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Stefanos ZeniosView profile

Professor

• Operations Research
• Innovation
• Entrepreneurship
• +3 more

Stefanos Zenios is Professor at Stanford Graduate School of Business with dual appointments in Entrepreneurship and Operations, Information & Technology . He directs Stanford GSB’s Center for Entrepreneurial Studies and co-directs the Doerr School of Sustainability ’s Program in Ecopreneurship. His Startup Garage course has launched companies like DoorDash while alumni have raised over $3B in venture capital. He co-authored the foundational Biodesign textbook and previously served as Editor-in-Chief of Operations Research . PhD, MIT Operations Research (1996) MA, University of Cambridge (1996) BA, University of Cambridge (1992) Research Focus Dr. Zenios’ work bridges operations research and innovation management , with significant contributions to: Healthcare operations : Administrative cost reduction, organ allocation optimization, and clinical workflow improvements Entrepreneurship : Venture creation frameworks and experiential education Ecopreneurship : Sustainable business model innovation His Precedents Thinking framework (HBR 2025) has gained global recognition for solving systemic inefficiencies. Current research includes the biennial Search Fund Study with Peter Kelly. Scientific Recognition INFORMS Fellow Multiple Best Paper Awards, INFORMS CAREER Award, National Science Foundation (2000) Dhirubhai Ambani Faculty Fellow (2017–2020) George E. Nicholson Award (1997) He has received extensive media coverage in Fast Company , Time Magazine , and Stanford Business . His research has been featured in over 150 press mentions including JAMA , Harvard Business Review , and Health Affairs .

Joel GohView profile

Associate Professor

• Health services and systems
• Transportation, logistics and supply chains
• Operations research
• +6 more

Joel Goh is Associate Professor at the Department of Analytics and Operations, NUS Business School, National University of Singapore. He serves as Director of the J.Y. Pillay Comparative Asia Research Centre (under NUS Global Asia Institute) and PhD Program Director at the Institute of Operations Research and Analytics (IORA). Previously, he was Assistant Professor at Harvard Business School (2014-2017) and Visiting Scholar (2017-2022). BSc, MSc, PhD in Operations, Information, and Technology from Stanford University His research focuses on healthcare analytics (preventing health conditions, hospital operations, frailty assessment), supply chain analytics (digital business models, platform leakage), and service platform operations (hospital-at-home programs, incentive design). He co-created the Robust Optimization Made Easy (ROME) software. Recent publications analyze workplace psychological safety (2024), hospital-at-home models (2024), and platform leakage dynamics (2023). His work spans 18+ journals with 740+ citations for burnout cost studies (2022) and 606+ citations for physician well-being research (2017). Teaching Honors : 2023: Best MBA Teaching & Skinner Innovation Award 2021: NUS Annual Teaching Excellence Award 2020: Early Career Research Excellence Award & 40 Under 40 Best MBA Professors Advising & Grants : Served as PhD Program Director. Received NUS Start-Up Grant R-314-000-110-133 (2021) and Humanities & Social Sciences Fellowship (2021). Editorial roles include Associate Editor at Management Science , Manufacturing & Service Operations Management , and Senior Editor at Production and Operations Management .

Robert MacCurdyView profile

Assistant Professor

• Automated robot design
• Additive manufacturing
• Soft robotics
• +6 more

Robert MacCurdy is an Assistant Professor at the Department of Mechanical Engineering, University of Colorado Boulder . He leads the Matter Assembly Computation Lab (MACLab) focused on automating robot design and fabrication. His research bridges computational design and advanced manufacturing to create "robots that walk out of the printer." The lab develops tools like OpenVCAD , an open-source volumetric multi-material geometry compiler.

