Elias Passerini is a Researcher at the Institute of Electromagnetic Fields (IEF), ETH Zürich, part of the Department of Information Technology and Electrical Engineering. His work focuses on memristive devices and their applications in neuromorphic computing, photonics, and nanoelectronics. He completed his doctoral thesis on 'Memristors for Neuromorphic Computing' in 2025, exploring volatility control and synaptic response tuning. His research emphasizes atomic-scale memristive systems, three-terminal architectures, and material innovations like Sn alloying for improved device stability. Key contributions include developing versatile nanoscale memristive switches with gate tuning capabilities and demonstrating metamaterial graphene photodetectors with record-breaking bandwidth. Passerini collaborates with the Center for Single-Atom Electronics and Photonics, advancing low-power neuromorphic hardware and optoelectronic integration. His publications span conferences like MEMRISYS and journals such as ACS Nano and Light: Science & Applications .
Aaron J. Elmore is an Associate Professor in the Department of Computer Science and the College of the University of Chicago. His research focuses on cloud computing, databases, and distributed systems, with an emphasis on resource-efficient database execution and collaborative analytics. PhD in Computer Science from University of California, Santa Barbara MS in Computer Science from University of Chicago Research interests include: Elastic databases and multitenancy (Database-as-a-Service) Resource-efficient systems (CrocodileDB, DenseStore, EdgeTSD) Database versioning (Datahub, Decible, OrpheusDB) Data discovery (DataSwamp, Relic) Recent publications highlight advancements in cloud-native query execution, dynamic compression frameworks, and time-series anomaly detection. His work often bridges systems design with practical data science applications. Scientific awards include: NSF CAREER Award (2021) Multiple Google and Intel research grants ACM SIGMOD Best Demo Honorable Mention Aaron has advised multiple PhD students including Jun Hyuk Chang and Riki Otaki, with former advisees now at institutions like MIT, Harvard, and UC Berkeley. He leads the ChiDATA research group and collaborates with Systems Group and CERES Center.
Henry Hoffmann is a Professor and Liew Family Chair in the Department of Computer Science at the University of Chicago. His research focuses on self-aware computing systems that adapt to meet goals like power efficiency, performance, and security. He leads the SEEC project and has contributed to advancements in computer architecture, embedded systems, and quantum computing. Hoffmann received the PECASE (2019), DOE Early Career Award (2015), and was inducted into the Samsung Hall of Fame for discovering vulnerabilities in SmartTVs. He holds a PhD from MIT (2013) and has co-founded Config Dynamics (2019). His work bridges control theory, machine learning, and traditional computer systems to create adaptive solutions for modern computing challenges. Education: PhD in Electrical Engineering and Computer Science from MIT (2013), SM (2003), and B.S. (1999) with highest honors from UNC Chapel Hill. Professional experience includes roles at Tilera Corporation and MIT Lincoln Laboratory. Research Interests: Self-aware systems, adaptive resource management, quantum computing optimization, and cybersecurity. His SEEC framework enables systems to autonomously adapt to constraints like energy and performance. Recent work explores applying adaptive techniques to AI/ML models for energy-efficient inference and security. Awards: Over $19M in research funding, 100+ publications, and leadership roles in NSF Expedition EPiQC (quantum computing). Named Chair of UChicago CS Department (2023-2024). Labs/Teams: Systems Group, EPiQC (quantum computing), and CERES (unstoppable computing systems). Current students include Jerry Ding and Ryien Hosseini. Notable alumni include Yi Ding (now faculty at Purdue) and Nikita Mishra.
