Dr. V.M. (Bala) Balasubramaniam is a Professor in the Department of Food Science and Technology at The Ohio State University. He holds editorial roles in food engineering journals and is a Fellow of IFT and IUFoST. His research focuses on clean food manufacturing technologies, particularly high-pressure and nonthermal methods, emphasizing microbial inactivation and nutrient preservation. He teaches unit operations in food engineering and contributes to industry via short courses and pilot plant demonstrations. Education: B.S. (Tamil Nadu Agricultural University), M.S. (Asian Institute of Technology), Ph.D. (Ohio State University). Research Interests: Thermal/nonthermal processing, food safety/quality modeling, and innovative applications of high-pressure technologies. Recent work includes ultra-shear technology development and superheated steam sanitation. Over 100 scientific papers, 20 book chapters, and co-edited books on high-pressure processing. Awards include the 2021 IFT Research & Development Award and 2017 Calvert L. Willey Award. Advising: Supervises graduate students like Liz Astorga Oquendo and Shruthy Seshadrinathan. Industrial outreach includes a USDA consortium for ultra-shear commercialization. Labs/teams focus on pilot-scale equipment testing and microbial efficacy studies.
Caroline Lemieux is an Assistant Professor at the Department of Computer Science, University of British Columbia (UBC), with research focused on advancing software correctness, security, and performance through innovative testing and synthesis techniques. Her work bridges Programming Languages and Software Engineering , particularly in fuzz testing, specification mining, and program synthesis. PhD from University of California, Berkeley (2021), advised by Koushik Sen Postdoctoral researcher at Microsoft Research, NYC (2021-2022) Key contributions: FuzzFactory , CodaMOSA , Arvada , and Gauss Her research integrates machine learning with traditional testing methods, exemplified by projects like RLCheck (reinforcement learning for test generation) and AutoPandas (neural synthesis for dataframes). Recent publications analyze generator-based fuzzing challenges and propose hybrid strategies combining coverage feedback with AI-driven insights. Scientific Awards : ACM/SIGSOFT Best Paper Award (ESEC/FSE 2019) ACM/SIGSOFT Tool Demonstration Award (ISSTA 2019) ACM/SIGSOFT Distinguished Artifact Award (ISSTA 2019) NSERC Postgraduate Scholarship-Doctoral (PGS D) UBC Governor General's Silver Medal (2016) Teaching roles include: 2025W2: CPSC 539L - Topics in Programming Languages 2024W2: CPSC 410 - Advanced Software Engineering 2023W2: CPSC 410 (with Alex Summers) She supervises graduate and undergraduate researchers working on projects like ExploTest (automated unit test generation) and GRIMOIRE (grammar extraction from pseudo-rules). Her research team collaborates with institutions including Microsoft Research, Google, and academic partners in systems security and AI-driven testing.
Georgia Zellou is an Associate Professor in the Department of Linguistics at the University of California, Davis, where she co-directs the Phonetics Lab and conducts award-winning research at the intersection of phonetics, speech perception, and human-AI interaction. Her work investigates how phonetic detail is cognitively represented through variations in speech production, with significant contributions to understanding speech alignment with voice assistants, face-masked speech intelligibility, and cross-linguistic perception of synthetic voices. Her academic credentials include a Ph.D. in Linguistics from the University of Colorado at Boulder (2012), an M.A. in Linguistics from Stony Brook University (2007), and a B.A. in Linguistics & Anthropology from the University of Florida (2005, Cum Laude, Phi Beta Kappa). Ph.D., Linguistics, University of Colorado at Boulder (2012) M.A., Linguistics, Stony Brook University (2007) B.A., Linguistics & Anthropology, University of Florida (2005) Professor Zellou's research program centers on laboratory phonology approaches to real-world communication challenges, examining how acoustic-phonetic details influence speech perception across contexts. Her studies span speech alignment with voice-AI systems (e.g., Amazon Alexa), sociophonetic variation in bilingual speech, and the cognitive mechanisms underlying perceptual compensation for coarticulation. She employs experimental methods including eye-tracking, acoustic analysis, and perceptual testing to uncover how phonetic variation functions pragmatically in human communication and human-machine