Shirin Saeedi Bidokhti is an Assistant Professor at the University of Pennsylvania's School of Engineering and Applied Science with primary appointment in Electrical and Systems Engineering and secondary appointment in Computer and Information Science. She is affiliated with the Warren Center for Network and Data Sciences. She holds M.Sc. and Ph.D. degrees from EPFL and completed postdoctoral work at Stanford and Technical University of Munich. Her research focuses on information theory, networking, data compression, and machine learning. Her recent publications demonstrate strong emphasis on neural compression algorithms, network optimization during the COVID-19 pandemic, and age-of-information theory. Awards include: 2023 IEEE Communications Society & Information Theory Society Joint Paper Award 2021 NSF CAREER Award 2019 NSF-CRII Award Swiss National Science Foundation Fellowships She advises PhD students including Xingran Chen. Current research involves developing data compression algorithms for IoT applications and network strategies for pandemic response.
Michio Honda is an Associate Professor (Reader) at the School of Informatics , University of Edinburgh , specializing in computer networking and operating systems . His research focuses on network stack designs, including co-design of networking and storage systems, and transport scale-out architectures. He has contributed to foundational work such as identifying TCP extensibility challenges (IMC'11) and pioneering TCP/IP stacks for persistent memory (NSDI'18). Research Trends : His 15 most recent works emphasize systems research, with keywords spanning Networking , Operating Systems , and High-Performance Computing . Sub-fields include TCP Protocol Design , Persistent Memory Optimization , and Network Scalability . Awards : Notable honors include the ISOC/IRTF Applied Networking Research Prize (2011), Facebook Research Award (2021), and Google Research Scholar Award (2022). Grants & Collaborations : Current projects involve network/storage co-design (HotNets'21) and transport scale-out (NSDI'21), often in collaboration with institutions like VMWare and Google.
Dr. John Glen is a Visiting Professor at the Cranfield School of Management, Cranfield University. He previously served as Director of the Executive MBA (2002–2004) and Full-Time MBA (2004–2007). His research focuses on housing economics, health economics, and macroeconomics, with notable work on mortgage arrears, property valuation impacts of school performance, and waste management economics. He regularly comments on UK and global macroeconomics and football finance for BBC media, having provided over 75 interviews in three years. Education : Not explicitly listed, but affiliated with Cranfield School of Management. Research Interests : Housing economics, health economics, macroeconomic trends, and sports finance. He employs econometric models to analyze policy impacts on markets, such as school performance on property prices and mortgage default risks. His articles span topics like waste incineration valuation, breast cancer treatment costs, and mortgage arrears determinants. He has advised major clients including Kuehne + Nagel, Jaguar Land Rover, and government entities in Dubai and Abu Dhabi. No awards are listed, but his work has been cited in over 10 studies on mortgage arrears and credit risk. Labs/Teams: Not explicitly mentioned, but collaborates with institutions like the Council of Mortgage Lenders and co-authored studies with Catarina Figueira and Joseph Nellis.
Nancy Kass is a Professor in the Department of Health Policy and Management at the Johns Hopkins Bloomberg School of Public Health, where she also holds the Phoebe R. Berman Professorship in Bioethics and Public Health. She serves as Vice Provost for Graduate and Professional Education at Johns Hopkins University and is the Interim Chair of the Department of Health Policy and Management. Additionally, she is Deputy Director for Public Health at the Johns Hopkins Berman Institute of Bioethics and co-directs the Johns Hopkins Fogarty African Bioethics Training Program. ScD, Johns Hopkins University, 1989 BA, Stanford University Postdoctoral Fellowship, Kennedy Institute of Ethics, Georgetown University Dr. Kass’s research focuses on the ethical dimensions of public health policy and research, with particular expertise in bioethics, research ethics, public health ethics, informed consent, learning health systems, and global health ethics . Her work addresses ethical challenges in HIV/AIDS, obesity prevention, genetics, and international research. She has developed influential frameworks for ethical oversight in public health and clinical research. Her recent publications (2024–2025) reflect a strong focus on modernizing clinical research ethics, including optimizing informed consent, integrating clinical trials with medical practice, and enhancing data infrastructure. These works emphasize ethical governance, patient-centered decision-making, and the alignment of research with real-world healthcare delivery. Her scholarship spans high-impact journals such as JAMA and Implementation Science , demonstrating sustained scholarly leadership. GBFFR Annual Award, Global Forum on Bioethics in Research, 2016 Member, National Academy of Medicine (formerly Institute of Medicine), 2008 Fellow, Hastings Center, 2007 Delta Omega Honorary Society in Public Health, 1996 AMTRA (Advising, Mentoring, and Teaching Award), Johns Hopkins, 1996 Dr. Kass has played a pivotal role in education and mentorship, having directed the PhD program in Bioethics and Health Policy for 15 years. She currently leads the Fogarty-funded African Bioethics Training Program, advancing global bioethics capacity. She has served on numerous national and international advisory bodies, including the National Cancer Institute’s central IRB, the National Academy of Medicine, and the WHO Ethics Review Committee. Her leadership extends to chairing the national Precision Medicine Initiative central IRB. She is actively involved in research projects such as the CDC Informed Consent Project, Bioethics of Quality Improvement, and Demonstrating Respect and Acceptable Consent Strategies in patient-centered outcomes research. These initiatives underscore her commitment to ethical innovation in public health and clinical practice.