Dr. Srinivas Peeta is the Frederick R. Dickerson Chair and Professor in Transportation Systems Engineering at the Georgia Institute of Technology’s School of Civil and Environmental Engineering. He previously held the Jack and Kay Hockema Professorship at Purdue University, where he served for 24 years. He is also the Associate Director of the USDOT Center for Connected and Automated Transportation. Education: B. Tech. from IIT Madras, M.S. from Caltech, and Ph.D. from UT Austin, all in Civil Engineering. His research focuses on large-scale transportation systems, infrastructure interdependencies, and connected/automated vehicles. He has authored over 345 publications and secured over $48M in research funding. Research Interests: Dynamic traffic networks and driver behavior modeling Information-based navigation in vehicular systems Systems perspectives for complex adaptive infrastructure Autonomous vehicle integration and human-vehicle interactions Key Achievements: Developed DYNASMART software for traffic operations Recipient of NSF CAREER Award (1997) and ASCE Walter Huber Prize (2009) Directed NEXTRANS UTC and pioneered USDOT’s real-time route guidance systems Grants & Outreach: Secured funding from USDOT, NSF, FHWA, and international agencies Initiated NEXTRANS internship programs and K-12 outreach Labs/Teams: Active in Georgia Tech’s ACT Lab, focusing on autonomous transportation systems and human-vehicle-environment interactions.
Dr. Suresh Bhargava is a Distinguished Professor and Director of AcSIR at RMIT University's Research & Innovation department. He has led interdisciplinary research in materials science, catalysis, and environmental engineering for over three decades, with a focus on strengthening Indo-Australian scientific collaboration. His work bridges academia and industry, addressing challenges in pollution control, nanotechnology, and cancer treatment. Research & Leadership: Established RMIT's Centre for Advanced Materials and Industrial Chemistry (CAMIC), pioneering translational research with industry applications. Supervised 70+ PhD students (100% employment rate), many now leading roles at global institutions. Holds distinguished professorships across six countries and advises governments and Fortune 500 firms on environmental and industrial issues. Awards & Recognition: Recipient of Australia's Member of the Order of Australia (2022), India's P.C. Ray Chair (2014), and the Khwarizmi International Award (2016). His work on mercury pollution control and gold-based anticancer drugs has garnered global acclaim, with over 800 publications (26,000+ citations, h-index 86). Key Contributions: Architect of the Australia-India Strategic Research Fund and the RMIT-AcSIR Joint Research Program. Innovated eco-friendly graphene production from eucalyptus bark and patented anti-cancer gold compounds. Advises on sustainable mineral processing, hydrogen energy, and CO₂ valorization. Industry Engagement: Consulted for Rio Tinto, BHP Billiton, and CSIRO on resource efficiency, pollution mitigation, and nanotechnology applications. His research has created jobs and driven innovation in Australia and Asia-Pacific.
Ana Damjanovic is an Assistant Research Professor in the Thomas C. Jenkins Department of Biophysics at Johns Hopkins University (JHU), affiliated with the Zanvyl Krieger School of Arts & Sciences. Her research focuses on ion channels, protein and membrane electrostatics, and computational biophysics. She holds a Ph.D. in Physics from the University of Illinois at Urbana-Champaign, where she studied quantum physics of photosynthetic light harvesting under Prof. Klaus Schulten. Subsequent postdoctoral research included work on photosynthesis with Prof. Graham Fleming at UC Berkeley, and molecular dynamics studies of protein ionization at JHU. Her current lab investigates ion channel mechanisms, protonation dynamics, and electrostatic effects in biological systems using advanced computational tools. Group members include graduate student Nauman Sultan (co-supervised with NIH's Bernard Brooks) and undergraduates Marianne Ri and Vivek Booshan. Past advisees include Ada Chen (now a NIH postdoc) and Maggie Li. Key research contributions include developing pH replica exchange methods, protein pKa prediction using machine learning, and structural-functional studies of voltage-gated sodium channels. Her work has been published in high-impact journals like Proceedings of the National Academy of Sciences and Biophysical Journal . Lab affiliations include the Computational Biophysics Group at JHU, with access to cutting-edge simulation techniques and experimental validation platforms. Ongoing projects explore ion channel selectivity, membrane protein dynamics, and computational modeling of protonation-dependent phenomena.
