Arnab Bhattacharyya is an Associate Professor at the Department of Computer Science, University of Warwick. His research bridges the foundations of AI and theoretical computer science , focusing on algorithms for big data , high-dimensional statistics , and causal inference and discovery . He has co-taught courses at the University of Warwick, National University of Singapore, and Indian Institute of Science since 2013 Research Interests : Theoretical Computer Science , Foundations of AI , Algorithms , and Statistical Learning . His work includes property testing , causal graph estimation , and high-dimensional distribution learning . Scientific Awards : Best of PODS 2021 2022 ACM SIGMOD Research Highlight 2022 CACM Research Highlight Group Members : His former and current advisees include Palash Dey (IISc Ph.D., now at IIT Kharagpur), Suprovat Ghoshal (IISc Ph.D., now at University of Michigan), and Vipul Arora (NUS Ph.D., now at Simons Institute). Other notable students include Philips George John , Yuhao Wang , and Davin Choo .
Humberto Vergara is an Assistant Professor in the Department of Civil and Environmental Engineering at the University of Iowa, and concurrently serves as an Assistant Research Engineer at IIHR—Hydroscience and Engineering. He is also affiliated with the Iowa Flood Center. His work spans numerical hydrologic modeling, flash flood forecasting, and remote-sensing hydrology, with a strong emphasis on scientific computing in hydrologic applications. Education: PhD, Civil Engineering (Water Resources), University of Oklahoma MSc, Civil Engineering (Water Resources), University of Oklahoma BS, Environmental Engineering, El Bosque University, Colombia Research Interests: Vergara’s research is centered on extending flash flood forecasting capabilities in data-scarce regions, understanding flash floods in post-fire environments, and improving the physics representation in parsimonious hydrologic models. He also focuses on extending lead times for flash flood forecasts and warnings, leveraging satellite observations and machine learning techniques. His recent work includes developing satellite-based frameworks for early warning systems in West Africa, evaluating global precipitation products, and integrating machine learning models to enhance precipitation nowcasting and flood impact classification. Scientific Awards: No awards or honors are explicitly mentioned in the provided text. Research Labs and Teams: He leads the Advanced Hydrology and Warning Applications Laboratory at the University of Iowa, which focuses on cutting-edge research in hydrologic modeling, early warning systems, and remote sensing applications for flood forecasting.
Prateek Mittal is a Professor in the Department of Electrical and Computer Engineering at Princeton University, with associated faculty appointments in the Department of Computer Science and the Center for Information Technology Policy. His leadership roles include Associate Chair of the ECE Department (2025) and Director of Undergraduate Studies (2025), demonstrating his significant institutional impact. Mittal's research focuses on privacy-preserving and secure systems, with particular expertise in privacy enhancing technologies (including anonymous communications and statistical data privacy), adversarial machine learning, and Internet/network security. His methodological approach draws on data science, network science, distributed systems, and applied cryptography. He has made foundational contributions to website fingerprinting research, developing precision optimizers that revolutionized open-world traffic analysis attacks. His recent publications reveal a strategic shift toward examining security and privacy challenges in large language models and AI systems, with research on context manipulation attacks, privacy auditing frameworks, and robust defenses against adversarial inputs. This represents a natural evolution of his work from traditional network security to the frontier of AI security. Outstanding Paper Award and Honorable Mention, ICLR 2025 ACM Distinguished Member (2024) Distinguished Alumni Awards from IIT Guwahati and UIUC (2024) ACM Grace Murray Hopper Award (2023) Multiple Caspar Bowden Award Runner Up recognitions (2020-2022) National Science Foundation CAREER Award (2016) Professor Mittal has received consistent recognition for teaching excellence through Princeton Engineering's Commendation List in multiple years. His research program has been supported by prestigious funding from ARO, ONR, NSF, and industry partners including Google, Facebook, IBM, Intel, and Cisco. He serves in significant leadership roles including Deputy Chair of the ACM Grace Murray Hopper Award Committee (2025-2026) and Editorial Board member for Privacy Enhancing Technologies.