Olof Bälter is a Professor in Computer Science at KTH Royal Institute of Technology, affiliated with the Division of Media Technology and Interaction Design within the School of Electrical Engineering and Computer Science. He is the founder of the Technology-Enhanced Learning research group and holds a focus on learning engineering and human-computer interaction. His research interests center on technology-enhanced learning , question-based learning , learning analytics , AI in education , and inclusive pedagogy . A consistent theme in his work is improving efficiency in education and daily life through digital tools. He developed the Pure Question-Based Learning (Pure QBL) methodology, a digital Socratic approach that enhances student engagement and learning outcomes. His work extends to wellness in education through initiatives like walking seminars, and he investigates digital interventions for mental health, such as online Cognitive Behavioral Therapy (CBT) courses. His recent publications highlight trends in AI-generated educational content , learning efficiency , digital pedagogy , and inclusive course design , with applications in computer science education, language instruction, and global development. His research often employs experimental and data-driven methods, including randomized controlled trials and learning analytics. Teacher of the Year at the Surveying program KTH's Pedagogical Prize Higher Education Hero STINT Excellence in Teaching Scholarship (2008 and 2013) Olof Bälter has supervised numerous courses in programming, computer science, media technology, and learning engineering. He has collaborated with institutions such as Stanford University, Williams College, Region Stockholm, Stockholm University, and organizations like Promobilia and Begripsam. His projects aim to scale effective learning methods globally and make education more accessible and efficient. He leads research on the effectiveness of Pure QBL for students with ADHD and is involved in developing digital tools for health literacy and professional development in Ethiopia and Rwanda. His work bridges theory and practice, aiming to transform educational delivery through innovation and evidence-based design.
Norman Sadeh is a Professor in the School of Computer Science at Carnegie Mellon University (CMU), where he has made significant contributions to cybersecurity, privacy, and AI research. He has co-founded and co-directed several groundbreaking graduate programs at CMU, including the Privacy Engineering Program (2012-present), the Ph.D. Program in Societal Computing (2003-2013), and the MBA track in Technology Strategy and Product Management (2005-2017). Carnegie Mellon University, School of Computer Science Software and Societal Systems Department CyLab Security and Privacy Institute Manufacturing Futures Institute Dr. Sadeh received his Ph.D. in Computer Science at CMU with a major in Artificial Intelligence and a minor in Operations Research. He holds an M.Sc. in computer science from the University of Southern California and a BS/MS degree in electrical engineering and applied physics from the Free University of Brussels (Belgium) as 'Ingénieur Civil Physicien.' Professor Sadeh's research spans cybersecurity, online privacy, Human-AI Interaction, AI governance, mobile computing, the Internet of Things, user-oriented machine learning, and language technologies. He is particularly known for his pioneering work on AI-based privacy enhancing technologies, including privacy assistants, automated privacy compliance tools, and NLP-based privacy solutions. His work has influenced the design of privacy features at major technology companies including Apple, Google, and Facebook/Meta, as well as privacy policies at regulatory agencies like the Federal Trade Commission and the California Office of the Attorney General. Analysis of his recent publications shows a strong focus on practical privacy solutions, particularly in mobile and IoT contexts, with an emphasis on making privacy more usable and understandable for end users. His work bridges technical innovation with policy implications, addressing both the technological and human aspects of privacy protection. 2018 Outstanding Entrepreneur of the Year award from the Pittsburgh Venture Capital Association Test of time award by the AAAI Conference on Web and Social Media (ICWSM) Gartner Group's Magic Quadrant leader in Security Awareness Computer-Based Training for 4 consecutive years Deloitte's Technology Fast 500 recognition for 3 consecutive years Professor Sadeh has advised numerous students, including PhD candidates like Aerin (Shikhun) Zhang, whose dissertation focused on understanding diverse privacy attitudes. His research has been funded through various grants, including NSF SaTC projects, and has resulted in technologies that protect tens of millions of users worldwide. He also founded Wombat Security Technologies, which was acquired by Proofpoint in 2018 and whose technologies are used by over 75% of Fortune 100 companies. Professor Sadeh leads several research initiatives including the Privacy Engineering Program, the Usable Privacy Policy Project, the Personalized Privacy Assistant Project, and CMU's Privacy Infrastructure for the Internet of Things. His Mobile Commerce Lab and E-Supply Chain Management Lab have produced influential research that has been commercialized by major organizations including IBM, Raytheon, Boeing, and the U.S. Army.
