Diabetes Data Network. These programs involve multidisciplinary teams of researchers, clinicians, and support staff working collaboratively to advance understanding and treatment of childhood diabetes. Her work at the intersection of virology and diabetes represents a unique and innovative approach to understanding the environmental triggers of type 1 diabetes.
Joseph Kable is the Jean-Marie Kneeley President's Distinguished Professor of Psychology at the University of Pennsylvania's Department of Psychology within the School of Arts and Sciences. His research integrates experimental economics, cognitive neuroscience, and personality psychology to investigate the neural and psychological mechanisms underlying decision-making. He explores how subjective value is represented in the brain, deviations from rational choice theory, and individual differences in decision processes. His lab employs fMRI and interdisciplinary methods to study topics like risk tolerance, impulsivity, and neural plasticity. Education: BS in Chemistry from Emory University (undergraduate), PhD in Neuroscience from the University of Pennsylvania (doctoral). Research focuses on behavioral and cognitive neuroscience mechanisms of choice, including studies on temporal predictions, value signals, and brain structure-function relationships. His recent work examines how neural markers correlate with decision-making variability across individuals. He currently advises graduate students in Psychology and has post-doctoral researchers in his lab. Associated with MindCORE, Penn's hub for integrative mind research. Lab activities include undergraduate research programs and active studies exploring decision neuroscience and neuroeconomics.
Professor Chris Holmes is a Professor of Biostatistics at the University of Oxford, where he moved from Imperial College London in February 2004. He is a Fellow at St Anne's College and works in the Department of Statistics. His research focuses on applications and statistical methods development in genomic sciences and genetic epidemiology, holding a prestigious Programme Leaders Grant in Statistical Genomics from the Medical Research Council. Prior to his position at Oxford, Professor Holmes completed his doctorate in Bayesian statistics at Imperial College London, investigating novel nonlinear pattern recognition methods. This was followed by a post-doctoral position and then a lectureship at Imperial. Before his academic career, he worked in industry for several years in scientific computing, developing techniques for real-time pattern recognition models in defense and SCADA systems. Professor Holmes has a broad interest in the theory, methods and applications of statistics and statistical modeling, with a particular foundation in Bayesian statistics which he views as providing a unified framework for stochastic modeling and information processing. His specific research interests include: Bayesian statistics and stochastic simulation Markov chain Monte Carlo methods Pattern recognition and nonlinear, nonparametric methods Spatial statistics Statistical genetics and genomics Genetic epidemiology His recent publications (2023-2025) demonstrate a strong focus on the intersection of biostatistics, artificial intelligence, and healthcare applications. His work spans multiple domains including AI-driven disease classification in neurology, genomic data analysis for health equity, machine learning tools for healthcare prediction, and addressing bias in medical AI systems. A notable trend across his research is the application of advanced statistical methods to solve pressing problems in genomics, epidemiology, and medical diagnostics, with an increasing emphasis on health equity and the ethical implications of AI in healthcare. Professor Holmes currently supervises PhD students Oscar Clivio, Sahra Ghalebikesabi, and Natalia Garcia Martin. His research is supported by multiple grants, including the MRC Programme Leaders Grant in Statistical Genomics which funds his work in statistical genomics. He is actively involved in three research groups at Oxford that reflect the breadth of his scholarly interests: Computational Statistics and Machine Learning Statistical Genetics and Epidemiology Statistical Theory and Methodology
Federica Tomao is an Associate Professor at the Department of Maternal, Child and Urological Sciences within Sapienza University of Rome. She actively teaches and supervises courses in Medicine and Surgery , Nursing , and Midwifery programs across multiple institutions. Current faculty member with academic rank Teaching roles in 6th, 3rd, and 2nd year courses Specialized in gynecologic oncology Research Focus : Her work spans ovarian cancer, breast cancer, and endometrial cancer, emphasizing chemotherapy optimization, precision medicine, and radiomics. Notably, she contributes to understanding PARP inhibitors, immune checkpoint therapies, and fertility preservation techniques in cancer survivors. Recent Publications highlight advancements in sarcopenia analysis, BRCA testing, and radiogenomic nomograms. These studies demonstrate her commitment to bridging imaging and molecular data for improved cancer management. Email : federica.tomao@uniroma1.it
Alexis Battle is an Associate Professor at Johns Hopkins University with appointments in Biomedical Engineering , Computer Science , and Genetic Medicine (secondary). She directs the Malone Center for Engineering in Healthcare and serves as Deputy Director of the Data Science and AI Institute . Educated at Stanford University (PhD in Computer Science, 2013), Battle transitioned to academia after leadership roles at Google. Research Focus: Battle’s work bridges genomics and machine learning , emphasizing the impact of genetic variation on human health. Her lab develops tools like Watershed to predict functional effects of rare variants, aiming to enhance rare disease diagnosis. Key themes include non-coding DNA analysis , personalized genomics , and systems biology , with applications in cardiovascular disease and neurodegenerative disorders . Publications & Awards: Over 60 peer-reviewed articles in journals like Nature , Science , and Genome Biology , with recent emphasis on single-cell transcriptomics , multiomics integration , and telomere biology . Recipient of the President’s Frontier Award (2022), Microsoft Investigator Fellowship (2019), and Searle Scholar (2016). Scientific Awards: 2022 President’s Frontier Award 2019 Microsoft Investigator Fellowship 2019 Johns Hopkins Discovery Award 2017 Johns Hopkins Catalyst Award 2016 Searle Scholar Advising & Funding: Mentors 11 PhD students, 3 undergraduates, and postdoctoral fellows. Her research is funded by NIH, Searle Scholars, and institutional grants. The Battle Lab collaborates on projects like the GTEx Consortium , focusing on gene regulation and clinical genomics .
