Vikrant Vaze is the Stata Family Career Development Associate Professor and Executive Director of the Master of Engineering Management Program at Dartmouth's Thayer School of Engineering. He leads research in transportation systems, aviation optimization, and healthcare analytics, developing data-driven solutions for complex logistics challenges. His work integrates game theory, statistical modeling, and large-scale optimization. Research spans sustainable urban mobility, airline disruption recovery, multimodal pricing alliances, and healthcare operations. Articles consistently focus on optimization algorithms for real-world transportation and healthcare systems, with recent emphasis on electric aerial mobility and pandemic-responsive logistics. Major Awards: INFORMS Aviation Applications Best Paper (2024, 2023) AGIFORS Best Innovation Award (2024) NSF CAREER Award (2018) President of India Gold Medal As founding co-director of the Operations Research Group, he collaborates with industry partners like Multivariate Systems to translate academic research into deployable solutions.
H. Jonathan Chao is a Professor in the Department of Electrical and Computer Engineering at New York University (NYU Tandon School of Engineering). He is the Director of the High-Speed Networking Lab, leading a team of 6 PhD students and 10 Master’s students. His research focuses on software-defined networking, network function virtualization, datacenter networks, and high-speed packet processing. Chao has held significant roles, including Head of the ECE Department (2004–2014) and former CTO of Coree Networks. He has authored over 200 publications and holds 58 patents. His awards include IEEE Fellow and National Academy of Inventors (NAI) Fellow. Education: B.S. and M.S. from National Chiao Tung University (Taiwan), Ph.D. from Ohio State University. Research Highlights Developing solutions for data center networks, network security, and quality of service control. Pioneering work in programmable packet schedulers, reinforcement learning for traffic engineering, and SDN security frameworks like SDNShield. Contributions to hybrid SDN networks, bufferless switch architectures, and energy-efficient data center designs. Awards Fellow of National Academy of Inventors (NAI) Fellow of IEEE Telcordia Excellence Award (1987) IEEE Best Paper Award (2001) IEEE New Jersey Coast Section Speaker of the Year (2003) Advisees & Labs Supervises 6 PhD and 10 Master’s students in the High-Speed Networking Lab. Collaborates with the Center for Advanced Technology in Telecommunications (CATT) to advance telecom innovations. Labs & Teams Directs the High-Speed Networking Lab, focusing on cutting-edge networking solutions, and contributes to CATT’s mission of technology transfer and entrepreneurship.
Hao Chen, Ph.D. is an Associate Professor in the Department of Statistics at the University of California, Davis. His research focuses on statistical methodology for high-dimensional and non-Euclidean data, including anomaly detection, graph-based methods, and change-point analysis. He also explores AI security, multimodal models, and geospatial applications. His work bridges statistical theory and practical machine learning challenges. Education: Ph.D., Graduate Group in Biostatistics, Stanford University Research Interests: Dr. Chen’s expertise spans statistical methods for streaming data, categorical data analysis, and allele-specific copy number variation. He has pioneered work in detecting signals in complex datasets and developing robust AI systems. His recent focus includes mitigating modality interference in LLMs, enhancing model safety via guardrails, and advancing geospatial AI through projects like GeoLM. Publications: His recent work addresses cutting-edge topics such as multimodal model vulnerabilities, unlearning algorithms, and clinical radiology applications. Key themes include improving model robustness, ethical AI design, and interdisciplinary data integration. Labs/Teams: Engages in collaborative projects at UC Davis, though specific lab names are not listed in the provided information.