Aman Arora is an Assistant Professor at Arizona State University's Ira A. Fulton Schools of Engineering, specializing in the School of Computing and Augmented Intelligence. His research focuses on reconfigurable computing, hardware acceleration of machine learning, and non-traditional computing paradigms like Processing-In-Memory. With over a decade of semiconductor industry experience, he bridges academic research and industrial applications. PhD in Computer Science from The University of Texas at Austin Research interests emphasize domain-specific acceleration through FPGA optimization , compute-in-memory architectures , and machine learning for CAD/EDA . His work addresses critical challenges in energy efficiency and throughput for AI workloads. Recent publications demonstrate trends toward compute-in-memory systems , FPGA-based deep learning acceleration , and sustainable hardware design . Key contributions include frameworks like SAF, CSR, and GAMA for dynamic hardware optimization. Laboratory Website: ADVENT Lab Teaching includes courses on digital hardware design (CSE 320) and advanced topics in machine learning acceleration (CEN 524/CSE 524). Industry experience informs his practical approach to research and education.
Andrea Carminati is a Full Professor at the Department of Environmental Systems Science, ETH Zurich. His research focuses on soil-plant hydraulics , rhizosphere dynamics , and drought adaptation mechanisms in crops and forest species. He investigates how root traits , soil texture , and biogenic substances like mucilage influence water uptake , gas exchange , and soil microbial activity . Key Research Areas: Soil-Plant Water Relations Rhizosphere Hydrology Drought Resistance in Maize and Trees Microplastics in Agricultural Soils Hydraulic Redistribution and Isohydricity Contact: Email: andrea.carminati@usys.ethz.ch Phone: +41 44 633 61 60 Recent studies highlight his work on soil texture-specific transpiration responses , rhizosheath properties under drought , and microplastic impacts on soil hydrology . He employs advanced techniques like X-ray computed tomography and neutron radiography to visualize root-soil interactions.
Doç. Dr. Muhammed Aras is an Associate Professor in the Department of Mechanical Engineering at Baskent University (Başkent Üniversitesi), with a research focus on sustainable machining processes, tool wear monitoring, and surface roughness optimization. His work spans advanced manufacturing technologies, energy storage systems, and biomedical device design. PhD in Manufacturing Engineering (2018), Gazi Üniversitesi MSc in Mechanical Education (2013), Gazi Üniversitesi BSc in Mechanical Engineering (2010), Tabriz Islamic Azad University Research interests include sustainable machining (dry/hard turning, cooling-lubrication strategies), tool wear analysis (CBN, ceramic and coated inserts), and surface integrity optimization using AI-based methods (firefly algorithm, TOPSIS, Grey Relational Analysis). His 15 most recent articles (2017-2024) examine topics like: Surface roughness prediction in dry hard turning Energy storage technology viability assessments Cutting parameter optimization for various steels Acoustic/vibration monitoring in machining He has received scientific awards including the Teşvik Ödülü (Encouragement Award, 2015). His patent on an automatic orthognathic surgery articulator and book chapters on tool monitoring systems demonstrate his multidisciplinary impact.
Alison Galvani is the Burnett and Stender Families Professor of Epidemiology at Yale School of Public Health and Yale School of Medicine, where she serves as founding director of the Center for Infectious Disease Modeling and Analysis (CIDMA). Her interdisciplinary work bridges epidemiology, evolutionary ecology, and health economics to inform public health policies for diseases including HIV, Ebola, influenza, and COVID-19. Her research focuses on optimizing vaccination strategies and healthcare interventions through mathematical modeling. Recent studies examine SARS-CoV-2 transmission dynamics, RSV vaccine impact, and integration of social determinants into infectious disease models. She has pioneered frameworks for conflict-induced migration analysis and pharmaceutical policy evaluations. Notable scientific awards include the Bellman Prize, Blavatnik Award for Young Scientists, and Guggenheim Fellowship. Her publications span top journals like The Lancet , Nature Communications , and PNAS , with media coverage in major outlets and policy references.