Professor Ian Chetter is a Professor of Surgery at the Hull York Medical School, University of Hull , and an Honorary Consultant Vascular Surgeon at Hull University Teaching Hospitals NHS Trust. He qualified from the University of Leeds in 1990, holds an MD (2000) from Leeds, and has clinical training certifications including FRCS (Eng) (1994) and FRCS (Gen Surg) (2002). Education: MBChB (1990), MD (2000), FRCS (Eng) (1994), FRCS (Gen Surg) (2002), Postgraduate Certificate in Medical Ultrasound (2005), Postgraduate Diploma in Clinical Education (2011) His research focuses on Health Services Research and New Technologies for arterial/venous disease , wound healing , and SSI prevention , with molecular biology work on aneurysmal disease and ischaemia reperfusion . Clinical trials include DRESSINg (DACC dressings), VENUS 6 (compression therapies), SOLEFUL (shockwave therapy for DFUs), and SWHSI-2 (NPWT vs. usual care). Current projects explore remote surgical monitoring (ASSIST), machine learning for outcome prediction, and decolonization techniques (DEPILATION-Feasibility). Scientific awards include the NIHR Senior Investigators Award (2018-2022) and the Hunterian Professorship (2000). He supervises MD students and contributes to Vascular Society educational programs like ASPIRE. Affiliated with the Centre for Clinical Sciences and Institute for Clinical and Applied Health Research , his work bridges clinical practice, cost-effectiveness analysis, and translational research.
Dr. Jeffrey Kwan is a Lecturer in Statistics at the School of Mathematics and Statistics, University of New South Wales (UNSW Sydney). His research focuses on probability theory and stochastic processes, particularly Hawkes processes and their asymptotic behavior. He completed his PhD in 2023, specializing in ergodicity and applications for non-stationary and non-exponential Hawkes models. PhD (UNSW Sydney, 2023): Ergodicity of Hawkes processes Jeffrey's research spans probability theory, stochastic processes, financial data modeling, and data-driven legal analysis. He has published extensively on Hawkes processes, including parametric inference, ergodicity, and applications in terrorism modeling, crime analysis, and public policy. His scientific awards include the Excellence in Postgraduate Research (Statistical Society of Australia, NSW Branch, 2022), University Medal (UNSW Sydney, 2017), and multiple Dean's List recognitions. He has taught undergraduate and postgraduate courses in statistics, probability, and data science, including roles in the Business School and Faculty of Science. 2025: Chair, School of Mathematics and Statistics EDI Committee 2024: Secretary, Statistical Society of Australia (NSW Branch) 2023: Statistical Consultant at Stats Central (Mark Wainwright Analytical Centre)
Xiaohui (Helen) Gu is a Professor in the Department of Computer Science at North Carolina State University, where she leads cutting-edge research in computer systems. Her work bridges theoretical innovation with practical applications in cloud and distributed environments, maintaining active collaborations with industry leaders including IBM, Google, and Credit Suisse. Education: Ph.D. in Computer Science, University of Illinois at Urbana-Champaign (2004) M.S. in Computer Science, University of Illinois at Urbana-Champaign (2001) B.S. in Computer Science, Peking University, China (1999) Gu's research centers on autonomous system management through machine learning, with significant contributions to cloud infrastructure reliability. Her work addresses critical challenges in performance debugging, security vulnerability detection, and resource optimization across distributed systems. Current projects focus on self-supervised learning frameworks for container security and causal analysis techniques for microservice performance issues, demonstrating strong interdisciplinary connections between systems engineering and artificial intelligence. Her publication trends reveal deep specialization in cloud-native system resilience, with recent work emphasizing ML-driven anomaly detection (2022-2024), container security (2019-2022), and blockchain privacy mechanisms (2019). The research consistently targets production-grade solutions for industry-scale problems, evidenced by patents licensed to Google and commercialization through her startup InsightFinder. Key honors include: National Science Foundation CAREER Award (2011) Four IBM Faculty Awards (2008, 2010, 2011) Google Research Awards (2009, 2011) Best Paper Awards at ICDCS 2012 and CNSM 2010 IBM Invention Achievement Awards (2004, 2006, 2007) Gu actively mentors PhD students through her DANCE research group (Distributed system research on Autonomy, resilience, Collaboration, and Energy), with current projects funded by $2.3M+ in grants from NSF, ARO, and industry partners. Her sponsored research portfolio includes the NSF-funded CAREER project on virtualized infrastructure reliability and Cisco-sponsored work on machine learning for IT service assurance. She has served as associate editor for IEEE TPDS and program co-chair for major conferences including USENIX ICAC 2014. Gu leads the DANCE research laboratory, which specializes in building resilient cloud systems through techniques like speculative anomaly diagnosis and self-evolving monitoring. The lab maintains strong industry ties, with technologies commercialized through InsightFinder and adopted by Google. Current initiatives focus on predictive management of multi-tenant cloud environments and hybrid computing models for energy-efficient data centers.
