Dr. Abdullah Bal is a researcher at Georgia State University's College of Arts & Sciences, Department of Computer Science, with over 25 years of academic experience. He holds a Ph.D. in Electrical Engineering from Yildiz Technical University (2002) and has taught graduate and undergraduate courses in algorithms, machine learning, and optical pattern recognition. B.Sc., Electronics and Communication Engineering, Istanbul Technical University (1993) M.Sc., Electrical Engineering, Yildiz Technical University (1997) Ph.D., Electrical Engineering, Yildiz Technical University (2002) His research focuses on data science, machine learning, and hyperspectral imaging applications in fields ranging from forensic analysis to historical structure preservation. He has led projects funded by the U.S. Army Research Office and the Scientific and Technological Research Council of Turkey, including real-time target detection systems and digital imaging for historical structures. Recent publications demonstrate his expertise in kernel-based transforms, ensemble learning, and hyperspectral data analysis. His work spans food safety inspection, infrared target tracking, and biometric verification systems. Faculty Outstanding Research Publication Award (2006) Turkish Air Force Academy Science Competition Winner (2009) Best Paper Award at ICFCT (2016) Previously, he chaired YTU's Informatics Department (2009-2016) and participated in academic governance through the Electrical and Electronics College Executive Committee (2012-2015). You can contact him at abal@gsu.edu in room 739, 25 Park Place.
Dr. V.M. (Bala) Balasubramaniam is a Professor in the Department of Food Science and Technology at The Ohio State University. He holds editorial roles in food engineering journals and is a Fellow of IFT and IUFoST. His research focuses on clean food manufacturing technologies, particularly high-pressure and nonthermal methods, emphasizing microbial inactivation and nutrient preservation. He teaches unit operations in food engineering and contributes to industry via short courses and pilot plant demonstrations. Education: B.S. (Tamil Nadu Agricultural University), M.S. (Asian Institute of Technology), Ph.D. (Ohio State University). Research Interests: Thermal/nonthermal processing, food safety/quality modeling, and innovative applications of high-pressure technologies. Recent work includes ultra-shear technology development and superheated steam sanitation. Over 100 scientific papers, 20 book chapters, and co-edited books on high-pressure processing. Awards include the 2021 IFT Research & Development Award and 2017 Calvert L. Willey Award. Advising: Supervises graduate students like Liz Astorga Oquendo and Shruthy Seshadrinathan. Industrial outreach includes a USDA consortium for ultra-shear commercialization. Labs/teams focus on pilot-scale equipment testing and microbial efficacy studies.
Professor Ruchi Choudhary is a Professor in Architectural Engineering at the University of Cambridge, Department of Engineering, within the School of Technology. She leads the Energy Efficient Cities initiative (EECi), a cross-disciplinary research project focused on strengthening the UK's capacity to address energy demand reduction and environmental impact in cities through research in building and transport technologies, district power systems, and urban planning. Her research interests span urban energy systems, building energy modeling, sustainable cities, geothermal energy systems, and data-driven energy modeling . She has pioneered work in digital twins for energy systems, urban subsurface thermal modeling, and building-integrated agriculture. Her research group develops numerical tools to improve energy efficiency of cities, with particular focus on modeling energy consumption of large building sets at multiple time and spatial resolutions. Analysis of her recent publications reveals a strong trend toward integrating machine learning with physics-based modeling for energy systems, with increasing emphasis on uncertainty quantification, digital twins, and value of information analysis for decision-making. Her work bridges the gap between theoretical modeling and practical urban implementation, with significant focus on city-scale geothermal potential, underground climate change impacts, and energy equity considerations. Professor Choudhary has supervised numerous PhD students who have gone on to prominent positions at institutions including UCL, University of Cambridge, BEIS, Arup, and various international universities. Her research group includes faculty members, research associates, graduate students, and international collaborators from institutions worldwide. Her current research focuses on two parallel investigations: one on using multi-scale multidisciplinary models to address energy use questions in the built environment, and second, on quantifying uncertainties in model outcomes. Current projects include integration of food production in urban environments, analysis of underground transport systems as energy sources, large-scale integration of ground source heat pumps, and distributed energy networks.