interaction. Analysis of her 15 most recent publications (2023-2025) reveals three dominant research trajectories: (1) human-AI voice interaction dynamics, including prosodic alignment and social evaluation of TTS voices; (2) intelligibility optimization in challenging contexts (face masks, clear speech for diverse listeners); and (3) cross-linguistic phonetic variation in vowelless words and consonant clusters. These works consistently bridge theoretical phonology with applied speech technology, demonstrating how fine-grained phonetic detail influences communication effectiveness in both human-human and human-machine contexts. Her scientific recognition includes: Fulbright Scholar (2022) for research in France Chancellor’s Award for Excellence in Undergraduate Mentoring (2019) Fellow of the Linguistic Society of America (2020) Amazon Faculty Research Award (2019) for Alexa-related speech studies Dean’s Fellow designation at UC Davis (2020-2023) Professor Zellou maintains an active mentoring practice recognized with the Chancellor’s Award, supervising undergraduate researchers in the Phonetics Lab while teaching core linguistics courses from introductory to advanced graduate levels. Her research program is supported by competitive grants including NSF funding, Amazon Research Awards, and UC Davis internal grants (Hellman Foundation, ISS Junior Faculty Grant), reflecting the translational value of her work for speech technology development. She has co-directed major initiatives including the 2019 LSA Linguistic Institute. The Phonetics Lab she co-leads serves as a hub for experimental phonetics research, focusing on speech production-perception relationships through projects investigating vocal accommodation to voice assistants, nasal coarticulation dynamics, and cross-linguistic prosody. Current collaborations with industry partners aim to implement human speech adaptation principles into voice assistant design to enhance naturalness and engagement.
Hazel Rose Markus is the Davis-Brack Professor in the Behavioral Sciences at Stanford University's Department of Psychology within the School of Humanities and Sciences. With a distinguished career spanning decades, she has made significant contributions to cultural psychology and the understanding of how social contexts shape self and behavior. Her work bridges academic research and practical application through her role as Faculty Director of Stanford SPARQ. Markus received her B.A. from California State University at San Diego and her Ph.D. from the University of Michigan in Psychology. Her educational background laid the foundation for her groundbreaking work in cultural psychology. Her research focuses on the role of self in regulating behavior and how the social world shapes the self. She investigates people as culturally-shaped shapers of their cultures, examining how nation or region of origin, gender, social class, race, ethnicity, religion, and occupation shape thought, feeling, and action. Her work spans multiple domains including education, healthcare, workplace environments, and social policy. Analysis of her recent publications reveals a consistent focus on cultural frameworks, particularly examining independence-interdependence cultural models. Her research increasingly addresses social inequality, educational disparities, and systemic bias through empirical studies and intervention development. She has pioneered the Culture Cycle Framework for understanding and changing cultural patterns that perpetuate inequality. Member of the National Academy of Sciences Member of the British Academy Fellow of the American Academy of Arts and Sciences American Psychological Association's Distinguished Scientific Contribution Award Donald T. Campbell Award from SPSP APS William James Award for lifetime achievement Markus actively mentors doctoral students and postdoctoral scholars, with current advisees including Leslie Remache, Enna Chen, Ayo Dada, and Efrain Garcia Sanchez. She teaches courses including Graduate Seminar in Social Psychology Research, Intergroup Communication Facilitation, and Mind, Culture, and Society. As Faculty Director of Stanford SPARQ, she leads initiatives that partner with industry leaders to tackle disparities and inspire culture change in criminal justice, economic mobility, education, and health. Her laboratory work focuses on cultural psychology, examining how cultural contexts shape cognition, emotion, and behavior across diverse populations. Through SPARQ, she connects academic research with real-world applications to address societal challenges.