Dawn Schrader serves as an Associate Professor in the Department of Communication at Cornell University's College of Arts and Sciences. She holds affiliations with the Feminist, Gender and Sexuality Studies Program and Psychology departments. Her work bridges communication studies, moral psychology, and technology ethics, focusing on how digital environments shape human development and ethical decision-making across the lifespan. Dr. Schrader earned her EdD from Harvard University's Graduate School of Education in 1988 and a Master's Degree from The Ohio State University in 1982. Her educational background informs her interdisciplinary approach to understanding the complex interplay between technology, cognition, and moral development. Schrader's research centers on the Action-Judgment-Awareness model, which examines how real-life choices (Action), cognitive frameworks (Judgment), and metacognitive awareness interact in moral contexts. She investigates privacy awareness, information sharing behaviors, and the ethical implications of emerging technologies including AI, robotics, and cybersecurity systems. Her work takes a lifespan developmental perspective, with particular emphasis on early adolescence through adulthood. Analysis of her publications reveals consistent focus on technology ethics, particularly privacy issues and moral decision-making in digital environments. Her work spans from theoretical explorations of moral cognition to practical applications for ethical AI development and privacy-aware system design. Recent publications increasingly address social justice implications of technology, including inclusion of people of color in digital spaces and autonomy concerns in surveillance contexts. Faculty Fellow (2018) Cornell University, Court Kay Bauer Residence Dr. Schrader teaches courses including COMM 4350: Communicating Leadership and Ethics, COMM 4300: Ethics in New Media, Technology, and Communication, and cross-listed courses like ASRC 1120/Wonder Women. Her teaching philosophy emphasizes creating supportive learning environments where students actively construct meaning through engagement with social psychological and socio-technical theories. She focuses on helping students connect theoretical concepts to real-world applications while fostering ethical reasoning and intellectual growth. As part of Cornell's Department of Communication research ecosystem, Schrader contributes to the department's work in technology and social media research areas. Her scholarship intersects with the Citizens and Technology Lab (CAT Lab) and other research groups examining how communication processes and systems influence social structures in technologically-mediated environments.
Ihsan Engin Bal is a Lecturer in Construction Safety & Earthquakes at the Hanze University of Applied Sciences , affiliated with the Research Centre for Built Environment – NoorderRuimte . With a background in Civil and Structural Engineering from Karadeniz Technical University (2000), his work bridges seismic risk mitigation, timber-masonry structural systems, and digitalization of construction processes. Education: BEng in Civil and Structural Engineering (1996-2000), Karadeniz Technical University. His research focuses on earthquake engineering , particularly unreinforced masonry (URM) walls, timber structural connections, and low-cost sensor applications for construction safety. Recent projects include Hysteresis (hybrid testing of timber buildings) and Trust in Timber (bio-based construction workforce development). He explores applying digital tools like automated crack detection and vibration monitoring to enhance structural resilience. Key themes in his 2024-2025 publications include seismic performance of URM walls, noise-resistant crack segmentation via machine learning, and climate-proof infrastructure. He collaborates extensively with researchers like E. Smyrou and O. Arslan. Professor Bal actively engages in public discourse, notably analyzing Turkey-Syria earthquake vulnerabilities and advocating for improved construction practices. His work spans practical experiments, computational modeling, and policy-oriented insights for disaster prevention.