Ayse Coskun is a Professor in the Electrical and Computer Engineering Department at Boston University's College of Engineering. She serves as Director of the Center for Information and Systems Engineering (CISE) and as interim Associate Dean for Research and Faculty Development. Her research focuses on the intersection of computer systems, energy efficiency, and AI. Dr. Coskun received her PhD from the University of California, San Diego in 2009. Prior to joining academia, she worked at Sun Microsystems (now Oracle). Her research spans energy-efficient computing, cloud computing, high performance computing, computer architecture, and embedded systems, with recent work focusing on AI's impact on data center energy demands. Her publication record shows consistent innovation across multiple domains, with recent work emphasizing AI applications for improving cloud security (through frameworks like DeltaSherlock and Praxi) and transforming data centers into grid-responsive assets (Emerald AI project). Her research bridges theoretical advances with practical applications, resulting in tools adopted by industry partners including IBM. IBM Faculty Award (2020) Ernest S. Kuh Early Career Award (2017) NSF CAREER Award (2012-2017) Multiple best paper and artifact awards at top conferences As an educator, Dr. Coskun teaches courses including EC327 Introduction to Software Engineering, EC535 Introduction to Embedded Systems, and EC713 Advanced Computing Systems and Architecture. She has advised numerous PhD students including Mert Toslali, Anthony Byrne, and Burak Aksar. Her lab maintains strong industry partnerships with IBM, Intel, AMD, and Oracle, and collaborates with academic institutions worldwide including Brown University, MIT, EPFL, and CEA-Tech in France. Dr. Coskun leads the Coskun Lab, which secured a $500K grant from Sandia National Labs for AI-based analytics in high performance computing systems, demonstrating the practical impact of her research on critical computing infrastructure.
Prof. Sadettin Emre Alptekin is a full Professor of Industrial Engineering at Galatasaray University, Faculty of Engineering and Technology, where he also serves as Vice Dean. Since joining the university as a research assistant in 2000, he has steadily advanced through the academic ranks, becoming an Assistant Professor (2006–2010), Associate Professor (2010–2023), and finally Professor in 2023. Education: PhD (Dr), Industrial Engineering, Istanbul Technical University, Institute of Science and Technology, 2001–2006 MSc, Industrial Engineering, Galatasaray University, Faculty of Engineering and Technology, 1999–2001 BSc, Industrial Engineering, Istanbul Technical University, Faculty of Management, 1995–1999 Languages: Advanced English (C1), Upper-Intermediate French (B2), Advanced German (C1) Research Interests: Prof. Alptekin’s research focuses on Computer Learning , Fuzzy Sets and Systems , and Decision Support Systems . His work integrates artificial intelligence, machine learning, and soft-computing techniques to solve complex industrial and managerial problems in areas such as supply chain management, quality function deployment, blockchain adoption, and mental-health prediction. Publication Trends: Across more than 50 refereed publications, Prof. Alptekin has consistently explored hybrid intelligent models that combine fuzzy logic, machine learning, and multi-criteria decision-making. Recent articles emphasize deep-learning-based anomaly detection in industrial time-series data, blockchain adoption in supply chains, and machine-learning applications in subjective well-being and mental-health modeling. Scientific Awards & Honors: No specific awards or medals are listed in the provided documents. Research Leadership & Funding: Since 2008 he has been the principal investigator (executive) of 12 nationally funded projects, covering topics such as Industry 4.0 sub-system design, Internet of Things applications, artificial neural networks in organizational decision-making, big-data analytics, and strategic decision processes. Graduate Advising: He has formally supervised at least 8 master’s theses and numerous undergraduate projects. Representative thesis titles include Gaussian-process-regression-based man-hour prediction, machine-learning-driven human-behavior modeling, recommender-system design for e-commerce, thyroid-nodule diagnosis from scintigraphic images, software-effort estimation via neural networks, spreadsheet heuristics for joint-replenishment problems, cross-selling decision systems in insurance, and profitability analyses of Turkish banks under disinflation. Laboratories & Teams: While no dedicated laboratory name is disclosed, his continuous role as Vice Dean and principal investigator implies active leadership of the Industrial Engineering department’s research clusters in intelligent systems and decision support technologies.