Dr. Amir Hakami is a Professor in the Department of Civil & Environmental Engineering at Carleton University , where he leads the Carleton Atmospheric Modelling Group . His research focuses on advanced air quality modeling techniques to inform environmental policy. Degrees: B.Sc. (Polytechnic of Tehran), M.Sc., Ph.D. (Georgia Tech), Postdoc (Caltech) Contact: Office 3454 Mackenzie Building, Phone: 613-520-2600 ext. 8609, Email: amir.hakami@carleton.ca Research Interests: Air quality modeling at multiple spatial scales Adjoint sensitivity analysis for atmospheric response Inverse modeling and data assimilation techniques Uncertainty quantification in environmental systems Interdisciplinary applications in policy, public health, and economics Teaching: Courses include Environmental Engineering Systems Modeling , Contaminant Transport , and Air Pollution & Emissions Control at undergraduate and graduate levels. Research Group: The group includes Ph.D. candidates, postdoctoral fellows, and alumni working on topics ranging from atmospheric chemistry to sustainable energy systems. Members come from diverse backgrounds in engineering, science, and policy disciplines.
Alexei A. Efros is the Howard Friesen Professor in the EECS Department at UC Berkeley, affiliated with the Berkeley Artificial Intelligence Research (BAIR) Lab. Previously, he spent a decade at CMU's Robotics Institute and held a postdoc at the University of Oxford under Andrew Zisserman. He collaborates with INRIA/École Normale Supérieure in Paris. His research focuses on self-supervised learning, generative models, and visual data mining, with applications to robotics, computational photography, and art. Education & Academic Roles: Postdoc at Oxford (with Andrew Zisserman), faculty at CMU (2005–2015), currently at UC Berkeley. Teaches courses like CS 180/280A (Computer Vision) and CS 280 (Graduate Computer Vision). Research Interests: Self-supervised learning, generative models (e.g., diffusion models, inpainting), visual commonsense, and cross-modal reasoning. His work bridges computer vision and graphics, emphasizing data-driven approaches. Recent projects include Visual Jenga, Diffusion Models as Data Mining Tools, and Prioritized Generative Replay. Grants & Labs: Leads the Efros Research Group, advised over 40 PhD students (e.g., Jun-Yan Zhu, Tinghui Zhou). Collaborates with institutions like INRIA and NVIDIA. Active in grants related to AI, vision, and robotics. Labs/Teams: BAIR Lab (UC Berkeley), former affiliations with CMU Robotics Institute and Willow Team (INRIA/ENS Paris). Current lab focuses on generative AI, 3D perception, and visual reasoning.
Dr. Steven H. H. Ding is an Assistant Professor at McGill University's School of Information Studies, specializing in cybersecurity, machine learning, and data mining. His research focuses on AI-driven solutions for malware detection, software vulnerability analysis, and reverse engineering. He holds a PhD from McGill University and has been supported by BlackBerry Cylance and DRDC. His work bridges theoretical advancements with practical applications in military systems and avionics cybersecurity. Dr. Ding earned his PhD in 2019 with notable awards including the FRQNT Doctoral Research Scholarship and McGill's Dean’s Graduate Award. His educational background includes degrees from McGill, Concordia University, and the University of Shanghai for Science and Technology. His research interests span cybersecurity domains such as zero-day malware identification, code obfuscation countermeasures, authorship verification for digital forensics, and AI applications in avionics anomaly detection. He actively contributes to open-source tools like the Kam1n0 MapReduce-based assembly clone search system. Recent work emphasizes adversarial machine learning for evasive malware generation, transformer-based anomaly detection in avionics, and automated SBOM generation for firmware analysis. His publications reflect a focus on real-world cybersecurity challenges in both civilian and defense sectors. Dr. Ding leads the L1NNA Lab and collaborates with industry partners on cutting-edge projects. His contributions include novel techniques for phishing detection leveraging large language models and innovative approaches to reverse engineering software composition in JavaScript applications.