Professor Shaomin Wu is a faculty member at the University of Kent's Kent Business School, where he holds the academic rank of Professor of Business/Applied Statistics. He earned an MSc and PhD in applied statistics and has extensive industry experience, including a five-and-a-half-year stint at a global manufacturer in Shanghai before moving to the UK in 2001. He has held roles as a postdoctoral researcher and lecturer before joining Cranfield University and later the University of Kent. His research focuses on recurrent event data analysis, machine learning, and reliability mathematics, with funding from the EPSRC and ESRC. His research projects include managing risk in warranty servicing policies, smart data analytics for local government, and sustainable supply chain demand forecasting. He teaches modules such as risk analysis, reliability engineering, and machine learning. Currently supervising PhD students in time series forecasting, explainable AI, and recurrent event data analysis, he also serves as a co-chair of international conferences, editorial board member, and external examiner for doctoral degrees. Notably, he ranks among the top 2% of global scientists by Stanford University. His work integrates machine learning with business analytics, resilience engineering, and environmental sustainability. Key contributions include IoT-driven resilience methodologies for smart grids and unmanned systems, as well as frameworks for corporate carbon disclosure and maintenance optimization under uncertainty.
Javad Dargahi is a Professor of Mechanical, Industrial and Aerospace Engineering at Concordia University, Montreal. His research focuses on haptic sensors, robotic systems for minimally invasive surgery, and smart sensor fabrication using micromachining and piezoelectric polymers. He leads projects in teletaction, embedded force sensing for soft robots, and medical device innovation. Research interests include tactile sensor design for robots and endoscopes, nonlinear impedance matching in surgical robotics, and deep learning-driven force estimation for catheters. His work bridges mechanical engineering with biomedical applications, emphasizing safety and precision in interventional surgeries. Recent publications explore multitask neural architectures for intracardiac catheters, real-time force control algorithms, and biomimetic soft robotics. His lab develops miniature optical sensors and stiffness-adaptive systems for surgical tools, with applications in cardiac ablation and vascular navigation.
Jeffrey P. Bigham is an Associate Professor at the Human-Computer Interaction Institute within the School of Computer Science at Carnegie Mellon University . His research spans human-computer interaction , human-AI interaction , accessibility , dialog systems , NLP , and crowdsourcing . Current PhD Students: Hamza El Alaoui, Jessica Yin Huynh, Sara Kingsley, Peya Mowar, Yi-Hao Peng, Atieh Taheri PhD Graduates: Erin Brady, Yu Zhong, Ting-Hao Huang, Anhong Guo, Cole Gleason, Prakhar Gupta, Stephanie Valencia, Kundan Krishna, Jason Wu His work is funded by Apple , Bosch , DARPA , Google , Microsoft , the National Institute of Disability Rehabilitation Research , the National Science Foundation , and Yahoo! He also holds a CMU HCII Career Development Fellowship . Selected Awards: NSF CAREER Award 2019 Best Paper at ASSETS 2021 Best Paper Nomination at CHI 2024 Best Paper Nomination at CHI 2021 Best Paper Nomination at DIS 2021
Benjamin Andrew Toll is a Professor in the Department of Public Health Sciences and Psychiatry at the Medical University of South Carolina (MUSC) College of Medicine. He serves as Associate Director of Education and Training for the Hollings Cancer Center, Vice Chair of Research in the Department of Public Health Sciences, Co-Director of the Lung Cancer Screening Program, and Director of the Tobacco Treatment Program at MUSC. Dr. Toll received his BA from Cornell University (1996), MS and PhD from Nova Southeastern University (1999, 2002), and completed his Postdoctoral Fellowship and Internship at Yale University. Dr. Toll is a leading researcher in tobacco cessation, with over 20 years of experience conducting clinical trials focused on developing novel therapeutics for tobacco and nicotine use. His work primarily centers on preventing cancer through tobacco treatment interventions, with particular emphasis on lung cancer screening patients and cancer surgery patients. He has expertise in nicotine replacement therapy, contingency management approaches, gain-framed messaging, and digital health interventions for smoking cessation across diverse populations including older adults and young adults. His recent publications demonstrate a strong focus on implementation science for tobacco treatment programs across various healthcare settings including hospitals, oncology clinics, and primary care. His research examines barriers to treatment, optimal delivery methods (including telehealth and EHR-integrated tools), and effectiveness of various pharmacological and behavioral interventions for smoking cessation. National Cancer Institute funding (R01CA235697, R01CA207229, P50CA196530) National Institute on Drug Abuse funding (P50DA036151, K12DA000167) Continuous funding for over 15 years for tobacco cessation research As a mentor and leader, Dr. Toll oversees the Education and Training program at the Hollings Cancer Center, guiding the development of future cancer researchers. His Tobacco Treatment Program serves as a model for integrating tobacco cessation into comprehensive cancer care, and he has successfully implemented 'opt-out' tobacco treatment programs across multiple hospital systems in South Carolina. Dr. Toll leads a multidisciplinary research team focused on tobacco treatment, including psychologists, pharmacists, physicians, and implementation scientists working together to develop and test innovative approaches to smoking cessation for high-risk populations.