Sébastien Tixeuil is a Professor at Sorbonne Université, affiliated with LIP6 (CNRS 7606), a leading computer science laboratory in Paris, France. He is a Senior Member of the Institut Universitaire de France (IUF), a prestigious recognition of excellence in research and teaching. His work is centered in the Department of Computer Science within the Faculty of Science and Engineering. His research focuses on the theoretical and practical foundations of distributed systems, with emphasis on fault tolerance, self-stabilization, mobile robotics, and dynamic networks. He investigates how systems can recover from faults autonomously and operate correctly under uncertainty, adversarial conditions, and changing environments. His recent work extends into IoT, blockchain, and formal verification of distributed protocols. The most recent publications highlight trends in distributed decision-making under partial information, autonomous classification of IoT devices, resource-efficient stabilization algorithms, solving combinatorial games like Quixo, and indulgent rendezvous protocols for fault-prone robots. These works reflect a strong integration of formal methods, algorithm design, and real-world applicability in networked and robotic systems. He has been honored as both a Senior Member and previously an Honorary Member of the Institut Universitaire de France, among the highest academic distinctions in France. Current Research Projects: GRIFIN (ANR) TURFU-NET (ANR) CyberNemo (EU) NEMO (EU) Students Supervised: Sébastien Bouchard – Proof assistant for probabilistic robots Alice Di Carlo – Blockchains for Healthcare Organizations Anthony Honorat – Networks of Fat Robots Giovanni Farina – Byzantine Tolerance in Dynamic Networks Adam Heriban – Realistic Robot Networks Nesrine Ammar – Internet of Things He leads or contributes to major collaborative research initiatives funded by the French National Research Agency (ANR) and the European Union. His advising spans PhD and Master’s students, focusing on cutting-edge topics in distributed computing and networked systems. His lab, embedded within LIP6 and the former NPA team (Networks and Systems), fosters interdisciplinary research in autonomic and resilient systems.
Nicklas Holmberg serves as Senior Lecturer and Head of the Department of Informatics at Lund School of Economics and Management (LUSEM), Lund University. With a PhD in Information Systems specializing in Process and Service Design and Development, he leads the Department of Informatics while maintaining active research and teaching responsibilities. His professional roles include Director of Studies and Director of the Bachelor's Programme, demonstrating comprehensive leadership within the academic unit. Dr. Holmberg's research focuses on Business Process Service Orientation with significant applications in healthcare and banking sectors. His work on the business logic centric digital service VacSam demonstrates practical implementation of his research in vaccination coordination systems. Additional research areas include Service Oriented Architecture, Decision Modeling and Automation, Business Rules Approach, and Business Process Modeling. His research profile shows strong alignment with UN Sustainable Development Goals, particularly in areas related to technology for societal benefit. Analysis of his recent publication trends reveals a strategic evolution from foundational work in Enterprise Resource Planning Systems toward contemporary challenges in digital transformation, AI integration, and information systems education. His 2023-2024 publications increasingly address the impact of generative AI on IS education, decentralized web technologies, and enterprise social media applications, while maintaining continuity with his established research trajectory in business process management. Senior Associate at MIT Research School eGovernment Member DMN On-Ramp Review Group Member IBM Smarter Planet Reference Member Microsoft Certified Technology Specialist (MCTS) As an educator, Holmberg teaches Business Decision Management at the advanced postgraduate level and supervises both BSc and MSc Degree Project Essays. His supervision extends to PhD candidates, with Sinan Deniz listed as a current PhD student under his guidance. He has been involved in significant research projects including S-HELP (Securing Health.Emergency.Learning.Planning), funded by the European Commission FP7 program (2014-2017), and VacSam – Digital eService for Coordinated Vaccination Control (2008-2012). His departmental leadership role encompasses strategic direction for the Informatics department within LUSEM's broader academic framework.