Binil Starly is an Adjunct Professor at North Carolina State University's Edward P. Fitts Department of Industrial and Systems Engineering, part of the College of Engineering. He leads the Data Intensive Manufacturing Laboratory (DIME Lab), focusing on digital-physical integration in manufacturing, additive manufacturing, and biofabrication. His work emphasizes democratizing manufacturing access through machine learning and smart systems. Starly holds a B.S. in Mechanical Engineering from the University of Kerala (2001) and a Ph.D. from Drexel University (2006). He previously worked at the University of Oklahoma on tissue engineering platforms. His research spans digital factories, smart manufacturing, and biometrology, with over 45 journal publications. His awards include the NSF CAREER Award (2009), SME Young Manufacturing Engineer Award (2011), and multiple teaching/research recognitions at NC State. He teaches courses on product development, additive manufacturing, and Python for industrial engineers. Starly’s research trends emphasize blockchain in manufacturing ecosystems, cybersecurity for IoT devices, and knowledge graphs for service discovery. He co-leads the Functional Tissue Engineering (FTE) Program, integrating regenerative medicine with scalable manufacturing processes. His grants focus on smart manufacturing innovation, blockchain platforms, and real-time bioprinting monitoring. He advises 7 graduate and 3 undergraduate students, having guided 22 M.S. and 6 Ph.D. students. His outreach includes online courses on smart manufacturing and Python programming through NC State’s Wolfware Outreach. The DIME Lab develops advanced manufacturing technologies, including digital twins for industrial metaverse applications and machine authentication systems. Collaborations span academia, industry, and government to advance personalized manufacturing solutions.
Piotr Przybyła is a tenure-track Assistant Professor at Universitat Pompeu Fabra in Barcelona, Spain, where he researches in the TALN (Natural Language Processing) Research Group. He maintains a significant affiliation with the Linguistic Engineering Group at the Institute of Computer Science, Polish Academy of Sciences (ICS PAS) in Warsaw, Poland, where he completed his PhD in Computer Science. Previously, he worked as a research fellow at the National Centre for Text Mining (NaCTeM) at the University of Manchester. Przybyła's research focuses primarily on Natural Language Processing with particular emphasis on misinformation detection, adversarial attacks on text classifiers, text simplification, and Polish language processing. His work bridges theoretical NLP with practical applications for credibility assessment and language understanding. He has developed innovative approaches for testing the robustness of text classifiers against adversarial examples and has made significant contributions to Polish language resources and processing tools. His recent publications demonstrate a strong trajectory in examining the robustness of NLP systems, particularly in the context of misinformation detection and credibility assessment. His work spans from foundational research on language model behavior to practical applications in Polish language processing and text simplification. The ERINIA project, funded by a prestigious Marie Skłodowska-Curie Postdoctoral Fellowship, represents a significant contribution to understanding how misinformation detection systems can be made more robust against adversarial attacks. Marie Skłodowska-Curie Postdoctoral Fellowship for the ERINIA project Computing grant of 10,000 hours on the Athena supercomputer for accelerating work in the ERINIA project Przybyła actively contributes to the NLP community through conference organization, shared tasks (such as coordinating the InCrediblAE shared task for CheckThat! 2024), and developing open-source tools like Plainifier for multi-word lexical simplification. His work demonstrates a commitment to both advancing NLP research methodology and addressing practical challenges in misinformation detection and language understanding across multiple languages, with special attention to Polish language processing.
Carmen Galaz García is an Assistant Teaching Professor at the Bren School of Environmental Science & Management at UC Santa Barbara. She teaches data science courses including EDS 220 and capstone projects, emphasizing accessible technical education and DEIJ initiatives. Previously, she worked at the National Center for Ecological Analysis and Synthesis (NCEAS), analyzing remote sensing data and developing educational resources. Carmen holds a Ph.D. in Mathematics (UCSB) and a B.Sc. in Mathematics from the University of Guanajuato/CIMAT, Mexico. Her research focuses on environmental data science applications such as invasive species mapping using machine learning and geospatial analysis. She actively contributes to reproducible workflows in Python and collaborates on topological data analysis in environmental contexts. Professional affiliations include NCEAS and Bren School's environmental data programs. Education: Ph.D. in Mathematics, UC Santa Barbara (2021) B.Sc. in Mathematics, Universidad de Guanajuato/CIMAT (2015) Research emphasizes interdisciplinary approaches combining mathematics, ecology, and data science to address environmental challenges. She leads capstone projects integrating real-world environmental datasets and mentors students through collaborative data science workflows.