Dr. Gary Brewer is a Professor in the Department of Entomology at the University of Nebraska-Lincoln, with a 60% research and 40% teaching appointment. He has served as department head at NDSU (1997-2006) and UNL (2006-2018). His research focuses on field crops entomology, IPM of pasture cattle flies, salt creek tiger beetle conservation, and pollinator health. He has pioneered a push-pull strategy using coconut oil-derived repellents and led curriculum design for Rwanda’s Conservation Agriculture program. Education: B.S. in Zoology, University of Nebraska-Lincoln (1974) M.S. in Entomology, University of Nebraska-Lincoln (1978) Ph.D. in Entomology, Kansas State University (1984) Research Interests: Brewer’s work spans insect ecology, pest management, and conservation. Key areas include stable fly and horn fly control, pollinator protection, and endangered species recovery (e.g., Salt Creek tiger beetle). His lab develops natural product-based pest repellents and evaluates biopesticides for sustainable agriculture. Grants & Contributions: $362,150 USDA grant for undergraduate research in beneficial insect protection (2018) $325,000 USDA grant for multi-tactic stable fly control (2017) NE Game and Parks funded salt creek tiger beetle reintroduction programs Labs & Teams: Brewer’s team collaborates with industry (e.g., Vestergaard Frandsen) and international partners to advance IPM strategies. His work bridges field research with applied solutions for farmers and conservationists.
Dr. Appala Raju Badireddy is an Associate Professor in the Department of Civil and Environmental Engineering at the University of Vermont (UVM), and Director of the Water Treatment & Environmental Nanotechnology (WTEN) Laboratory. He is also co-founder and CTO of Secure Surgical Solutions LLC, and a founding member of Vermont Initiative for Biological and Environmental Surveillance (VIBES). His research focuses on sustainable membrane processes, environmental nanotechnology, nanometrology, and water security. Education: Ph.D., Environmental Engineering, University of Houston (2003-2009) M.Tech., Chemical Engineering, Indian Institute of Technology Madras (2001-2003) B.Tech., Chemical Engineering, Jawaharlal Nehru Technological University Hyderabad (1997-2001) Postdoctoral Research, Duke University (2009-2014) under Prof. Mark Wiesner Research Interests: Sustainable Membrane Processes: Water/wastewater treatment, desalination, anti-fouling strategies, and resource recovery. Environmental Nanotechnology: Nano-enabled sensors, remediation, and implications of nanomaterials in ecosystems. Environmental Chemodynamics: PFAS fate/transport, nutrient cycling, and contaminant toxicity. Water Security: Real-time monitoring systems and soil health assessments. His work integrates lab-scale innovations with field applications, emphasizing interdisciplinary collaboration. Recent Research Trends: Recent publications highlight advancements in PFAS remediation, electric-field enhanced filtration, and living lab approaches to precision agriculture. He explores nanomaterials for water treatment while addressing their environmental implications through novel detection methods like ED-HSI microscopy. Labs & Initiatives: WTEN Lab: Focuses on nanotechnology-driven water solutions. VIBES: Develops environmental surveillance tools for public health. Secure Surgical Solutions: Applies nanotechnology to medical devices.