James Fogarty is a Professor at the Paul G. Allen School of Computer Science & Engineering, University of Washington. He serves as a core member of the DUB Group (Design. Use. Build.), a cross-campus initiative advancing Human-Computer Interaction and Design research. His work bridges computer science with healthcare applications, focusing on ubiquitous computing and accessibility. Fogarty's research centers on Human-Computer Interaction, Ubiquitous Computing, and Accessibility. He develops systems to overcome human obstacles in adopting intelligent computing technologies, particularly in healthcare contexts. His work spans food and symptom tracking for conditions like Irritable Bowel Syndrome, accessibility solutions for mobile interfaces, and self-experimentation frameworks for personalized health. Key themes include designing for real-world adoption, balancing automation with user control in personal informatics, and creating accessible technologies for diverse populations. His most recent publications reveal strong trends in health-focused HCI: 60% address chronic condition management (IBS, migraines), 30% focus on accessibility innovations, and 10% explore collaborative computing. Subfield analysis shows deep specialization in food/symptom tracking systems, mobile accessibility enhancements, and personalized health experimentation frameworks, with consistent emphasis on user-centered design and real-world deployment. Fogarty actively mentors doctoral students including Shaan Chopra, Tae Jones, and Aaleyah Lewis. His research receives direct funding from the National Science Foundation, National Library of Medicine, and Agency for Healthcare Research and Quality, with additional support from Adobe, Google, Intel, Microsoft, and Nokia. His lab operates at the intersection of HCI, health informatics, and ubiquitous computing. He leads projects within the DUB Group ecosystem, focusing on practical applications of sensing technologies and intelligent systems. Current work emphasizes patient-provider collaboration tools, accessibility repair mechanisms for mobile applications, and self-experimentation frameworks for personalized health management.
Ying Lu is an Associate Professor at the Department of Applied Statistics, Social Science, and Humanities within the Steinhardt School of Culture, Education, and Human Development at New York University. She holds dual PhDs in Public Policy and Demography from Princeton University (2005) and in Statistics from the University of North Carolina at Chapel Hill (2009). Before joining NYU, she was an Assistant Professor at the University of Colorado Boulder, affiliated with the Institute of Behavioral Science. Her research focuses on quantitative methodology in social and behavioral sciences, including applications in demography, health, and political behavior, as well as statistical methods like model selection and hypothesis testing for high-dimensional data. Her interdisciplinary work bridges statistical rigor with real-world societal challenges. Recent articles highlight her contributions to areas such as employee outcomes in HRM, gut microbiota-cardiometabolic disease links, and innovative clinical trial designs. She has also explored topics in food science, environmental catalysis, and sustainable development policy. Ying Lu’s academic journey reflects a commitment to advancing statistical methodologies while addressing pressing issues in health, policy, and environmental science. She has advised numerous projects but no specific students are listed in the provided texts.
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.
Dr. Yi Shen is a Senior Lecturer at the School of Chemical and Biomolecular Engineering, The University of Sydney, and Chair of RACI Women in Chemistry. She is also affiliated with multiple research institutes including Sydney Institute of Agriculture, Sydney Southeast Asia Centre, The Centre for Drug Discovery Innovation, and The University of Sydney Nano Institute. PhD in Soft Materials from ETH Zurich Postdoctoral research at University of Cambridge and Harvard University Her research focuses on protein phase behavior and functional biomaterials development, utilizing soft matter approaches and microfluidic techniques to address challenges in neurodegenerative diseases, sustainable materials, and biomedical engineering. She has published extensively in top journals like Nature Nanotechnology and PNAS, with a particular emphasis on: Protein liquid-liquid phase separation mechanisms Biomaterials from protein nanofibrils Microfluidic manipulation of biological systems Biodegradable bioplastics development Shear force effects on biomolecular systems Pathological protein aggregation dynamics Key scientific achievements include: 2022 ARC DECRA Fellowship 2022 Sydney Nano Frontier award 2018 ETH Zurich Spark Award (for Fe delivery system invention) 2012 Princeton Grand Challenges Program 2 patents pending 2 Nature Nanotechnology cover articles As an educator, she coordinates CHNG2802 Chemical Engineering Modelling and Analysis, co-teaches CHNG3804 Biochemical Engineering and CHNG5605 Bio-products: Laboratory to Marketplace, and guest lectures across biomedical and nanotechnology programs. Her lab actively collaborates with institutions in Switzerland (ETH Zurich), UK (Cambridge), and US (Harvard, Princeton), focusing on transforming biomolecular understanding into real-world applications in health, industry, and environmental sustainability.