Pieter AbbeelView profile

Professor

• Artificial Intelligence (AI)
• Robotics
• Machine Learning
• +5 more

Pieter Abbeel is a Professor in the Department of Electrical Engineering and Computer Sciences (EECS) at the University of California, Berkeley. He leads the Berkeley Robot Learning Lab and co-directs the Berkeley Artificial Intelligence Research (BAIR) Lab. His work focuses on advancing AI and robotics through deep reinforcement learning, imitation learning, and unsupervised learning, with applications in automation, healthcare, and education. Abbeel's research also explores the societal implications of AI and its potential to revolutionize other scientific and engineering fields. Education: Ph.D. in Computer Science, Stanford University (2008) M.S. in Electrical Engineering, KU Leuven, Belgium (2000) Research Interests: Robotics, AI, Machine Learning, Reinforcement Learning, Autonomous Systems, and Applications in Surgery, Manufacturing, and Education. Recent Article Trends: Focus on multimodal learning, robot manipulation, protein structure prediction, and scalable AI systems. Key areas include sim-to-real transfer, embodied AI, and foundation models for decision-making. Awards & Honors: IEEE Kiyo Tomiyasu Award (2022) ACM Prize in Computing (2021) IEEE Fellow (2018) MIT Tech Review TR35 (2011) Advising & Grants: Advises startups and has received grants from NSF, DARPA, and industry partnerships. Notable students include those advancing robotics, reinforcement learning, and bioAI. Labs & Initiatives: Berkeley Robot Learning Lab, BAIR Lab, and collaborations with the Center for Human-Compatible AI (CHAI). Founded companies include Gradescope, Covariant, and Berkeley Open Arms.

Subhasish MitraView profile

Professor

• Robust Computing
• NanoSystems
• Electronic Design Automation (EDA)
• +3 more

Subhasish Mitra is the William E. Ayer Professor of Electrical Engineering and Computer Science at Stanford University, holding dual appointments in both departments. He leads the Stanford Robust Systems Group and serves on the leadership team of the Microelectronics Commons AI Hardware Hub under the US CHIPS and Science Act. His research spans Robust Computing, NanoSystems, Electronic Design Automation (EDA), and Neurosciences, with breakthroughs in X-Compact test compression, carbon nanotube computing, and 3D integration. He has held international roles like the Carnot Chair at CEA-LETI and Visiting Professorships globally. Education & Honors: Recipient of over 40 awards including the IEEE Computer Society’s Harry H. Goode Memorial Award, ACM/IEEE’s A. Richard Newton Technical Impact Award, and the Intel Achievement Award. He earned top academic accolades from IIT Kharagpur and Jadavpur University, and is a Fellow of ACM and IEEE. Research Impact: Pioneered first-of-their-kind systems like the carbon nanotube computer and monolithic 3D integration. His work on robust computing techniques like QED validation and X-Compact compression has industry-wide adoption, saving billions in manufacturing costs. Collaborates with industry leaders like Intel, Google, and Samsung. Publications & Grants: Over 400 publications, including award-winning papers in DAC, ISSCC, and IEEE journals. Leads grants from NSF, DoE, and industry partnerships. His lab explores cutting-edge topics like neuromorphic computing, 3D thermal scaffolding, and AI hardware acceleration. Administration & Outreach: Serves as Associate Chair (Faculty Affairs) for Stanford’s Computer Science Department. Recognized by students for mentorship, and frequently invited to global forums like the World Economic Forum and National Academy of Engineering.

Jennifer WilcoxView profile

Professor

• Carbon Management
• Carbon Capture and Storage
• Direct Air Capture
• +6 more

Jennifer Wilcox is the Presidential Distinguished Professor of Chemical Engineering and Energy Policy at the University of Pennsylvania's School of Engineering and Applied Science. She holds the James H. Manning Chair and directs the Clean Energy Conversions Lab, which focuses on carbon management strategies to mitigate climate change. Wilcox also served as Principal Deputy Assistant Secretary of Fossil Energy and Carbon Management at the U.S. Department of Energy from January 2021. Her research spans carbon capture, utilization, and storage (CCUS), direct air capture (DAC), mineral carbonization, life cycle assessment, and techno-economic analysis of carbon management technologies. Wilcox's work examines both mitigation and adaptation strategies to minimize negative climate impacts associated with society's dependence on fossil fuels. She takes a multi-perspective approach that includes experimental work, materials characterization, geo-spatial analyses, systems modeling, and techno-economic analysis while considering environmental and social contexts. Wilcox's research has been featured in major publications including the first textbook on Carbon Capture and Storage, the California Getting to Neutral report, the CDR primer, Greenhouse Gas Removal Technologies, the State of CDR Volume 2, and the Roads to Removal report. Her work has received recognition including the DOE Secretary's Achievement Award for contributions to the Getting to Neutral report. Secretary's Achievement Award for work on the Getting to Neutral Report Principal Deputy Assistant Secretary of Fossil Energy and Carbon Management (2021) Author of the first textbook on Carbon Capture and Storage Lead contributor to the California Getting to Neutral report Co-author of the CDR primer with nearly 40 subject matter experts Wilcox mentors several PhD candidates and research associates including Maxwell Pisciotta, Shelvey Swett, Hélène Pilorgé, Shrey Patel, Aline Uwase, Katherine Vaz Gomes, and Abby Lunstrum. Her lab examines various carbon management strategies from technology development to deployment optimization, with a focus on maximizing climate change mitigation while minimizing adverse social and environmental impacts. The Clean Energy Conversions Lab tracks public funding for carbon management projects across the United States and analyzes lessons from recent legislation like the Bipartisan Infrastructure Law and Inflation Reduction Act to identify opportunities for carbon management.