Joshua B. Gross is an Associate Professor in the Department of Biological Sciences at the University of Cincinnati, where he has been conducting research since 2010. His work focuses on evolutionary biology, particularly using the Mexican cavefish ( Astyanax mexicanus ) as a model system to study adaptation to extreme environments. Dr. Gross received his academic training at prestigious institutions: Ph.D. in Organismic and Evolutionary Biology from Harvard University (2005) M.S. with Distinction in Biological Sciences from University of Denver (2001) B.A. in Psychology from Miami University (1995) Dr. Gross's research explores the genetic and developmental basis of evolutionary changes, with a focus on how organisms adapt to extreme environments. His primary model system is the Mexican cavefish ( Astyanax mexicanus ), which exists in both surface-dwelling (with eyes and pigmentation) and cave-dwelling (blind and depigmented) forms. His work integrates quantitative genetics, transcriptomics, and phenotypic analysis to understand the genetic changes underlying cave adaptation, including both regressive traits (like eye loss) and constructive traits (like enhanced taste systems). Analysis of Dr. Gross's recent publications reveals a strong focus on sensory adaptation and craniofacial evolution in cavefish. His work has increasingly incorporated genomic and transcriptomic approaches to understand how cavefish adapt to low-oxygen environments, changes in sensory systems (particularly taste and lateral line), and craniofacial modifications. There's a clear trajectory toward understanding the integration between different biological systems, such as how sensory neuromasts influence skeletal development. Dr. Gross has received several notable awards and recognitions: National Academies Education Fellow in the Life Sciences (2014-2015) Young Investigator Winner, Sigma Xi, University of Cincinnati Chapter (2016) Honorable Mention, Excellence in Doctoral Mentoring Award Nominated for 2018 Dean's Award for Innovative Instruction Young Anatomist's Publication Award from the American Association of Anatomists (2004) As a principal investigator, Dr. Gross has secured substantial funding from the National Science Foundation and National Institutes of Health, including multiple R01 grants from NIH and major awards from NSF. His current projects include "The developmental basis for sensory-skeletal integration: The osteo-inductive role of neuromasts" (NSF IOS-2205928, 2022-2026) and "The constructive evolution of gustation: Molecular, organismal and environmental attributes of taste tuning" (NSF DEB-2343857, 2024-2028). He has mentored numerous undergraduate and graduate students through research projects and has been recognized for his teaching excellence, particularly in Human Genetics. Dr. Gross leads a research laboratory focused on evolutionary and developmental biology at the University of Cincinnati. His team employs a multidisciplinary approach combining field work in Mexican caves, laboratory experiments, genomic analysis, and developmental studies. He has organized international scientific meetings, including the Astyanax International Meeting, fostering collaboration among researchers studying cave-adapted organisms worldwide.
Joshua Gess is an Associate Professor in the Mechanical, Industrial, and Manufacturing Engineering department at Oregon State University's College of Engineering. He joined Oregon State in 2015 and serves as a co-principal investigator at the Enhanced Heat Transfer Laboratory, where he leads research in thermal management solutions for high-performance microelectronics. His educational background includes: PhD, Mechanical Engineering, Auburn University, 2015 MS, Mechanical Engineering, Auburn University, 2012 B.E., Mechanical Engineering, Vanderbilt University, 2005 Before academia, he worked as a mechanical engineer at SSOE Group (including consulting for Johns Manville) and Northrop Grumman where he focused on military communication equipment. Professor Gess specializes in advancing thermal management solutions for high-performance microelectronic equipment. His research spans multiple scales, examining single and two-phase heat transfer on the macro-scale with passive and active liquid immersion techniques, as well as on the micro and nano scale for complex embedded thermal management solutions. He combines fundamental heat transfer knowledge with novel experimental methods such as two-phase PIV and high-speed image capture to develop reliable and energy-efficient cooling solutions for demanding electronics systems. His publication record demonstrates a clear trajectory toward increasingly sophisticated thermal management solutions, with recent work focusing on additive manufacturing applications for cooling systems, semiconductor thermal management, and nuclear reactor cooling systems. His research has significant implications for data center energy efficiency, where even small improvements in cooling efficiency could save enormous amounts of energy that could be returned to the grid. Gess is deeply committed to mentoring graduate students, emphasizing the practical applications of engineering principles. He attributes his interest in engineering to childhood influences like the movie RoboCop and the TV series MacGyver, and finds the reality of engineering work just as gratifying as he'd imagined. He particularly values the moments when his graduate students "get it" and watching them grow with each new accomplishment. As a person with a disability himself, Gess is passionate about establishing more robust support systems for people with disabilities at Oregon State. He is working with the School of Public Health to start an adaptive sports program, with the goal of building infrastructure that allows anyone to feel welcome and pursue advanced degrees at the university.