Martin T. Wells is the Charles A. Alexander Professor of Statistical Sciences at Cornell University, with joint appointments in the Department of Statistical Science, Department of Biological Statistics and Computational Biology, Department of Social Statistics, and as Professor of Clinical Epidemiology and Health Services Research at Weill Medical School. He serves as Editor-in-Chief of the ASA-SIAM Book Series and Co-Editor of the Journal of Empirical Legal Studies. Cornell University, Ithaca, NY Weill Cornell Medical College Research Interests span applied and theoretical statistics, Bayesian methods, biostatistics, clinical epidemiology, and computational biology. His work bridges disciplines like finance, legal studies, and health services research. Article Trends highlight advancements in Bayesian modeling, quantum cognition machine learning, tensor analysis, and misclassification correction, with applications in genomics, finance, and public health. Fellow of the American Statistical Association Fellow of the Royal Statistical Society Contributions include developing statistical software (e.g., rTensor), methodological innovations in clinical trials, and empirical legal studies on civil rights and the death penalty.
Steven I-Jy Chien serves as Professor and Director of the Transportation Program within the Department of Civil and Environmental Engineering at the New Jersey Institute of Technology (NJIT). His career spans academia, government, and industry with significant contributions to transportation engineering research and practice. His educational credentials include: Ph.D. in Civil and Environmental Engineering from University of Maryland-College Park (1995) M.S. in Civil and Environmental Engineering from University of Maryland-College Park (1991) B.S. in Civil Engineering from Tamkang University (1983) Professor Chien's research focuses on transportation system resilience, sustainable transit operations, and advanced traffic modeling. His work addresses critical challenges in urban rail networks, demand-responsive transit services, and energy-efficient transportation systems. He employs sophisticated computational methods including genetic algorithms, machine learning, and Bayesian approaches to solve complex transportation problems involving network vulnerability, passenger behavior, and infrastructure optimization under uncertainty. Analysis of his recent publications reveals strong emphasis on transportation resilience against cascading failures, sustainable operations for electric transit systems, and pandemic-responsive aviation scheduling. His research spans diverse geographic contexts including major Chinese metropolitan areas and U.S. transportation networks, demonstrating global applicability of his methodologies. His professional recognition includes: 2024 Keynote Speaker at Union-Tech Lecture, National Taiwan Ocean University 2022 Keynote Speaker at International Conference of Chinese Institute of Transportation 2022 Best Poster Award from New Jersey Department of Transportation Professor Chien has secured research funding from federal agencies including the Federal Highway Administration (FHWA) where he contributed to CORSIM traffic simulation software development. His industry experience with China Engineering Consultants Inc. and Information Dynamic Inc. informs his practical approach to transportation challenges. As Transportation Program Director, he oversees curriculum development and industry partnerships that prepare students for transportation sector careers. He maintains active collaboration with transportation agencies globally, particularly through his leadership in the Transportation Program at NJIT which serves as a hub for innovation in urban mobility solutions.