Rakesh KumarView profile

Professor

• Computer Architecture
• System-Level Design Automation
• Low Power Computing
• +3 more

Rakesh Kumar is a Professor and John Bardeen Faculty Scholar in the Electrical and Computer Engineering Department at the University of Illinois at Urbana-Champaign. His work focuses on computer architecture, system-level design automation, and low-power computing. PhD in Computer Engineering from University of California, San Diego BS in Electrical Engineering from IIT Kharagpur His research spans all layers of the computing stack, with key contributions to flexible computer systems , waferscale computing , error-resilient architectures , and approximate computing . He has pioneered work on voltage-reliability tradeoffs and peak power management techniques. Recent publications highlight trends in space microdatacenters , printed microprocessors , and neural graph accelerators . His work on plastic chips was recognized as one of the three biggest semiconductor headlines of 2022 by IEEE Spectrum. IEEE Fellow (2024) ISCA Influential Paper Award MICRO Test-of-Time Award ICCAD Ten Year Retrospective Most Influential Paper Award Best Paper Awards at CASES, SELSE, HPCA He has received teaching accolades including the Stanley H. Pierce Faculty Award and Ronald W. Pratt Outstanding Teaching Award . His research group explores hardware-software co-design for emerging applications in AI, IoT, and sustainable computing.

• Data Mining
• Database Systems
• Explainable AI
• +5 more

Elena Maria Baralis is a Full Professor at the Department of Control and Computer Science (DAUIN) at the Polytechnic University of Turin. She serves as Pro-Rector, member of the Board of Directors (without voting rights), member of the Academic Senate (without voting rights), and coordinator of the University's Permanent Observatory for Monitoring the Academic Sector. She chairs the Control and Computer Engineering Department and previously chaired the Computer Engineering School from October 2012 to October 2018. Her research interests focus on database systems and data mining, specifically explainable AI, bias detection in data analytics, and machine learning algorithms for big data. Her work spans various application domains including predictive maintenance, Industry 4.0, and healthcare. Recent publications demonstrate her expertise in speech processing, bias mitigation, and innovative neural network architectures like Kolmogorov-Arnold Networks. Her research output shows a clear trend toward addressing fairness and explainability in AI systems while exploring novel approaches to speech and language understanding. Professor Baralis has received significant recognition including becoming a Fellow of the Academy of Sciences of Turin in 2017. She has served as Editor-in-Chief for IEEE Internet of Things Journal (2016-2019) and Knowledge and Information Systems (2014-present). She actively mentors doctoral students including Claudio Savelli (researching Machine Unlearning), Eleonora Poeta, Giuseppe Gallipoli, Alkis Koudounas, and others. Her research is supported by numerous projects including AI4CTI (Artificial Intelligence for Cyber Threat Intelligence, 2025-2028), Smart manufacturing driven by Machine Learning in Industry 4.0 (2019-2020), and I-REACT (2016-2019).

Michael J. AzizView profile

Professor

• Materials Science
• Energy Technologies
• Electrochemical Engineering
• +4 more