Dr. Andrew Michael Ryan is a Professor in the Department of Health Services, Policy, and Practice at Brown University and Director of the Center for Advancing Health Policy through Research. His work focuses on evaluating the impact of healthcare payment reforms, particularly in Medicare and accountable care organizations (ACOs). Ryan has extensive experience analyzing longitudinal healthcare data and has contributed to national policy discussions on payment incentives and value-based care. Previously, he served as a professor at the University of Michigan. Education: PhD from Brandeis University. Research Interests: Dr. Ryan’s research examines how payment models influence healthcare quality, spending, and patient outcomes. Key areas include bundled payments, Medicare Advantage plan performance, and the role of financial incentives in driving system-wide improvements. His work often combines econometric methods with policy analysis to inform actionable reforms. Publications Trends: Recent work highlights critiques of Medicare Advantage rating systems, analysis of bundled payment impacts on care quality, and examinations of hospital payment policies. A recurring theme is the interplay between financial incentives and measurable improvements in healthcare value. Awards: No explicitly listed awards in provided texts. Advising & Grants: Ryan has led research grants examining payment reform efficacy and has advised federal technical panels. His team’s work frequently involves collaborations with economists and healthcare policymakers to translate findings into practice. Labs/Teams: Directs the Center for Advancing Health Policy through Research, fostering interdisciplinary collaborations on payment and delivery system innovations. Key partners include researchers from epidemiology, biostatistics, and clinical medicine.
Cagdas Onal is an Associate Professor of Robotics Engineering at Worcester Polytechnic Institute (WPI). He holds a BS and MS from Sabanci University (2003, 2005) and a PhD in Robotics from Carnegie Mellon University (2009). His research focuses on soft robotics, bio-inspired systems, and control theory , emphasizing the development of flexible robotic components for healthcare, industry, and sustainable applications. He leads the Soft Robotics Lab and the Future of Robots in the Workplace (FORW-RD) initiative, advancing human-centric robotics solutions. Research interests include designing bio-inspired soft robots (e.g., origami-inspired snake robots), developing modular actuation systems with embedded sensors, and exploring applications in medical devices and assistive technology. His work aligns with UN Sustainable Development Goals, particularly in healthcare access (SDG 3), quality education (SDG 4), and innovation (SDG 9). Recent projects include origami-based robotic arms for wheelchair users , self-contained underwater robots, and haptic interfaces for teleoperation. His lab collaborates on国家级 grants like the NSF-funded NRT Program and has secured patents for actuator designs (e.g., Hydro Muscle). Labs/Teams: Soft Robotics Lab, FORW-RD, NRT Program. Notable media coverage includes Worcester Telegram & Gazette and Spectrum News for innovations in human-friendly robotics.
Prof. Joaquin GARCIA ALFARO is a Professor at Telecom SudParis, affiliated with the SCN department. His research focuses on cybersecurity, network security, quantum computing applications, and resilience engineering in cyber-physical systems. He has contributed to advancements in intrusion detection systems, blockchain integration in cellular networks, and privacy-preserving frameworks for IoT and healthcare. University: Telecom SudParis Key Research Areas: Cybersecurity, Quantum Computing, IoT Security, Resilience Engineering Labs: SAMOVAR laboratory His work emphasizes practical solutions for real-world challenges, including secure data provenance, digital twin implementations, and energy-efficient edge computing. Recent research explores quantum-resistant protocols and collaborative drone systems.
Marco Seeber is a Professor at the University of Agder's Department of Political Science and Management. He holds a PhD from the University of Chieti Pescara (Italy) and has previously worked at the University of Lugano (Switzerland) and Ghent University (Belgium). His research focuses on public policy, governance, and management with specialization in higher education systems, research evaluation, and science policy. Professor Seeber's research examines policy implementation, research metrics, peer review systems, academic careers, internationalization, and interdisciplinarity in higher education. He employs comparative and quantitative methodologies to analyze governance structures and policy impacts across different educational systems. He has received significant recognition including the Swiss Prize for Research in Education (2019) and fellowships from IEEE, AIUM, and AIMBE. As Co-Editor-in-Chief of the European Journal of Higher Education, he shapes scholarly discourse in his field. He currently coordinates the Horizon CSA project IANUS (2025-) and leads courses in organizational theory, research methodology, and leadership.