Laura E. Brumariu is a Professor and Associate Dean for Professional Programs and Student Advancement at the Gordon F. Derner School of Psychology, Adelphi University. She holds a Ph.D. from Kent State University and completed postdoctoral research fellowships at Harvard Medical School. Her office is located in the Hy Weinberg Center, and she is licensed as a psychologist in New York State. Education: Postdoctoral Research Fellow, Harvard Medical School/CHA/MGA (2013) Postdoctoral Research Fellow with Clinical Attributions, Cambridge Health Alliance/Harvard Medical School (2012) Ph.D., Kent State University (2010) Her research adopts a developmental psychopathology perspective, focusing on how parent-child attachment influences emotional and social development, particularly in middle childhood. She investigates emotion regulation, anxiety, disorganized attachment, role-confusion, and family processes related to borderline personality features and dissociation. She developed the Middle Childhood Attachment Strategies Coding System and leads the Child and Adolescent Research (CARE) Lab. Her recent work emphasizes meta-analytic reviews on emotion socialization, attachment, anxiety, and empathy. Her most recent publications reflect trends in attachment theory, emotion regulation, parenting, and internalizing disorders across development, often using meta-analytic and longitudinal methods. Much of her work integrates international collaboration, especially with Romanian researchers. Scientific Awards and Honors: Clinical Research Training Program, Harvard Medical School, Research Fellow (2010–2012) The Jeanette and Louis Reuter Fellowship in Developmental Sciences, Kent State University (2008–2009) She has mentored numerous doctoral students whose research spans topics such as gratitude, empathy, emotion socialization, and trauma. She teaches courses in psychological research, family therapy, and doctoral thesis supervision. She has secured research funding and collaborates extensively on studies related to child and adolescent mental health, though specific grants are not detailed in the text. Her professional activities include frequent presentations at major psychological conferences such as the Association for Psychological Science and the International Attachment Conference. Labs and Research Teams: She directs the Child and Adolescent Research (CARE) Lab at Adelphi University, which focuses on attachment, emotion regulation, and psychopathology in children and adolescents. The lab conducts both observational and survey-based research and trains graduate students in developmental and clinical methods.
Brendan T. O'Connor is an Associate Professor at the College of Information and Computer Sciences, University of Massachusetts Amherst, where he directs the SLANG Lab and serves as Associate Director of the Computational Social Science Institute. His research bridges statistical machine learning and natural language processing with social science applications, particularly using text data from news and social media to understand societal patterns. His work focuses on developing text analysis methods to answer social science questions in domains like political science and sociolinguistics. Current collaborative projects include combating misinformation, analyzing bias in news coverage, and developing tools for clinical discourse assessment using large language models. O'Connor's publications demonstrate a consistent focus on computational social science, with recent work exploring multilingual analysis, legal discourse patterns, and sociolinguistic variation. His methodological contributions span coreference resolution, event extraction, and argument mining. At UMass, he contributes to multiple research centers including the Computational Social Science Institute, UMass NLP group, and Centers for Data Science and Intelligent Information Retrieval. He teaches graduate seminars in natural language processing and maintains active collaborations across disciplines.