Ion Stoica is a Professor in the Electrical Engineering and Computer Sciences Department at the University of California, Berkeley, where he holds the Xu Bao Chancellor Chair. He serves as Director of the Sky Computing Lab and is Executive Chairman of both Databricks and Anyscale. His research spans distributed systems, cloud computing, and AI systems, with significant contributions to large-scale data processing frameworks. Stoica's research interests focus on the intersection of AI and systems, with emphasis on developing practical implementations that bridge theoretical foundations with real-world deployability. His work addresses fundamental challenges in distributed computing, resource management, and large-scale machine learning systems. Current projects include Ray (a distributed execution framework), vLLM (a high-throughput inference engine for LLMs), Chatbot Arena (an open platform for human preference evaluations), and SkyPilot (a framework for running AI workloads across clouds). His research output demonstrates a consistent trajectory toward more efficient, scalable systems for modern AI workloads, particularly focusing on optimizing inference performance, resource utilization, and cross-cloud deployment. Recent publications reflect growing interest in large language model serving, video generation optimization, and agent-based systems. ACM Fellow SIGOPS Hall of Fame Award (2015) SIGCOMM Test of Time Award (2011) ACM Doctoral Dissertation Award (2001) Member of National Academy of Engineering Honorary Member of the Romanian Academy Stoica has advised an extensive number of doctoral students who have gone on to prominent positions in academia and industry, including assistant professorships at Stanford, MIT, Carnegie Mellon, and other top institutions. He has received significant research funding through his lab activities and startup ventures. His research group has been particularly successful in translating academic research into widely adopted open-source technologies and commercial products. Stoica leads the Sky Computing Lab at UC Berkeley, which focuses on developing systems for AI workloads across multiple clouds. His research group has produced numerous influential open-source projects including Apache Spark, Apache Mesos, and Alluxio, which have become industry standards for large-scale data processing. The lab maintains strong industry partnerships while pursuing fundamental research in distributed systems and AI infrastructure.
Cristian Danescu-Niculescu-Mizil is an Associate Professor at the Department of Information Science , Cornell University . His research focuses on computational frameworks for social behavior analysis through large-scale natural language data , particularly in online communities and crisis counseling contexts. Recipient of WWW Best Paper Award (2013) and Yahoo! Key Scientific Challenges Award Co-developer of ConvoKit , a comprehensive conversational analysis toolkit Principal investigator in NLP for mental health , antisocial behavior detection , and linguistic coordination studies His work spans computational social science and human-centered AI , with recent publications in EMNLP 2025 , ACL 2025 , and CSCW 2025 focusing on conversation dynamics modeling , pivotal moment detection , and talk-time equity analysis . He has advised multiple PhD students who became faculty at Harvey Mudd , University of Michigan , and Thompson Reuters . Key scientific contributions : 2013 : WWW Best Paper - Power dynamics through linguistic coordination 2016 : IJCAI NLP & Journalism Best Paper - Gender bias quantification 2017 : ICWSM Best Paper - Trolling behavior analysis He teaches NLP and Social Interaction (INFO/CS 6742) and Language and Information (INFO/CS 4300) , with teaching resources including the Politeness Web App and ConvoWizard interactive tool featured in NPR's Weekend Edition . His work has been covered by New Scientist , NBC Today Show , and New York Times .
Christopher Lawson is an Assistant Professor in the Department of Chemical Engineering and Applied Chemistry at the University of Toronto, affiliated with the Faculty of Applied Science and Engineering. He serves as Principal Investigator of the Microbiome Engineering Lab and is part of BioZone – the Centre for Applied Bioscience and Bioengineering. His research focuses on engineering anaerobic microbiomes for resource recovery from waste streams using systems biology, synthetic biology, and machine learning approaches. B.A.Sc., M.A.Sc. (University of British Columbia) Ph.D. (University of Wisconsin-Madison) Postdoctoral Training (Berkeley Lab) Lawson's work addresses the challenge of controlling complex microbial interactions in engineered systems to enable scalable biotechnologies for renewable energy, chemicals, and materials. His lab develops high-throughput methods integrating automation and computational tools to optimize microbiome assembly and metabolic fluxes. Recent publications highlight advancements in metabolic modeling , isotope tracing , and systems-level analysis of anaerobic microbiomes, with applications in wastewater treatment , anammox granules , and bioenergy production . His research bridges fundamental microbiology with industrial-scale bioprocess engineering. Scientific Awards ISME/IWA BioCluster Rising Star Award (2022) Jacobs Engineering Group/AEESP Outstanding Doctoral Dissertation Award (2020) Wesley Eckenfelder Graduate Research Award (2019) WEF Canham Graduate Studies Scholarship (2018) NSERC Post-Graduate Scholarship – Doctoral (2014) Lawson actively mentors students and postdocs, emphasizing technical rigor, communication skills, and independence. His lab collaborates within BioZone and with industry partners to advance "team science" principles. Current projects focus on creating engineered microbiomes for commercial-scale waste valorization.