Michael J. Aziz is the Gene and Tracy Sykes Professor of Materials and Energy Technologies at Harvard University's John A. Paulson School of Engineering and Applied Sciences (SEAS). He serves as Area Chair for Materials Science and Mechanical Engineering and is a Faculty Associate at the Harvard University Center for the Environment. His research focuses on electrochemical engineering for energy and environmental applications, including redox flow batteries, carbon capture, and sustainable energy technologies. Aziz leads the Aziz Group, which develops grid-scale energy storage solutions and innovative methods for CO₂ removal. He holds equity in Quino Energy, a startup commercializing his battery research, and serves as Chief Scientist and Board Member. His work bridges fundamental materials science with practical engineering, emphasizing ClimateTech solutions. Key contributions include aqueous organic redox flow batteries, quinone-based carbon capture systems, and wearable energy storage devices. Education & Affiliations: Affiliated with SEAS since joining Harvard, his academic roles include coordinating the Graduate Consortium for Energy and Environment (2009–2018). His lab (Materials Science Group) is located at McKay 504, with administrative support from Sabrina Azinheira. Research Interests: Aziz's group investigates electrochemical energy storage, CO₂ capture via electrochemical systems, and novel materials for sustainable technologies. They employ advanced techniques like operando electrochemical fluorescence microscopy to study porous electrode dynamics and battery degradation mechanisms. Their work emphasizes scalability and real-world applicability, such as grid-scale battery infrastructure and decarbonization strategies. Recent Trends in Publications: Aziz's recent work emphasizes carbon capture innovations (e.g., acid-base concentration swing methods), hydrogen storage under ambient conditions, and electrochemical synthesis of industrial chemicals like hydrogen peroxide. His group also develops open-source tools like RFBzero for battery modeling and explores bioinspired materials (e.g., self-gelling hydrogel batteries). Awards & Recognition: While no personal awards are explicitly listed in the text, his team members (e.g., Dawei Xi) have received accolades such as the 2025 Carbon Future Young Investigator Award. Aziz's contributions have been recognized through industry partnerships and startup ventures. Advising & Industry Impact: Aziz advises PhD students focusing on electrochemical systems (e.g., Jordan Sosa, Tommy George). His industry engagement includes licensing intellectual property to Quino Energy, which achieved a manufacturing milestone in 2024 for grid-scale battery systems. His research bridges academia and industry, addressing climate challenges through technological innovation. Labs & Teams: The Aziz Group includes interdisciplinary researchers from electrochemistry, chemical engineering, and materials science. Collaborators include institutions like MIT and industry partners. Current projects target next-gen batteries, CO₂ removal systems, and scalable energy storage solutions.

Gonzalo Guillén GosálbezView profile

Professor

• Process Systems Engineering
• Sustainable Chemistry
• Environmental Impact Assessment
• +7 more

Prof. Dr. Gonzalo Guillén Gosálbez is a Full Professor at the Department of Chemistry and Applied Biosciences , ETH Zürich. He holds a PhD in Process Systems Engineering (UPC, 2005) and has held academic positions at Imperial College London (Reader), University of Manchester (Senior Lecturer), and Universitat Rovira i Virgili (Assistant/Associate Professor). His research focuses on Sustainable Chemical Processes , integrating life cycle assessment, optimization techniques, and planetary boundary analysis to evaluate and design low-carbon technologies. Current position: Full Professor, ETH Zürich (2019–present) Prior roles: Imperial College London (2016–2019), University of Manchester (2014–2016), URV Spain (2008–2014) Education: PhD (UPC, 2005), MEng/BEng (University of Murcia) His research explores CO2 valorization , green methanol synthesis , circular marine fuels , and planetary boundary compliance in energy and chemical systems. Recent work emphasizes machine learning for process modeling, single-atom catalysis , and decentralized ammonia production . Scientific contributions include 15+ peer-reviewed articles (2023–2025) in journals like Nature Chemical Engineering , ACS Sustainable Chemistry & Engineering , and Energy & Environmental Science . Key themes: Optimization of hybrid fossil/renewable carbon systems Environmental impacts of energy transitions Catalyst design for sustainable chemistry Life cycle assessment of emerging technologies Awarded UPC Top Doctoral Student Award and Top National Student Award , he combines process systems engineering with sustainability metrics to address global challenges in chemical and energy systems.

Henry MossView profile

Researcher

• Machine Learning
• Bayesian Optimization
• Theoretical Physics
• +3 more

Dr Henry Moss is a Researcher at the Department of Applied Mathematics and Theoretical Physics within the School of Physical Sciences at the University of Cambridge. His work focuses on machine learning applications in climate modeling, Bayesian optimization, and Gaussian processes, bridging computational mathematics with environmental science and chemistry. His research interests include: Bayesian optimization for environmental and chemical systems Reinforcement learning in climate modeling Gaussian processes for molecular property prediction High-throughput machine learning in scientific domains Interpretable AI for coastal flooding prediction Hybrid ML-physics modeling Dr Moss's publications highlight his contributions to federated learning for climate models, sparse Gaussian process techniques, and multi-objective optimization frameworks. These works span applications in weather prediction, chemical engineering, and oceanography. Email: hwm26@cam.ac.uk