Alexander R. Pruss is a tenured Professor in the Department of Philosophy at Baylor University , within the College of Arts and Sciences . He holds a dual PhD in Philosophy (University of Pittsburgh, 2001) and Mathematics (University of British Columbia, 1996), and has held previous academic positions at Georgetown University. His work is deeply interdisciplinary, bridging metaphysics, philosophy of religion, formal epistemology, and ethics. Education: Ph.D. in Philosophy, University of Pittsburgh (2001) Ph.D. in Mathematics, University of British Columbia (1996) B.Sc. (Hon.) in Mathematics and Physics, University of Western Ontario (1991) Pruss’s research interests include metaphysics—particularly the Principle of Sufficient Reason , modality , and infinity —philosophy of religion, divine attributes , cosmological arguments , and sexual ethics . He is known for integrating rigorous formal methods with classical theistic metaphysics. His recent publications explore the intersection of probability theory, paradox, and theology, particularly in infinite domains. He has authored influential books such as The Principle of Sufficient Reason: A Reassessment (2006), Infinity, Causation and Paradox (2018), and One Body: An Essay in Christian Sexual Ethics (2012). The trends in his recent articles show a sustained focus on the philosophical implications of infinity, symmetry, and probability. He frequently investigates paradoxes in probability (e.g., infinite lotteries), challenges to modal realism, and the metaphysical coherence of divine attributes. His work combines analytic rigor with theological depth, often aiming to defend classical theism through logical and mathematical reasoning. Scientific awards and honors: Aquinas Medal, American Catholic Philosophical Association (2025) Wilde Lecturer, Oriel College, University of Oxford (2019) Outstanding Tenured Faculty Research Award, College of Arts and Sciences (2013) National Endowment for the Humanities Summer Stipend (2002) Social Sciences and Humanities Research Council of Canada Fellowship (1997–2000) Pruss has been actively involved in academic service, including serving on the Executive Council of the American Catholic Philosophical Association (2021–2024) and the Society of Christian Philosophers (2011–2013) . He has held editorial roles for journals such as American Philosophical Quarterly and Analysis and Existence . He has delivered numerous invited lectures globally, including at Oxford, Notre Dame, and MIT. There is no mention of formal PhD or Master’s students in the provided text, but he advises through graduate seminars and research supervision. He has not received specific grant mentions beyond fellowships and stipends. He is affiliated with research groups such as the Baylor Institute for Faith and Learning and the Thomistic Institute , and contributes to philosophy of science and theology dialogues. His work continues to shape contemporary debates in analytic philosophy of religion and metaphysics.
Mohammad Mohammadi Amiri serves as an Assistant Professor in the Department of Computer Science at Rensselaer Polytechnic Institute (RPI), appointed in Fall 2023. His research focuses on advancing artificial intelligence through strategic data utilization, with emphasis on large language models, data valuation, federated learning, and deep learning. Previously, he held postdoctoral appointments at Princeton University and MIT Media Lab, building on his strong educational foundation from Imperial College London, University of Tehran, and Iran University of Science and Technology. Education: Ph.D. in Electrical and Electronic Engineering, Imperial College London (2019) - Best Ph.D. Thesis Award recipient M.Sc. in Electrical and Computer Engineering, University of Tehran (2014) - Ranked 1st among all M.Sc. students B.Sc. in Electrical Engineering, Iran University of Science and Technology (2011) - Ranked 1st among all B.Sc. students Dr. Amiri's research centers on optimizing artificial intelligence systems through innovative data strategies. His work addresses critical challenges in large language models including efficiency, memory usage, alignment, and reasoning capabilities. In data valuation, he develops principled methods to quantify data worth for fair trading platforms. His federated learning research tackles privacy concerns, heterogeneous data distribution, and communication overhead in decentralized environments. The deep learning component explores theoretical foundations to improve model interpretability and robustness. Analysis of his recent publications reveals a strong focus on making AI systems more efficient and accessible, with particular emphasis on large language model optimization, federated learning advancements, and data valuation frameworks. His work bridges theoretical foundations with practical applications in wireless communications and distributed computing environments. Scientific Awards: IEEE Communications Society Young Author Best Paper Award (2022) Best PhD Thesis Award from IEEE Information Theory Chapter of UK and Ireland (2019) Eryl Cadwallader Davies Prize for Outstanding PhD Thesis (2019) EEE Departmental Scholarship at Imperial College London (2015-2019) Ranked 1st among M.Sc. students at University of Tehran (2014) Ranked 1st among B.Sc. students at Iran University of Science and Technology (2011) Dr. Amiri actively mentors graduate students, currently supervising five Ph.D. candidates and one M.Sc. student working on efficient LLM fine-tuning, inference, and storage. His research has attracted significant attention, evidenced by numerous keynote invitations at prestigious institutions including Bell Labs, MIT, King's College London, and various IEEE conferences. He serves on program committees for major conferences including IEEE Globecom and ICC, demonstrating his growing influence in the academic community. His research group operates at the intersection of machine learning and wireless communications, developing innovative solutions for resource-constrained environments while addressing fundamental theoretical challenges in AI systems. Current projects focus on making advanced AI more scalable and accessible through efficiency improvements in model training and inference.