Dr. Samira Lakhal-Littleton is an Associate Professor of Cell Physiology and MRC Senior Non-Clinical Research Fellow at the University of Oxford, affiliated with the Department of Physiology, Anatomy and Genetics and Brasenose College. Her research focuses on iron homeostasis, systems biology, and oxygen sensing mechanisms in cardiovascular and systemic physiology. Education: BSc in Human Genetics (University College London), DPhil in Molecular Medicine (University of Oxford) Her work bridges cell physiology and translational medicine, with key discoveries on hypoxia-inducible factors (HIFs), iron regulatory genes TMPRSS6 and GDF15 , and the role of hepcidin in altitude adaptation and chronic diseases. She utilizes tissue-specific animal models to study iron regulation in heart, kidney, placenta, and vasculature. Recent publications highlight her contributions to understanding: FLASH radiotherapy effects linked to iron-dependent lipid peroxidation Clinical implications of myocardial iron dynamics in heart failure Hepcidin's role in vascular protection and placental iron transfer Biomarker development for predictive iron deficiency diagnostics Scientific Leadership: British Heart Foundation Intermediate Fellowship (2012) MRC Senior Fellowship (2020) BioIron Society Board Member (2019) She collaborates with clinical teams on translational projects and serves as a Tutorial Fellow in Medicine at Brasenose College, mentoring students in physiological sciences.
Bernhard J. Berger is a Lecturer in the Department of Computer Engineering at the Institute of Embedded Systems, Hamburg University of Technology (TUHH). His research focuses on software security, static code analysis, machine learning, optimization, and research data management. He has held significant roles such as Program Committee member for ICPC 2025 and MSR 2025, and has received awards including the Best Reviewer Award (ICPC 2023) and Best Engineering Paper Award (SCAM 2019). His work spans interdisciplinary applications including maritime systems security, GPU-accelerated AI, and evolutionary algorithms. Recent studies emphasize AI-driven security tools (e.g., ML-SAST) and domain-specific language approaches to optimization (EvoAl). He has contributed to over 30 peer-reviewed publications, with notable work in IEEE Transactions on Software Engineering and Science of Computer Programming. Berger collaborates closely with industry through DAAD review committees and serves on artifact evaluation boards for ISSTA and ARES conferences. Education: Doctoral Thesis (2022), Diploma in Computer Science (2007) Key Projects: ArchSec tool suite, Threat Modeling Frameworks, Bauhaus static analysis methodology Lab Affiliation: Embedded Systems Design Group His advisory roles include Deputy of TUHH's Election Verification Committee and Session Chair at IEEE Congress on Evolutionary Computation 2023. Current research trends integrate machine learning with static analysis for automated vulnerability detection, while also exploring explainable AI techniques for neural network optimization.
Daniel Adelman is the Charles I. Clough, Jr. Professor of Operations Management at the University of Chicago Booth School of Business. He joined the faculty in 1997 after completing his PhD in industrial engineering and operations research at Georgia Tech. Adelman is a leading expert in Business Analytics and Management Analytics, helping companies deploy data and decision analysis to build world-class strategic and tactical management capabilities. Adelman received his PhD in industrial engineering and operations research in 1997, along with a bachelor's degree in industrial engineering and a master's degree in operations research, all from the School of Industrial and Systems Engineering at the Georgia Institute of Technology. Daniel Adelman's research focuses on applying analytical models to solve complex business problems across multiple industries. He has worked with firms from diverse sectors including internet services, chemical distribution, airlines, third party logistics, fiber-optics manufacturing, semiconductor manufacturing, oil, and healthcare. His research integrates real-world data with analytical models to bring structure and discipline to decision and control processes, enabling firms to achieve higher profits with lower risk. Adelman's recent work has concentrated heavily on healthcare analytics, where he leads the Healthcare Analytics Laboratory at Chicago Booth. This lab works with teams of doctoral and MBA students on projects with major healthcare institutions to optimize clinical, operational, and financial outcomes. His research spans foundational operations research including approximate dynamic programming, inventory theory/supply chain management, and revenue management/pricing optimization, as well as examining the linkage between operational performance metrics and financial performance of firms. Adelman's publications show a clear trend toward increasing focus on healthcare applications while maintaining strong theoretical foundations in operations research. His earlier work focused more on general operations management problems like inventory control and supply chain optimization, while his recent publications demonstrate a strategic shift toward healthcare analytics, particularly examining surgical team dynamics, hospital performance metrics, and resource allocation during public health emergencies like the COVID-19 pandemic. George B. Dantzig Prize (1998) for the best dissertation in operations research and management sciences that is innovative and relevant to practice Adelman regularly advises doctoral and MBA students through the Healthcare Analytics Laboratory at Chicago Booth. He has served as Associate Editor for Management Science, currently serves as Associate Editor for Manufacturing and Service Operations Management, and is the Area Editor for Operations and Supply Chain at Operations Research. His industry collaborations include significant projects with Akamai on internet pricing, with GE Global Research Labs on the electricity smart grid, with BP on gasoline supply contract portfolio optimization, and with Symantec on software release planning. Adelman leads the Healthcare Analytics Laboratory at Chicago Booth, which brings together interdisciplinary teams of doctoral and MBA students to work on a portfolio of projects with major healthcare institutions. The lab focuses on optimizing clinical, operational, and financial outcomes through advanced analytics and decision modeling.