Prof. Raul Fangueiro is a Full Professor and Vice-Dean at the School of Engineering, University of Minho, Portugal. As a Senior Researcher, he leads FIBRENAMICS – Institute of Innovation on Fiber-Based Materials and Composites. His work spans advanced materials (nano, smart, composites) and structures (3D, auxetic, multiscale) with applications in defense, healthcare, construction, and automotive sectors. Supervised over 20 PhD and Post-Doc researchers Scientific coordinator of 20+ national/international research projects Author of 200+ journal papers (H-index: 47), 500+ conference publications, 36 books, 40 patents Research focuses on nanotechnology , electrospinning , and sustainable material systems : Auxetic composites for personal protection Biodegradable nanofibers for medical use Smart textiles for biological/chemical resistance Recycled mineral/wood-based composites Graphene-reinforced green materials Multiscale fiber architectures Scientific recognition includes: Top 2% most influential scientist (Elsevier/Stanford 2020) Founder of AUXDEFENSE and ICNF conferences Editorial board member of leading composite journals Advisor to European Defense Agency/NATO working groups Active in industry-academia partnerships through spin-offs (Sciencentris, B4Logic, Beyond Composites, Givaware, Pixartidea) and collaborative projects with institutions like Instituto Superior Técnico, University of Aveiro, and international universities.
Carla P. Gomes is a Professor of Computer Science at Cornell University with joint appointments in the Department of Computer Science and the Dyson School of Applied Economics and Management. She holds a PhD in computer science from the University of Edinburgh and an M.Sc. in applied mathematics from the University of Lisbon. Her research focuses on artificial intelligence, constraint reasoning, optimization, and computational sustainability. As Director of the Institute for Computational Sustainability (ICS) and co-director of the Cornell University AI for Science Institute, she leads efforts to integrate AI with sustainability challenges. Her research themes include the integration of constraint reasoning, machine learning, and operations research to solve large-scale problems. She pioneered the field of Computational Sustainability, addressing environmental, economic, and societal challenges through AI. Gomes directed two NSF Expeditions in Computing awards and established CompSustNet, a large-scale sustainability research network. Key awards include the 2021 ACM–AAAI Allen Newell Award, AAAI Feigenbaum Prize, and fellowships from AAAI, ACM, and AAAS. Her work spans over 200 publications, with contributions to AI, sustainability, and materials discovery. She advises numerous PhD students and oversees postdocs in AI, sustainability, and interdisciplinary projects. Gomes' lab focuses on AI for scientific discovery, including autonomous materials synthesis and crystal-structure phase mapping. She collaborates with institutions like JCAP and the Materials Project, advancing AI-driven solutions for energy and environmental challenges. Current projects include Schmidt AI in Science postdoc initiatives and AI-driven materials discovery platforms like DRNets and SARA.
Dr. Paula Gonzalez-Figueroa is a Research Fellow at the Clinical Hub for Interventional Research (CHOIR) in the College of Health and Medicine at The Australian National University (ANU). She holds a PhD in Medical Sciences from ANU and completed postdoctoral research at the John Curtin School of Medical Research (ANU) and the Francis Crick Institute (UK). Her research focuses on immunology, autoimmunity, allergy, and clinical translation. Education: PhD in Medical Sciences (ANU), Biotechnology degree. Research Interests: Regulatory T cells, germinal centers, B cell biology, neuritin-based therapies, preclinical drug testing, and early-phase clinical trials. Affiliations: CHOIR (Researcher), Polizzotto Group, Genome Sciences and Cancer Division. Her work includes developing a neuritin-based biotherapeutic for allergies and autoimmune diseases, and leading preclinical/Phase I clinical programs for hematological cancers. She has contributed to studies on Tfr cell regulation, IgE responses, and germinal center dynamics. Publications span immunology, molecular biology, and translational research, with notable contributions to Nature Immunology , Cell , and Journal of Experimental Medicine .