Ruth Fong is a Teaching Professor at the Department of Computer Science, Princeton University , where she teaches foundational and advanced AI/ML courses (COS324, COS126) while leading the Looking Glass Lab in explainable AI research. She collaborates closely with the Visual AI Lab and Professor Olga Russakovsky . Education: PhD in Visual Geometry Group, University of Oxford (advised by Andrea Vedaldi , funded by Rhodes Trust and Open Philanthropy ) MSc in Neuroscience, University of Oxford (with Rafal Bogacz , Ben Willmore , and Nicol Harper ) AB in Computer Science, Harvard University (with David Cox and Walter Scheirer ) Research Focus: Pioneering Explainable AI and ML Fairness , with emphasis on post-hoc model understanding, interpretable-by-design architectures, and human-AI interaction frameworks. Her work spans computer vision, self-supervised learning, and neuroscience-inspired methodologies. Publication Trends: Recent papers (2023-2025) analyze interactive explanations , concept salience , and gender artifacts in vision datasets . Earlier work (2017-2020) established foundational techniques in extremal perturbations , backpropagation saliency , and neural network interpretability . Scientific Awards: Princeton Engineering Council Teaching Award (2025) Keller Center Summer Course Development Grant (2025) CHI Honorable Mention Paper Award (2023) Open Philanthropy AI Fellowship (2018) Rhodes Scholarship (2015) Advising: Directly mentored 10 Princeton undergraduates on IW/senior theses projects spanning generative AI , medical imaging fairness , and interactive visualization tools . Grants include Princeton SEAS and Open Philanthropy funding for the Looking Glass Lab. Lab & Team: Leads the Looking Glass Lab with 6 graduate/postgraduate members including Rawand Aziz , Matthew Barrett , and Ben Wachspress . Collaborates with faculty across Princeton and Oxford.
Melissa Koenig serves as Professor and Director of Graduate Studies at the University of Minnesota's Institute of Child Development (ICD), where her research examines social and testimonial learning mechanisms in children through investigations of trust, cultural learning, memory, language, and cognitive development. As a first-generation college student, she prioritizes supporting students navigating academic systems through collaborative mentorship. Education PhD (2002), University of Texas at Austin Her research program spans cognitive development, cross-cultural studies, early childhood, language acquisition, theory of mind, and social-emotional development across peer, parent, and romantic contexts. The lab employs interdisciplinary, multi-method approaches with explicit cultural analysis to advance developmental science, particularly examining how children evaluate information sources and integrate testimony into moral frameworks. Analysis of her 2021-2024 publications reveals dominant themes in epistemic trust development, including how children assess informant credibility through moral behavior, group affiliation, and cultural context. Key trajectories show increasing sophistication in distinguishing epistemic versus practical reasoning, cross-cultural variations in trust attribution, and the developmental emergence of resistance to power-based corruption like bribery. Advising & Mentorship Accepts new PhD students for Fall 2026 cohort Requires prospective students to contact prior to December 1 application deadline Public advising statement details mutual expectations and support structures Specializes in guiding students through academic navigation and hidden curriculum challenges She directs the Early Language and Experience Lab, which maintains a collaborative research environment focused on uncovering constraints and supports for children's social learning across diverse contexts, with particular attention to cultural and socioeconomic variables in developmental processes.