Vikramaditya G. YadavView profile

Associate Professor

• Biocatalysis
• Bioremediation
• Bioprocess engineering
• +15 more

Vikramaditya G. Yadav is an Associate Professor at the University of British Columbia (UBC) in the Department of Chemical and Biological Engineering, Faculty of Applied Science. He directs the Master of Engineering Leadership (MEL) Program in Sustainable Process Engineering and leads the BioFoundry research group. Education: B.A.Sc., University of Waterloo (2007) Ph.D., Massachusetts Institute of Technology (2013) Postdoctoral Associate, Harvard University (2014) His research spans sustainable chemical manufacturing, metabolic engineering, and biotechnology. Key areas include: Designing biosynthetic enzymes for biomass valorization Developing bioremediation strategies for industrial water quality Creating innovative drug delivery systems and tissue engineering solutions Advancing synthetic biology for pharmaceutical and bioenergy applications His recent work focuses on ocular drug delivery, cannabinoid biosynthesis in E. coli, lignin-based nanoparticles for cancer therapy, and computational analysis of plant secondary metabolites. Collaborations with start-ups, industry, and medical labs drive innovation in Canada's bioeconomy. Professional Leadership: Chair, Biotechnology Division of the Chemical Institute of Canada Associate Editor, The Canadian Journal of Chemical Engineering He is affiliated with UBC's BioProducts Institute and contributes to project-based learning pedagogy.

Animesh GargView profile

Assistant Professor

• Robotics
• Reinforcement Learning
• Artificial Intelligence
• +3 more

Animesh Garg is an Assistant Professor at the School of Interactive Computing at Georgia Tech, where he leads the People, AI, and Robotics (PAIR) research group . He holds a Senior Researcher position at Nvidia Research and has courtesy appointments at the University of Toronto and Vector Institute. Previously, he served as Chief Scientific Officer at Apptronik (2024-2025) and Senior Staff Research Scientist at Nvidia Research (2018-2024). Education : Ph.D. in Operations Research from UC Berkeley (2011-2016), MS in Computer Science and Industrial Engineering from Georgia Tech and University of Delhi. Research Focus : Building Generalizable Autonomy through Reinforcement Learning , Control Theory , and 3D Vision , with applications in Surgical Robotics , Self-Driving Labs , and Manufacturing . Key Article Themes : His recent work emphasizes Foundation Models for robotics, Differentiable Simulation , Language-Guided Autonomy , and Structured Inductive Biases in sequential decision-making. Scientific Awards : Stephen Fleming Early Career Professorship at Georgia Tech. Teaching : Courses on AI, Deep Reinforcement Learning, and Algorithmic Intelligence in Robotics at Georgia Tech. Labs & Collaborations : Affiliated with Institute for Robotics and Intelligent Machines (IRIM) and ML@GT at Georgia Tech; collaborates intensively with Nvidia Robotics.

• Mechanical Engineering
• Additive Manufacturing
• 3D-Printing
• +2 more

Jouni Partanen is a Professor at Aalto University's Department of Energy and Mechanical Engineering within the College of Engineering. His research focuses on advanced production technologies including Additive Manufacturing (3D-Printing), modern laser processing, and micromachining. Research Group: Materiaaleista tuotteiksi Specialization: Integration of AI in manufacturing processes Sustainability emphasis: Biochar-reinforced materials and carbon footprint reduction His work spans from fundamental material behavior analysis to industrial applications, particularly in metal additive manufacturing and composite fabrication. Recent research explores corrosion resistance in lattice structures and multiscale photopolymerization techniques. Publications highlight interdisciplinary approaches combining mechanical engineering with biomedical applications (e.g., patient-specific implants) and environmental health studies on industrial 3D printing emissions.

• Aerospace Composites
• Damage Tolerance Analysis
• Impact Mechanics
• +3 more

Dr Andrew Rhead is a Senior Lecturer in the Department of Mechanical Engineering at the University of Bath, specializing in aerospace composites and damage tolerance analysis. His research focuses on impact damage detection, failure mechanism modeling, and Non-Destructive Evaluation (NDE) techniques for composite structures. MSci in Mathematical Sciences (Dynamical Systems) - University of Bristol (2006) PhD in Composite Damage Tolerance - University of Bath (2009) His work develops computationally efficient analytical models for compression after impact (CAI) strength prediction in composite laminates, surpassing traditional finite element methods. Key projects include hydrogen storage systems for aircraft, cryogenic composite testing, and steered fiber manufacturing optimization. Active in 10 projects including ASPIRE and HyFIVE Collaborates with Airbus, GKN Aerospace, and EPSRC Research trends show emphasis on sustainable aviation materials, structural battery integration, and advanced testing methodologies. Current affiliations include the Institute for Mathematical Innovation (IMI) and Centre for Integrated Materials, Processes & Structures (IMPS).