Hamsa Bastani is an Associate Professor of Operations, Information and Decisions at the Wharton School, University of Pennsylvania, with a secondary appointment in Statistics and Data Science. She co-directs the Wharton Healthcare Analytics Lab and serves as an Associate Editor for Operations Research, M&SOM and OR Letters. Her academic journey began with summa cum laude graduation from Harvard in 2012 with an A.M. in physics and A.B. in physics and mathematics. She completed her PhD in Stanford's Electrical Engineering department under Mohsen Bayati, followed by a Herman Goldstine postdoctoral fellowship at IBM Research. Professor Bastani's research focuses on developing novel machine learning algorithms for data-driven decision-making, with applications spanning healthcare operations, social good, and revenue management. Her work demonstrates particular expertise in sequential decision-making (bandits, reinforcement learning), learning from auxiliary data sources (transfer learning, meta-learning), and designing effective human-AI interfaces (interpretability, fairness). She has made significant contributions to understanding how AI systems affect and augment human behavior, with the goal of designing AI tools that help humans thrive. Her publications reveal a strong trend toward high-impact applications of machine learning in critical societal domains. A significant portion of her recent work focuses on healthcare applications, including optimizing health supply chains in low- and middle-income countries, designing clinical trial protocols, and creating targeted public health interventions. Another major theme examines the complex relationship between humans and AI systems, particularly how AI affects learning outcomes and decision-making processes. Her work frequently bridges theoretical advances with practical implementation, as evidenced by country-scale deployments in Greece and Sierra Leone. Wagner Prize for Excellence in Operations Research Practice (2021) Pierskalla Award for Best Paper in Healthcare (2021, 2019, 2016) Behavioral OM Best Paper Award (2021) Public Sector in OR Best Paper Award (2024) INFORMS Data Mining Best Paper Award (2022) Wharton Teaching Excellence Award (2019, 2020, 2021) Professor Bastani has advised numerous PhD students who have gone on to prominent positions, including Pia Ramchandani (Director of Responsible AI at PwC), Arielle Anderer (Assistant Professor at Cornell Johnson), and Kan Xu (Assistant Professor at ASU Carey). Her research has been supported by collaborations with national governments, including the Greek government where she co-designed Eva, the national-scale reinforcement learning system for targeted COVID-19 testing, and the Government of Sierra Leone where she improved patient access to essential medicines by nearly 20% via decision-aware learning. She has also conducted the first large field study deploying generative AI tutors in high school math classes. She leads the Wharton Healthcare Analytics Lab and serves on the Steering Committee for the Penn Center for Health Incentives and Behavioral Economics and on the statistics advisory committee for the AHA Food is Medicine Initiative. Outside academia, she serves on the Workday AI Advisory Board, demonstrating her commitment to translating academic research into practical applications.
Prof. Dr.-Ing. Ahmad Osman is a Professor at the Saarland University of Applied Sciences (htw saar), specializing in Test Technologies and Test Methods within the Faculty of Engineering. He also holds an Adjunct Professor position at Laval University in Quebec, Canada, in the Department of Electrical Engineering and Computer Science. His research focuses on Artificial Intelligence applications in Signal and Image Processing for Non-destructive Testing (NDT) , with extensive work on Deep Learning , 3D Ultrasound Tomography , and Sensor Data Fusion in industrial contexts. Engineering Artificial Intelligence Signal Processing Image Processing Non-destructive Testing Quality Control Augmented Reality Osman leads the AutomaTiQ research group and serves as Head of the Algorithms/Signal and Data Processing Department at Fraunhofer IZFP . His recent publications (2017–2022) emphasize Deep Learning for defect detection in CFRP , Terahertz Imaging for artwork diagnostics, and Acoustic Sensors for agricultural quality control. He has organized international conferences on Structural Health Monitoring and contributed to Springer books on NDT technologies. His projects include ComforTex-AI (2024) and development of 3D positioners for ultrasound measurements. Collaborations span institutions in Germany, Canada, Italy, and Brazil, with advisory roles in the German Society for NDT and technical committees for conferences in Montreal and Egypt.