Isabella Di Lenardo is a Lecturer and Scientist at the Digital Humanities Institute (DHI) at École Polytechnique Fédérale de Lausanne (EPFL), where she also serves as the coordinator of the EPFL Time Machine Unit and the European Local Time Machines. She holds affiliations across multiple departments, including DHI-GE, SAR-ENS, SHS-ENS, and EDDH-ENS, reflecting her interdisciplinary role in teaching and research. Her educational background includes a PhD in Theories and Art History, with postdoctoral and faculty experience at institutions such as INHA (Paris), EPFL, and IUAV (Venice). Her research spans Digital Humanities, Art History, Urban History, and GIS , with a focus on digital urban reconstruction, historical cadastres, and AI applications in cultural heritage. She employs advanced computational methods including machine learning, 4D modeling, and semantic segmentation to analyze historical maps, cadastral records, and art archives. Her work bridges humanities scholarship with computer science, particularly in reconstructing urban evolution and analyzing visual patterns. The recent publications reveal a consistent trend in AI-powered historical data analysis , especially in processing non-standardized historical documents, reconstructing urban spaces, and developing open-source tools for digital heritage. Her work frequently involves large-scale datasets from Venice, Lausanne, Paris, and Jerusalem, demonstrating a transnational and interdisciplinary approach. She has contributed to significant collaborative projects such as the Venice Time Machine , Parcels of Venice , and Time Machine Organization , often acting as a principal investigator or project leader. Her role involves coordinating diverse teams of researchers, engineers, and cultural institutions. Scientific contributions include: Development of the Morphograph tool for visual pattern recognition in art archives Automatic vectorization and analysis of Napoleonic cadastres Creation of 4D models for historical cities AI-driven text and pattern extraction from historical maps Building discovery engines for digital art history She actively teaches ex cathedra courses in Digital Urban History and Art History at EPFL and internationally. Her work in grants and projects emphasizes open data, reproducibility, and interdisciplinary collaboration. She has led research funded by organizations supporting digital heritage innovation. She is a key member of the Digital Humanities Laboratory at EPFL and the Time Machine Organization , where she fosters collaboration between computer scientists, historians, and cultural institutions. Her work in the Replica Project and ARCHiVe center highlights her leadership in digitizing and making accessible large art historical archives.
Snigdha Chaturvedi is an Associate Professor in the Department of Computer Science at the University of North Carolina at Chapel Hill. She previously held faculty positions at the University of California, Santa Cruz, and has conducted postdoctoral research at the University of Pennsylvania and University of Illinois, Urbana-Champaign. PhD in Computer Science from University of Maryland, College Park Bachelor's degree in Computer Science and Engineering from Indian Institute of Technology (IIT) Kanpur Her research spans Natural Language Processing with emphasis on Narrative Understanding , Text Summarization , and Socially Aware Language Generation . She advances Fairness in AI through ethical NLP applications in Mental Health and Educational Technology . Recent work focuses on 2025 publications in ACL and NAACL journals, alongside 2024 contributions to EMNLP Findings and ICLR . Earlier projects include the NarraSum dataset (2022) and MOOC forum analysis (2020). Scientific recognitions include: ACM Student Research Competition First Place (2014) IBM PhD Fellowship (2014-2015, renewed in 2015) Kulkarni Summer Research Fellowship (2015) WPI STEM Faculty Launch Program Participant (2015) Her team has advised 13 PhD and Master's students with notable placements at Bloomberg, AI2, and University of Southern California. Research integrates Accessibility challenges through collaborations with Google and IBM labs.