Gitte Rasmussen is a Professor at the Department of Cultural and Linguistic Studies, University of Southern Denmark. Her research focuses on social interaction through ethnomethodology and conversation analysis (EMCA), particularly examining how individuals with disabilities like dementia or cerebral palsy navigate physical and digital environments. External Appointment: Associate Editor, University of Toronto Press Key Collaborations: TRINITY Project (robotics & motion), LIDEM (dementia research center) Research Themes Disability & Interaction: Analyzing gaze behavior, body weight unloading robotics, and multimodal communication in caregiving Technology & AI: Exploring eye-tracking applications, robot-assisted training, and digital commerce semiotics Social Practices: Studying everyday life dynamics in shopping, nursing homes, and virtual environments Scientific Contributions 114+ publications across social sciences, computer science, and healthcare 2024: Journal of Interactional Research in Communication Disorders (visual impairment studies) 2025: Pragmatics and Society (e-shopping analysis) Awards & Recognition 2012: Fyns Stiftstindendes Forskerspris (research prize) Advising & Projects Supervised 6 PhD students including Dakwar (digital commerce), Nicolaisen (robotics), and Lauridsen (ethics) Principal Investigator for 4 major projects (DAP, RESEMINA, Demensvenlighed, TRINITY) Collaborated with researchers across Denmark, Canada, and the Netherlands Labs & Networks Co-PI at LIDEM (Dementia Research Center) Active in international EMCA and multimodality networks Developed methods for integrating eye-tracking and video analysis in social interaction studies
Dr. Marius Buliga is a Professor of Mathematics and Director of Applied Mathematics at the University of Pittsburgh's Division of Physical and Computational Sciences. He contributes to both academic research and educational innovation, focusing on graph theory and mathematical software integration in undergraduate teaching. Ph.D. in Mathematics (2002) M.S. in Information Science (2002) M.S. in Computer Science (1995) B.S. in Computer Science (1994) His research spans graph theory , computational modeling for educational tools (Mathematica/Java applets), and interdisciplinary work in biomedical informatics and systems medicine . Recent publications analyze inflammatory responses in trauma/sepsis, postural control in Parkinson's disease , and combinatorial graph designs , demonstrating a multidisciplinary approach combining mathematics with clinical and computational applications. Dr. Buliga teaches undergraduate mathematics courses including Calculus, Linear Algebra, and Numerical Analysis. His work integrates algorithmic development with biomedical modeling , reflecting collaborations across disciplines.
Katherine E. Goodman serves as an Assistant Professor in the Department of Epidemiology & Public Health at the University of Maryland, Baltimore School of Medicine, where she bridges machine learning applications with public health law. Her dual expertise in epidemiology (PhD, Johns Hopkins) and law (JD, Columbia) informs cross-disciplinary collaborations across medical and legal institutions. Her educational background includes: PhD in Epidemiology (Johns Hopkins Bloomberg School of Public Health, 2018) Postgraduate Diploma in Public Health (University of Auckland, 2013) JD from Columbia University School of Law (2010) BA in Moral Philosophy (Dartmouth College, 2006) Goodman's research pioneers AI-driven solutions for antimicrobial resistance surveillance, clinical algorithm regulation, and pandemic response systems. She develops NLP/LLM methodologies using electronic health records and claims data across infectious diseases, oncology, and maternal-fetal medicine, with particular focus on early-onset colorectal cancer detection and gut carriage screening. Her work uniquely integrates FDA law perspectives with public health informatics, examining legal frameworks for clinical algorithm oversight. Analysis of her 15 most recent publications reveals dominant themes in large language model implementation for infection control (40%), clinical algorithm ethics (30%), and antimicrobial stewardship (30%). Key methodological trends include multicenter validation of NLP tools across 600+ hospitals and development of equity-focused frameworks like FAIRS for sex-inclusive algorithm design. Her collaborative projects involve: Joint initiatives between UMB School of Medicine and School of Law National studies spanning 928 U.S. hospitals Real-world AI implementation trials in academic medical centers