Scott Stanley is a Professor affiliated with the Martin Gatton College of Agriculture, Food and Environment at the University of Kentucky. He is associated with the Gluck Equine Research Center, a prominent institution within the college. His research focuses on equine health, encompassing areas such as genetics, immunology, infectious diseases, toxicology, and musculoskeletal studies. He also contributes to veterinary diagnostic services and genetic testing initiatives through the college's resources. His professional roles include academic leadership within the college, alongside colleagues like Dean Laura Stephenson, Ph.D. While specific publications or awards are not detailed in the provided text, his work aligns with the college's broader goals in advancing agricultural and veterinary sciences.
Helen Nguyen is a Professor in the Department of Civil and Environmental Engineering at the University of Illinois at Urbana-Champaign , where she has held positions since 2006. She also serves as an Affiliate at the Carle Illinois College of Medicine and the Institute for Genomic Biology . Her academic roles include chairing the Environmental Engineering and Science Program (2017-2019) and prior positions as Associate and Assistant Professor at UIUC. Ph.D. (2005), M.S. (2004) in Environmental Engineering from Johns Hopkins University M.S. (2000) in Earth and Environmental Science from University of Illinois at Chicago B.S. (1995) in Geology from Ivan Franko National University of L'viv Nguyen's research focuses on pathogens and biofilms in drinking water distribution systems , environmental surveillance of pathogens , and water and food safety . Her work spans microbial inactivation mechanisms, biofilm dynamics, and innovative water treatment strategies. Her recent 15 articles (2023-2025) emphasize coronavirus stability , legionella contamination , rotavirus on produce , biofilm mechanics , and climate-pathogen interactions . Trends include environmental virology, microbial risk assessment, and disinfection science. Scientific awards include the NSF CAREER award , Fulbright Specialist , AEESP/CH2M Hill Outstanding Dissertation Award , and University of Illinois College of Engineering Research Excellence Awards at both Assistant and Associate Professor levels. Nguyen advises 10 undergraduate students on pathogen removal and has mentored award-winning graduate students like Ruiqing Lu (2015) and Chamteut Oh (2024). She leads Engineers Without Borders teams and collaborates on USDA-funded food safety workshops .
Mei-Po Kwan is a distinguished academic holding multiple roles at The Chinese University of Hong Kong (CUHK). She serves as the Head of Chung Chi College, Choh-Ming Li Professor of Geography and Resource Management, Director of the Institute of Space and Earth Information Science, and Professor at The Jockey Club School of Public Health and Primary Care. Her research focuses on geospatial health, urban mobility, environmental health, and innovative GIS methods, emphasizing individual-level environmental exposure and social disparities. Education: Ph.D. Geography, University of California, Santa Barbara (1994) M.A. Urban Planning, University of California, Los Angeles (1989) B.SoSci. Geography, The Chinese University of Hong Kong (1985) Research Interests: Dr. Kwan’s work bridges health, transport, and environmental geography, leveraging cutting-edge GIS and mixed-methods approaches. Key themes include: Uncertain Geographic Context Problem (UGCoP) and Neighborhood Effect Averaging Problem (NEAP) GIS-based analysis of greenspace, air/noise pollution, and mobility Geospatial AI and real-time sensing technologies Health disparities in urban environments Grants & Awards: She has secured over $68 million in research funding, including recent grants from the Hong Kong Research Grants Council and Innovation and Technology Commission. Notable awards include Fellowships from the American Association of Geographers, Royal Geographical Society, and multiple Highly Cited Researcher recognitions (2019, 2021). Professional Service: Editor of Annals of the American Association of American Geographers , founder of the International Geospatial Health Research Network, and member of prestigious editorial boards and advisory councils. Labs & Teams: Leads the Institute of Space and Earth Information Science and collaborates on projects like the 15-minute city framework, carbon monitoring systems, and geospatial health analytics.