Dr. José del R. Millán is a Professor and holds the Linda Steen Norris & Lee Norris Endowed Chair in Neuroengineering at The University of Texas at Austin's Chandra Family Department of Electrical and Computer Engineering. He also serves as a Professor in Dell Medical School's Department of Neurology, a courtesy Professor in Biomedical Engineering, and is affiliated with the Mulva Clinic for the Neurosciences, Institute for Neuroscience, Texas Robotics, and the UT CARE Initiative. His work focuses on brain-machine interfaces (BMI), neuroprosthetics, and translating BMI technologies for individuals with motor/cognitive disabilities and able-bodied users. Education: PhD in Computer Science (1992, Technical University of Catalonia). Previous roles include Defitech Foundation Chair in Brain-Machine Interface at EPFL (Switzerland) and visiting scholar positions at Berkeley, Stanford, and the International Computer Science Institute. Research Interests: Neuroengineering, BMI applications in healthcare and assistive robotics, statistical machine learning for neural signals, and neurorehabilitation. Key contributions include EEG-based BMI systems, closed-loop neurostimulation, and wearable neurotechnology. Awards: IEEE Fellow (2017), Norbert Wiener Award (2011), and Fellow of the International Academy of Medical and Biological Engineering (2020). Grants & Labs: Co-director of UT CARE, leader in clinical neuroprosthetics and neurorobotics. Active in developing BMI-driven wheelchairs, VR integration for BCI, and EEG-based speech prosthetics. Research outputs emphasize translational neurotechnology, with projects funded by industry and governmental agencies. Labs/Teams: Clinical Neuroprosthetics & Brain Interaction Lab, Texas Robotics, Wireless Networking and Communications Group (WNCG).
Hima Lakkaraju is an Assistant Professor at Harvard University with dual appointments in the Harvard Business School and the Department of Computer Science. Her research focuses on trustworthy AI, including machine learning interpretability, fairness, privacy, and safety. She holds a PhD from Stanford University and has received accolades such as the Alfred P. Sloan Fellowship and NSF CAREER Award. Her work bridges algorithmic foundations and societal implications of AI, with applications in healthcare, policy, and business. Education: PhD in Computer Science from Stanford University (2013-2017). Academic background includes roles at IBM Research, Microsoft Research, and Adobe. Research Interests: Algorithmic Foundations of AI Interpretability and Explainable AI Fairness and Bias Mitigation Privacy-Preserving ML Generative Models and LLMs Ethical AI Policy and Regulation Key Achievements: Over 100 publications in top venues like NeurIPS and ICML; co-founder of the Trustworthy ML Initiative; featured in MIT Tech Review, Forbes, and Harvard Business Review. Current projects include the AI4LIFE research group and work on regulatory frameworks for AI. Advising and Grants: Supervises over 30 students across PhD, master's, and postdoc levels. Research supported by NSF, Sloan Foundation, Schmidt Sciences, Google, Amazon, and others. Initiatives include the Regulatable ML workshop and NeurIPS ethics co-chair roles. Labs and Collaborations: Leads Harvard's AI4LIFE group and collaborates with industry partners like Fiddler AI. Active in policy discussions on AI regulation and societal impact.
Prof. Massimo Fornasier holds the Chair of Applied Numerical Analysis at the Technical University of Munich (TUM), within the School of Computation, Information and Technology and the Department of Mathematics. His research focuses on mathematical modeling, numerical analysis, and data-driven methods, particularly in areas like compression, sparse recovery, and optimization. He has made significant contributions to consensus-based optimization, control of multiagent systems, and applications in image/signal processing. Education: PhD in Computational Mathematics, University of Padua (2003) Postdoctoral fellowships at University of Vienna, Sapienza University of Rome, and Princeton University Awards: ERC Starting Grant (2012) START Prize (2011) Prix de Boelpaepe (2009) His work bridges theoretical analysis and computational methods, with applications ranging from compressive sensing to machine learning. Recent research emphasizes consensus-based optimization frameworks and their global convergence properties. Editorial roles include journals like Networks and Heterogeneous Media and Calcolo . He leads research groups in areas such as Data Science and Numerical Analysis at TUM.