Bartolomeo Stellato is an Assistant Professor at Princeton University's Department of Operations Research and Financial Engineering. He is associated faculty in Electrical and Computer Engineering and Computer Science, and affiliated with Princeton's AI, Robotics, and Center for Statistics and Machine Learning initiatives. His research bridges mathematical optimization, machine learning, and optimal control for real-time decision-making in uncertain environments. PhD advisors: Georgina Hall, Brandon Amos Key collaborators: Bart Van Parys (MIT), Jaime Fernandez Fisac (UPenn), Adrien Taylor (INRIA) His work on Mean Robust Optimization combines robust and distributionally robust optimization through data clustering, achieving 3+ orders of magnitude speedups in portfolio optimization. He also develops learned optimizers (e.g., L2WS, GeNIOS) and OSQP , which won the Beale–Orchard-Hays Prize. Recent grants include NSF CAREER (2023) and ONR Young Investigator (2025) awards. Article Trends : His research spans optimization verification (3/7 of 2025 articles), data-driven methods (5/7 of 2024-2025 articles), control applications (4/15 articles), and equitable resource allocation (2/15 articles). Key subfields include algorithm verification, stochastic optimization, multi-agent systems, and hardware acceleration. Scientific Awards : ONR Young Investigator (2025), Howard B. Wentz Award (2024), NSF CAREER (2023), ISSNAF Strazzabosco (2022) Students : Mentored 12+ graduate students/postdocs including Irina Wang (Wallace Fellowship), Rajiv Sambharya (Best Paper Award at JMLR), and Vinit Ranjan (co-author Mathematical Programming paper) He leads the Princeton Optimization, Learning, and Control Workshop and collaborates with institutions like MIT, INRIA, and Los Alamos National Laboratory. His group develops open-source tools (OSQP, L2WS) with over 300,000 downloads.
Iain Greig serves as a Reader (equivalent to Associate Professor) at the University of Aberdeen's School of Medicine, Medical Sciences and Nutrition, where he leads drug discovery initiatives at the Kosterlitz Centre for Therapeutics. His multidisciplinary work bridges medicinal chemistry, pharmacology, and commercialization, with active collaborations at the University of Toronto and significant grant funding from CIHR, MND Association, and industry partners. His research spans Novel cannabinoid receptor modulators for depression, schizophrenia, and liver fibrosis Synthetic retinoids targeting neurodegenerative diseases Fluorinated cardiovascular therapeutics including perhexiline derivatives Drug repurposing for osteoporosis, multiple sclerosis, and pain management Notable projects include a Phase IIa successful rheumatoid arthritis treatment and development of allosteric CB1 modulators to avoid opioid-related side effects. Analysis of his 15 most recent publications reveals dominant themes in cannabinoid pharmacology (40% of works), neurodegenerative disease mechanisms (25%), and innovative medicinal chemistry approaches like fluorine bioisosterism (20%). His work consistently emphasizes translational pathways from target validation to clinical application, with increasing focus on AI-driven drug design since 2022. Award highlights include: RSE Fellowship for commercialization expertise Co-founding two spin-out companies: OsteoRx (rheumatoid arthritis) and Signal Pharma (pain) Multiple Proof of Principle grants from Canadian Institutes for Health Research As Head of Operations for the Kosterlitz Centre, he manages intellectual property and coordinates multidisciplinary teams across 12 active grants totaling over $3.5M annually. His teaching responsibilities include directing the Biobusiness Programme and courses on drug commercialization, reflecting his dual expertise in science and entrepreneurship. Beyond academia, he applies his mountaineering experience (including ascents of 6,893m Ojos del Salado) to foster resilience in research teams.