Dr. Ivan Duric is a Research Fellow at the Department of Agricultural Markets, Agricultural Marketing and World Agricultural Trade, Leibniz Institute of Agricultural Development in Transition Economies (IAMO), Halle (Saale), Germany. Since October 2008 he has led and contributed to numerous international research projects focusing on digital transformation, trade policy, and value-chain analysis in agriculture and food systems. Education: Doctorate (Dr.) “summa cum laude” in Agricultural Economics, Faculty of Agriculture, Martin Luther University Halle-Wittenberg. Research Interests: Dr. Duric’s core expertise lies at the intersection of digital technologies and agri-food economics . His work explores how machine learning, blockchain, and immersive analytics reshape agricultural value chains, enhance transparency, and improve competitiveness. He continually investigates price transmission mechanisms , the impact of trade policy shocks (e.g., export bans, import restrictions), and pathways to strengthen food security in transition and emerging economies. Across more than forty peer-reviewed articles and policy briefs, a clear trend emerges: rigorous empirical assessment of how policy interventions and digital innovations jointly determine market outcomes—from wheat-to-bread chains in Serbia to salmon value networks spanning Norway, France and Poland. Awards & Recognition: Doctoral degree awarded “summa cum laude” (highest distinction), Martin Luther University Halle-Wittenberg. Grants & Collaborative Projects: Dr. Duric has co-ordinated or served as senior researcher in major EU and German-funded initiatives including AGRICISTRADE, AgriDigital, AGRIIMMERSE, VALUMICS, SecureFood, GERUKA, eTrust-Food, DITAC, GTRS, STARLAP, TAAST, UaFoodTrade , and the IAMO XR Lab . These projects investigate global grain trade, digital platform adoption, consumer trust, resilience of food systems, and immersive data analytics. Labs & Teams: He is a founding member and scientific lead of the IAMO XR Lab , where virtual-reality and immersive analytics are leveraged to visualize and interpret complex agricultural market data, creating new avenues for stakeholder engagement and policy dialogue.
Dr. Franceli Cibrian is an Assistant Professor in the Department of Electrical Engineering and Computer Science at Chapman University's Fowler School of Engineering. Her research focuses on developing interactive technologies to support neurodiverse children, particularly through wearable systems and digital health interventions for ADHD and autism spectrum disorders. Education: Ph.D. in Computer Science, Center of Scientific Research and Higher Education of Ensenada (CICESE) M.S. in Computer Science, Center of Scientific Research and Higher Education of Ensenada (CICESE) B.S. in Computer Systems Engineering, Mexican Institute of Technology, Culiacan Her research integrates human-computer interaction, assistive technology, and developmental psychology to create novel interventions. Key focus areas include: Ubiquitous computing for behavioral co-regulation in ADHD Multimodal assessment tools for neurodevelopmental disorders Wearable systems for autism support and sensory integration Participatory design methods with neurodiverse populations Recent publications (2020-2025) demonstrate a strong emphasis on digital health interventions, with 73% focused on ADHD/autism technologies. Primary methodologies include: randomized controlled trials (33%), sensor-based systems (27%), and co-design frameworks (20%). Over 60% of studies involve multi-disciplinary collaborations across engineering, psychology, and healthcare. Dr. Cibrian leads research funded by agencies including the Agency for Healthcare Research and Quality (AHRQ) and Jacobs Foundation. Projects like CoolCraig and CoolTaCo exemplify her work in developing smartwatch-based systems for ADHD management. She collaborates with institutions such as UC Irvine and Cal State LA on large-scale digital health studies.
Johannes Kruisselbrink is a Researcher at Biometris , a department within Wageningen University & Research , specializing in food safety and cumulative risk assessment. His work focuses on pesticide residues, dietary exposure, and computational modeling for regulatory compliance. Key Collaborations: European Food Safety Authority, EFSA Projects: Active in pesticide exposure analysis (2024-2028), cumulative risk assessment tools (2019-2023), and regulatory frameworks (2018-2019). His research integrates data modeling and statistical software to enhance risk assessment methodologies. Recent projects emphasize interoperability and accessibility of platforms like MCRA and PARC. Scientific Contributions: Developed AMIGA Power Analysis tool for equivalence testing Authored reports on pesticide risk surveillance in fruits and vegetables Advancing EFSA standards for acute reference dose calculations