Itsik Pe'er is a Full Professor and Vice-Chair in the Department of Computer Science at Columbia University's Fu Foundation School of Engineering & Applied Science, and holds a joint appointment as Professor of Systems Biology at the Vagelos College of Physicians and Surgeons. His research focuses on computational methods in human genetics, including genetic variation analysis, disease association studies, and algorithm development for genomic data. He leads the Itsik Pe'er Lab of Computational Genomics, which develops tools like Xplorigin, Germline, and SEACells to address challenges in genomics and medical research. His work spans machine learning applications in healthcare, microbiome analysis, and cancer genomics. Notable contributions include studies on hypertensive disorders in pregnancy, bias correction in predictive models, and the development of non-Euclidean learning libraries like Manify. Pe'er has advised students including Vladimir Vacic, Anat Kreimer, and Arthi Ramachandran, and collaborates on grants addressing genetic epidemiology and computational biology. His lab's location is in the Computer Science Building at Columbia's Morningside Campus.
Calliope Dendrou is an Associate Professor in Clinical Pathology and Inflammation at the Kennedy Institute of Rheumatology (KIR), University of Oxford, leading the Immune Disease Multiomics Laboratory. She previously held a Wellcome & Royal Society Sir Henry Dale Fellowship at the University of Oxford’s Centre for Human Genetics before joining KIR in 2023. Her research focuses on immune disease mechanisms using multiomics approaches, including genomic profiling to identify therapeutic targets across tissues and immune-mediated diseases. She co-leads large-scale projects like the Oxford-J&J Cartography Consortium and the Chan Zuckerberg Initiative’s LEGACY Network, and teaches on the MSc in Genomic Medicine program. Educational Background: BSc (Biology, Imperial College London, 2005; Forbes Memorial Medal Winner); PhD in Infection & Immunity (University of Cambridge, 2010). Postdoctoral training at the Weatherall Institute of Molecular Medicine under Prof. Lars Fugger. Research interests include immunogenetics, cytokine signaling pathways, drug repositioning, and cross-disease pathophysiology. Her work integrates single-cell and spatial transcriptomics to dissect immune-cell interactions in diseases like rheumatoid arthritis, inflammatory bowel disease, and celiac disease. Recent articles highlight her contributions to understanding vaccine adjuvant responses, Th17 cell roles in spondyloarthritis, and immune-epithelial networks in celiac disease. Collaborations emphasize multi-omic data analysis (e.g., Panpipes pipeline) and translational studies toward precision medicine. Awards: Forbes Memorial Medal (BSc), Wellcome & Royal Society Sir Henry Dale Fellowship. Leadership roles include Equality, Diversity, and Inclusion Champion and 'Single-Cell & Spatial Omics for Precision Medicine' Module Lead. Lab & Teams: Immune Disease Multiomics Lab at KIR. Active in collaborative initiatives such as the LEGACY Network, focusing on large-scale immune profiling in ancestrally diverse populations.
John P. O'Doherty serves as the Fletcher Jones Professor of Decision Neuroscience within Caltech's Division of Humanities and Social Sciences, holding continuous faculty appointments since 2004 (Assistant Professor 2004-07, Associate Professor 2007-09, Professor 2009-present, Fletcher Jones Professor 2021-present). He previously directed the Caltech Brain Imaging Center (2013-17) and maintains affiliations with the T&C Chen Center for Social and Decision Neuroscience. His educational background includes a B.A. from University of Dublin, Trinity College (1996) and D.Phil. from University of Oxford (2000). His research focuses on computational and neural mechanisms of reward-based learning and decision-making , employing fMRI, intracranial recordings, and mathematical modeling to investigate how the brain solves complex decision problems through evolutionarily conserved algorithms. Key areas include Reinforcement learning systems (model-based/model-free arbitration) Observational and social learning mechanisms Neural representation of value, risk, and uncertainty Computational phenotyping of mental disorders Temporal dynamics of goal persistence Analysis of his 2023-2025 publications reveals dominant trends in computational psychiatry (problem gambling, autism traits), hierarchical decision-making, and neuroeconomic modeling of social behavior. His work consistently integrates cross-species computational frameworks with human neuroimaging to identify transdiagnostic mechanisms. While specific awards beyond his endowed professorship aren't detailed, his leadership as Brain Imaging Center Director and prolific high-impact publications demonstrate significant recognition. Current advising includes graduate researcher Sneha Aenugu on goal-persistence projects, with administrative support from Mary A. Martin (mmartin@caltech.edu). His active research program continues to pioneer computational approaches to understanding decision pathologies.
